From 1eefe156c56861ac4f637bd7a6c3983ce0c9b311 Mon Sep 17 00:00:00 2001 From: LukasMasuch Date: Thu, 5 Sep 2024 15:53:36 +0000 Subject: [PATCH] Update best-of list for version 2024.09.05 --- README.md | 6007 +++++++++++++++---------------- history/2024-09-05_changes.md | 36 + history/2024-09-05_projects.csv | 919 +++++ latest-changes.md | 46 +- 4 files changed, 3919 insertions(+), 3089 deletions(-) create mode 100644 history/2024-09-05_changes.md create mode 100644 history/2024-09-05_projects.csv diff --git a/README.md b/README.md index 93a668e..3a92000 100644 --- a/README.md +++ b/README.md @@ -17,7 +17,7 @@

-This curated list contains 920 awesome open-source projects with a total of 4.5M stars grouped into 34 categories. All projects are ranked by a project-quality score, which is calculated based on various metrics automatically collected from GitHub and different package managers. If you like to add or update projects, feel free to open an [issue](https://github.com/ml-tooling/best-of-ml-python/issues/new/choose), submit a [pull request](https://github.com/ml-tooling/best-of-ml-python/pulls), or directly edit the [projects.yaml](https://github.com/ml-tooling/best-of-ml-python/edit/main/projects.yaml). Contributions are very welcome! +This curated list contains 920 awesome open-source projects with a total of 4.6M stars grouped into 34 categories. All projects are ranked by a project-quality score, which is calculated based on various metrics automatically collected from GitHub and different package managers. If you like to add or update projects, feel free to open an [issue](https://github.com/ml-tooling/best-of-ml-python/issues/new/choose), submit a [pull request](https://github.com/ml-tooling/best-of-ml-python/pulls), or directly edit the [projects.yaml](https://github.com/ml-tooling/best-of-ml-python/edit/main/projects.yaml). Contributions are very welcome! --- @@ -31,7 +31,7 @@ This curated list contains 920 awesome open-source projects with a total of 4.5M ## Contents -- [Machine Learning Frameworks](#machine-learning-frameworks) _62 projects_ +- [Machine Learning Frameworks](#machine-learning-frameworks) _63 projects_ - [Data Visualization](#data-visualization) _54 projects_ - [Text Data & NLP](#text-data--nlp) _102 projects_ - [Image Data](#image-data) _64 projects_ @@ -99,266 +99,250 @@ This curated list contains 920 awesome open-source projects with a total of 4.5M _General-purpose machine learning and deep learning frameworks._ -
Tensorflow (πŸ₯‡56 Β· ⭐ 190K) - An Open Source Machine Learning Framework for Everyone. Apache-2 +
PyTorch (πŸ₯‡56 Β· ⭐ 82K) - Tensors and Dynamic neural networks in Python with strong GPU.. BSD-3 -- [GitHub](https://github.com/tensorflow/tensorflow) (πŸ‘¨β€πŸ’» 4.6K Β· πŸ”€ 74K Β· πŸ“¦ 380K Β· πŸ“‹ 40K - 7% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/pytorch/pytorch) (πŸ‘¨β€πŸ’» 5.1K Β· πŸ”€ 22K Β· πŸ“₯ 55K Β· πŸ“¦ 520K Β· πŸ“‹ 46K - 32% open Β· ⏱️ 05.09.2024): ``` - git clone https://github.com/tensorflow/tensorflow - ``` -- [PyPi](https://pypi.org/project/tensorflow) (πŸ“₯ 21M / month Β· πŸ“¦ 7.4K Β· ⏱️ 09.03.2024): - ``` - pip install tensorflow + git clone https://github.com/pytorch/pytorch ``` -- [Conda](https://anaconda.org/conda-forge/tensorflow) (πŸ“₯ 4.7M Β· ⏱️ 24.05.2024): +- [PyPi](https://pypi.org/project/torch) (πŸ“₯ 34M / month Β· πŸ“¦ 18K Β· ⏱️ 04.09.2024): ``` - conda install -c conda-forge tensorflow + pip install torch ``` -- [Docker Hub](https://hub.docker.com/r/tensorflow/tensorflow) (πŸ“₯ 77M Β· ⭐ 2.4K Β· ⏱️ 06.06.2024): +- [Conda](https://anaconda.org/pytorch/pytorch) (πŸ“₯ 23M Β· ⏱️ 03.09.2024): ``` - docker pull tensorflow/tensorflow + conda install -c pytorch pytorch ```
-
PyTorch (πŸ₯‡55 Β· ⭐ 79K) - Tensors and Dynamic neural networks in Python with strong GPU.. BSD-3 +
Tensorflow (πŸ₯‡55 Β· ⭐ 190K) - An Open Source Machine Learning Framework for Everyone. Apache-2 -- [GitHub](https://github.com/pytorch/pytorch) (πŸ‘¨β€πŸ’» 4.9K Β· πŸ”€ 21K Β· πŸ“₯ 43K Β· πŸ“¦ 460K Β· πŸ“‹ 44K - 32% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/tensorflow/tensorflow) (πŸ‘¨β€πŸ’» 4.7K Β· πŸ”€ 74K Β· πŸ“¦ 410K Β· πŸ“‹ 43K - 10% open Β· ⏱️ 05.09.2024): ``` - git clone https://github.com/pytorch/pytorch + git clone https://github.com/tensorflow/tensorflow ``` -- [PyPi](https://pypi.org/project/torch) (πŸ“₯ 29M / month Β· πŸ“¦ 17K Β· ⏱️ 05.06.2024): +- [PyPi](https://pypi.org/project/tensorflow) (πŸ“₯ 18M / month Β· πŸ“¦ 7.8K Β· ⏱️ 11.07.2024): ``` - pip install torch + pip install tensorflow ``` -- [Conda](https://anaconda.org/pytorch/pytorch) (πŸ“₯ 22M Β· ⏱️ 04.06.2024): +- [Conda](https://anaconda.org/conda-forge/tensorflow) (πŸ“₯ 4.9M Β· ⏱️ 31.08.2024): ``` - conda install -c pytorch pytorch + conda install -c conda-forge tensorflow + ``` +- [Docker Hub](https://hub.docker.com/r/tensorflow/tensorflow) (πŸ“₯ 78M Β· ⭐ 2.5K Β· ⏱️ 04.09.2024): + ``` + docker pull tensorflow/tensorflow ```
scikit-learn (πŸ₯‡52 Β· ⭐ 59K) - scikit-learn: machine learning in Python. BSD-3 -- [GitHub](https://github.com/scikit-learn/scikit-learn) (πŸ‘¨β€πŸ’» 3.1K Β· πŸ”€ 25K Β· πŸ“₯ 960 Β· πŸ“¦ 790K Β· πŸ“‹ 11K - 17% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/scikit-learn/scikit-learn) (πŸ‘¨β€πŸ’» 3.2K Β· πŸ”€ 25K Β· πŸ“₯ 1K Β· πŸ“¦ 880K Β· πŸ“‹ 12K - 18% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/scikit-learn/scikit-learn ``` -- [PyPi](https://pypi.org/project/scikit-learn) (πŸ“₯ 68M / month Β· πŸ“¦ 22K Β· ⏱️ 21.05.2024): +- [PyPi](https://pypi.org/project/scikit-learn) (πŸ“₯ 72M / month Β· πŸ“¦ 24K Β· ⏱️ 03.07.2024): ``` pip install scikit-learn ``` -- [Conda](https://anaconda.org/conda-forge/scikit-learn) (πŸ“₯ 29M Β· ⏱️ 23.05.2024): +- [Conda](https://anaconda.org/conda-forge/scikit-learn) (πŸ“₯ 31M Β· ⏱️ 03.07.2024): ``` conda install -c conda-forge scikit-learn ```
-
Keras (πŸ₯‡48 Β· ⭐ 61K) - Deep Learning for humans. Apache-2 +
Keras (πŸ₯‡48 Β· ⭐ 62K) - Deep Learning for humans. Apache-2 -- [GitHub](https://github.com/keras-team/keras) (πŸ‘¨β€πŸ’» 1.3K Β· πŸ”€ 19K Β· πŸ“‹ 12K - 1% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/keras-team/keras) (πŸ‘¨β€πŸ’» 1.3K Β· πŸ”€ 19K Β· πŸ“‹ 12K - 1% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/keras-team/keras ``` -- [PyPi](https://pypi.org/project/keras) (πŸ“₯ 17M / month Β· πŸ“¦ 1.4K Β· ⏱️ 22.04.2024): +- [PyPi](https://pypi.org/project/keras) (πŸ“₯ 14M / month Β· πŸ“¦ 1.5K Β· ⏱️ 12.08.2024): ``` pip install keras ``` -- [Conda](https://anaconda.org/conda-forge/keras) (πŸ“₯ 3.5M Β· ⏱️ 27.04.2024): +- [Conda](https://anaconda.org/conda-forge/keras) (πŸ“₯ 3.7M Β· ⏱️ 17.08.2024): ``` conda install -c conda-forge keras ```
-
PySpark (πŸ₯‡45 Β· ⭐ 39K) - Apache Spark Python API. Apache-2 +
jax (πŸ₯‡46 Β· ⭐ 30K) - Composable transformations of Python+NumPy programs: differentiate,.. Apache-2 -- [GitHub](https://github.com/apache/spark) (πŸ‘¨β€πŸ’» 3.1K Β· πŸ”€ 28K Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/google/jax) (πŸ‘¨β€πŸ’» 740 Β· πŸ”€ 2.7K Β· πŸ“¦ 30K Β· πŸ“‹ 5.9K - 29% open Β· ⏱️ 05.09.2024): ``` - git clone https://github.com/apache/spark + git clone https://github.com/google/jax ``` -- [PyPi](https://pypi.org/project/pyspark) (πŸ“₯ 29M / month Β· πŸ“¦ 1.4K Β· ⏱️ 03.06.2024): +- [PyPi](https://pypi.org/project/jax) (πŸ“₯ 3.4M / month Β· πŸ“¦ 1.8K Β· ⏱️ 30.07.2024): ``` - pip install pyspark + pip install jax ``` -- [Conda](https://anaconda.org/conda-forge/pyspark) (πŸ“₯ 3.2M Β· ⏱️ 03.03.2024): +- [Conda](https://anaconda.org/conda-forge/jaxlib) (πŸ“₯ 1.6M Β· ⏱️ 31.08.2024): ``` - conda install -c conda-forge pyspark + conda install -c conda-forge jaxlib ```
-
jax (πŸ₯‡45 Β· ⭐ 29K) - Composable transformations of Python+NumPy programs: differentiate,.. Apache-2 +
PaddlePaddle (πŸ₯‡46 Β· ⭐ 22K) - PArallel Distributed Deep LEarning: Machine Learning.. Apache-2 -- [GitHub](https://github.com/google/jax) (πŸ‘¨β€πŸ’» 700 Β· πŸ”€ 2.6K Β· πŸ“¦ 26K Β· πŸ“‹ 5.5K - 29% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/PaddlePaddle/Paddle) (πŸ‘¨β€πŸ’» 1.3K Β· πŸ”€ 5.5K Β· πŸ“₯ 15K Β· πŸ“¦ 5.8K Β· πŸ“‹ 19K - 9% open Β· ⏱️ 05.09.2024): ``` - git clone https://github.com/google/jax - ``` -- [PyPi](https://pypi.org/project/jax) (πŸ“₯ 5.9M / month Β· πŸ“¦ 1.5K Β· ⏱️ 09.05.2024): - ``` - pip install jax + git clone https://github.com/PaddlePaddle/Paddle ``` -- [Conda](https://anaconda.org/conda-forge/jaxlib) (πŸ“₯ 1.3M Β· ⏱️ 22.05.2024): +- [PyPi](https://pypi.org/project/paddlepaddle) (πŸ“₯ 510K / month Β· πŸ“¦ 160 Β· ⏱️ 08.07.2024): ``` - conda install -c conda-forge jaxlib + pip install paddlepaddle ```
-
PaddlePaddle (πŸ₯‡45 Β· ⭐ 22K) - PArallel Distributed Deep LEarning: Machine Learning.. Apache-2 +
XGBoost (πŸ₯‡45 Β· ⭐ 26K) - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or.. Apache-2 -- [GitHub](https://github.com/PaddlePaddle/Paddle) (πŸ‘¨β€πŸ’» 1.2K Β· πŸ”€ 5.4K Β· πŸ“₯ 15K Β· πŸ“¦ 5.2K Β· πŸ“‹ 19K - 9% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/dmlc/xgboost) (πŸ‘¨β€πŸ’» 650 Β· πŸ”€ 8.7K Β· πŸ“₯ 11K Β· πŸ“¦ 110K Β· πŸ“‹ 5.3K - 8% open Β· ⏱️ 02.09.2024): ``` - git clone https://github.com/PaddlePaddle/Paddle + git clone https://github.com/dmlc/xgboost ``` -- [PyPi](https://pypi.org/project/paddlepaddle) (πŸ“₯ 210K / month Β· πŸ“¦ 110 Β· ⏱️ 19.03.2024): +- [PyPi](https://pypi.org/project/xgboost) (πŸ“₯ 21M / month Β· πŸ“¦ 1.9K Β· ⏱️ 31.07.2024): ``` - pip install paddlepaddle + pip install xgboost + ``` +- [Conda](https://anaconda.org/conda-forge/xgboost) (πŸ“₯ 5.2M Β· ⏱️ 28.08.2024): + ``` + conda install -c conda-forge xgboost ```
-
StatsModels (πŸ₯‡45 Β· ⭐ 9.7K) - Statsmodels: statistical modeling and econometrics in Python. BSD-3 +
StatsModels (πŸ₯‡45 Β· ⭐ 10K) - Statsmodels: statistical modeling and econometrics in Python. BSD-3 -- [GitHub](https://github.com/statsmodels/statsmodels) (πŸ‘¨β€πŸ’» 430 Β· πŸ”€ 2.8K Β· πŸ“₯ 31 Β· πŸ“¦ 130K Β· πŸ“‹ 5.5K - 50% open Β· ⏱️ 01.06.2024): +- [GitHub](https://github.com/statsmodels/statsmodels) (πŸ‘¨β€πŸ’» 430 Β· πŸ”€ 2.9K Β· πŸ“₯ 33 Β· πŸ“¦ 130K Β· πŸ“‹ 5.6K - 50% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/statsmodels/statsmodels ``` -- [PyPi](https://pypi.org/project/statsmodels) (πŸ“₯ 17M / month Β· πŸ“¦ 4K Β· ⏱️ 17.04.2024): +- [PyPi](https://pypi.org/project/statsmodels) (πŸ“₯ 16M / month Β· πŸ“¦ 4.3K Β· ⏱️ 17.04.2024): ``` pip install statsmodels ``` -- [Conda](https://anaconda.org/conda-forge/statsmodels) (πŸ“₯ 13M Β· ⏱️ 17.05.2024): +- [Conda](https://anaconda.org/conda-forge/statsmodels) (πŸ“₯ 15M Β· ⏱️ 17.05.2024): ``` conda install -c conda-forge statsmodels ```
-
pytorch-lightning (πŸ₯ˆ44 Β· ⭐ 27K) - Pretrain, finetune and deploy AI models on multiple.. Apache-2 +
PySpark (πŸ₯ˆ44 Β· ⭐ 39K) - Apache Spark Python API. Apache-2 -- [GitHub](https://github.com/Lightning-AI/pytorch-lightning) (πŸ‘¨β€πŸ’» 950 Β· πŸ”€ 3.3K Β· πŸ“₯ 7.6K Β· πŸ“¦ 33K Β· πŸ“‹ 6.9K - 10% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/apache/spark) (πŸ‘¨β€πŸ’» 3.1K Β· πŸ”€ 28K Β· ⏱️ 05.09.2024): ``` - git clone https://github.com/Lightning-AI/lightning + git clone https://github.com/apache/spark ``` -- [PyPi](https://pypi.org/project/pytorch-lightning) (πŸ“₯ 5.4M / month Β· πŸ“¦ 1.4K Β· ⏱️ 22.05.2024): +- [PyPi](https://pypi.org/project/pyspark) (πŸ“₯ 30M / month Β· πŸ“¦ 1.5K Β· ⏱️ 12.08.2024): ``` - pip install pytorch-lightning + pip install pyspark ``` -- [Conda](https://anaconda.org/conda-forge/pytorch-lightning) (πŸ“₯ 1.2M Β· ⏱️ 12.04.2024): +- [Conda](https://anaconda.org/conda-forge/pyspark) (πŸ“₯ 3.4M Β· ⏱️ 03.03.2024): ``` - conda install -c conda-forge pytorch-lightning + conda install -c conda-forge pyspark ```
-
XGBoost (πŸ₯ˆ44 Β· ⭐ 26K) - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or.. Apache-2 +
pytorch-lightning (πŸ₯ˆ44 Β· ⭐ 28K) - Pretrain, finetune and deploy AI models on multiple.. Apache-2 -- [GitHub](https://github.com/dmlc/xgboost) (πŸ‘¨β€πŸ’» 640 Β· πŸ”€ 8.7K Β· πŸ“₯ 8.6K Β· πŸ“¦ 94K Β· πŸ“‹ 5.2K - 8% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/Lightning-AI/pytorch-lightning) (πŸ‘¨β€πŸ’» 970 Β· πŸ”€ 3.3K Β· πŸ“₯ 8.3K Β· πŸ“¦ 36K Β· πŸ“‹ 7K - 10% open Β· ⏱️ 22.08.2024): ``` - git clone https://github.com/dmlc/xgboost + git clone https://github.com/Lightning-AI/lightning ``` -- [PyPi](https://pypi.org/project/xgboost) (πŸ“₯ 20M / month Β· πŸ“¦ 1.8K Β· ⏱️ 31.05.2024): +- [PyPi](https://pypi.org/project/pytorch-lightning) (πŸ“₯ 6.3M / month Β· πŸ“¦ 1.4K Β· ⏱️ 07.08.2024): ``` - pip install xgboost + pip install pytorch-lightning ``` -- [Conda](https://anaconda.org/conda-forge/xgboost) (πŸ“₯ 4.9M Β· ⏱️ 18.04.2024): +- [Conda](https://anaconda.org/conda-forge/pytorch-lightning) (πŸ“₯ 1.3M Β· ⏱️ 07.08.2024): ``` - conda install -c conda-forge xgboost + conda install -c conda-forge pytorch-lightning ```
-
LightGBM (πŸ₯ˆ43 Β· ⭐ 16K) - A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT,.. MIT +
LightGBM (πŸ₯ˆ43 Β· ⭐ 17K) - A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT,.. MIT -- [GitHub](https://github.com/microsoft/LightGBM) (πŸ‘¨β€πŸ’» 300 Β· πŸ”€ 3.8K Β· πŸ“₯ 220K Β· πŸ“¦ 34K Β· πŸ“‹ 3.4K - 11% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/microsoft/LightGBM) (πŸ‘¨β€πŸ’» 320 Β· πŸ”€ 3.8K Β· πŸ“₯ 230K Β· πŸ“¦ 37K Β· πŸ“‹ 3.4K - 10% open Β· ⏱️ 04.09.2024): ``` git clone https://github.com/microsoft/LightGBM ``` -- [PyPi](https://pypi.org/project/lightgbm) (πŸ“₯ 7.6M / month Β· πŸ“¦ 1K Β· ⏱️ 26.01.2024): +- [PyPi](https://pypi.org/project/lightgbm) (πŸ“₯ 10M / month Β· πŸ“¦ 1.1K Β· ⏱️ 26.07.2024): ``` pip install lightgbm ``` -- [Conda](https://anaconda.org/conda-forge/lightgbm) (πŸ“₯ 2.3M Β· ⏱️ 26.01.2024): +- [Conda](https://anaconda.org/conda-forge/lightgbm) (πŸ“₯ 2.6M Β· ⏱️ 02.08.2024): ``` conda install -c conda-forge lightgbm ```
-
Catboost (πŸ₯ˆ41 Β· ⭐ 7.8K) - A fast, scalable, high performance Gradient Boosting on Decision.. Apache-2 +
Catboost (πŸ₯ˆ41 Β· ⭐ 8K) - A fast, scalable, high performance Gradient Boosting on Decision.. Apache-2 -- [GitHub](https://github.com/catboost/catboost) (πŸ‘¨β€πŸ’» 1.2K Β· πŸ”€ 1.1K Β· πŸ“₯ 260K Β· πŸ“¦ 14 Β· πŸ“‹ 2.3K - 22% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/catboost/catboost) (πŸ‘¨β€πŸ’» 1.3K Β· πŸ”€ 1.2K Β· πŸ“₯ 290K Β· πŸ“¦ 14 Β· πŸ“‹ 2.3K - 23% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/catboost/catboost ``` -- [PyPi](https://pypi.org/project/catboost) (πŸ“₯ 2.2M / month Β· πŸ“¦ 390 Β· ⏱️ 18.04.2024): +- [PyPi](https://pypi.org/project/catboost) (πŸ“₯ 2.6M / month Β· πŸ“¦ 540 Β· ⏱️ 05.09.2024): ``` pip install catboost ``` -- [Conda](https://anaconda.org/conda-forge/catboost) (πŸ“₯ 1.5M Β· ⏱️ 18.04.2024): +- [Conda](https://anaconda.org/conda-forge/catboost) (πŸ“₯ 1.7M Β· ⏱️ 18.04.2024): ``` conda install -c conda-forge catboost ```
Fastai (πŸ₯ˆ40 Β· ⭐ 26K) - The fastai deep learning library. Apache-2 -- [GitHub](https://github.com/fastai/fastai) (πŸ‘¨β€πŸ’» 670 Β· πŸ”€ 7.5K Β· πŸ“¦ 17K Β· πŸ“‹ 1.8K - 11% open Β· ⏱️ 25.05.2024): +- [GitHub](https://github.com/fastai/fastai) (πŸ‘¨β€πŸ’» 670 Β· πŸ”€ 7.5K Β· πŸ“¦ 18K Β· πŸ“‹ 1.8K - 12% open Β· ⏱️ 27.08.2024): ``` git clone https://github.com/fastai/fastai ``` -- [PyPi](https://pypi.org/project/fastai) (πŸ“₯ 370K / month Β· πŸ“¦ 290 Β· ⏱️ 27.04.2024): +- [PyPi](https://pypi.org/project/fastai) (πŸ“₯ 320K / month Β· πŸ“¦ 300 Β· ⏱️ 27.08.2024): ``` pip install fastai ```
-
Jina (πŸ₯ˆ39 Β· ⭐ 20K) - Build multimodal AI applications with cloud-native stack. Apache-2 +
Jina (πŸ₯ˆ39 Β· ⭐ 21K) - Build multimodal AI applications with cloud-native stack. Apache-2 -- [GitHub](https://github.com/jina-ai/jina) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 2.2K Β· πŸ“¦ 1.7K Β· πŸ“‹ 2K - 1% open Β· ⏱️ 16.05.2024): +- [GitHub](https://github.com/jina-ai/jina) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 2.2K Β· πŸ“¦ 1.8K Β· πŸ“‹ 2K - 1% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/jina-ai/jina ``` -- [PyPi](https://pypi.org/project/jina) (πŸ“₯ 40K / month Β· πŸ“¦ 27 Β· ⏱️ 10.04.2024): +- [PyPi](https://pypi.org/project/jina) (πŸ“₯ 58K / month Β· πŸ“¦ 27 Β· ⏱️ 05.09.2024): ``` pip install jina ``` -- [Conda](https://anaconda.org/conda-forge/jina-core) (πŸ“₯ 65K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/jina-core) (πŸ“₯ 73K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge jina-core ``` -- [Docker Hub](https://hub.docker.com/r/jinaai/jina) (πŸ“₯ 1.3M Β· ⭐ 8 Β· ⏱️ 16.05.2024): +- [Docker Hub](https://hub.docker.com/r/jinaai/jina) (πŸ“₯ 1.7M Β· ⭐ 8 Β· ⏱️ 05.09.2024): ``` docker pull jinaai/jina ```
-
Flax (πŸ₯ˆ39 Β· ⭐ 5.7K) - Flax is a neural network library for JAX that is designed for.. Apache-2 - -- [GitHub](https://github.com/google/flax) (πŸ‘¨β€πŸ’» 220 Β· πŸ”€ 600 Β· πŸ“₯ 51 Β· πŸ“¦ 7.7K Β· πŸ“‹ 930 - 24% open Β· ⏱️ 06.06.2024): - - ``` - git clone https://github.com/google/flax - ``` -- [PyPi](https://pypi.org/project/flax) (πŸ“₯ 3.4M / month Β· πŸ“¦ 400 Β· ⏱️ 24.05.2024): - ``` - pip install flax - ``` -- [Conda](https://anaconda.org/conda-forge/flax) (πŸ“₯ 52K Β· ⏱️ 30.04.2024): - ``` - conda install -c conda-forge flax - ``` -
-
PyFlink (πŸ₯ˆ38 Β· ⭐ 23K) - Apache Flink Python API. Apache-2 +
PyFlink (πŸ₯ˆ38 Β· ⭐ 24K) - Apache Flink Python API. Apache-2 -- [GitHub](https://github.com/apache/flink) (πŸ‘¨β€πŸ’» 1.9K Β· πŸ”€ 13K Β· πŸ“¦ 21 Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/apache/flink) (πŸ‘¨β€πŸ’» 1.9K Β· πŸ”€ 13K Β· πŸ“¦ 21 Β· ⏱️ 05.09.2024): ``` git clone https://github.com/apache/flink ``` -- [PyPi](https://pypi.org/project/apache-flink) (πŸ“₯ 80K / month Β· πŸ“¦ 24 Β· ⏱️ 15.03.2024): +- [PyPi](https://pypi.org/project/apache-flink) (πŸ“₯ 150K / month Β· πŸ“¦ 35 Β· ⏱️ 01.08.2024): ``` pip install apache-flink ```
-
Theano (πŸ₯ˆ37 Β· ⭐ 9.9K) - Theano was a Python library that allows you to define, optimize, and.. BSD-3 +
Theano (πŸ₯ˆ37 Β· ⭐ 9.9K Β· πŸ’€) - Theano was a Python library that allows you to define, optimize, and.. BSD-3 - [GitHub](https://github.com/Theano/Theano) (πŸ‘¨β€πŸ’» 390 Β· πŸ”€ 2.5K Β· πŸ“¦ 15K Β· πŸ“‹ 2.8K - 24% open Β· ⏱️ 15.01.2024): ``` git clone https://github.com/Theano/Theano ``` -- [PyPi](https://pypi.org/project/theano) (πŸ“₯ 300K / month Β· πŸ“¦ 170 Β· ⏱️ 27.07.2020): +- [PyPi](https://pypi.org/project/theano) (πŸ“₯ 90K / month Β· πŸ“¦ 170 Β· ⏱️ 27.07.2020): ``` pip install theano ``` @@ -367,286 +351,286 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge theano ```
-
ivy (πŸ₯ˆ36 Β· ⭐ 14K Β· πŸ“ˆ) - The Unified AI Framework. Apache-2 +
Flax (πŸ₯ˆ37 Β· ⭐ 5.9K) - Flax is a neural network library for JAX that is designed for.. Apache-2 + +- [GitHub](https://github.com/google/flax) (πŸ‘¨β€πŸ’» 240 Β· πŸ”€ 620 Β· πŸ“₯ 51 Β· πŸ“¦ 9K Β· πŸ“‹ 990 - 26% open Β· ⏱️ 05.09.2024): + + ``` + git clone https://github.com/google/flax + ``` +- [PyPi](https://pypi.org/project/flax) (πŸ“₯ 670K / month Β· πŸ“¦ 450 Β· ⏱️ 27.08.2024): + ``` + pip install flax + ``` +- [Conda](https://anaconda.org/conda-forge/flax) (πŸ“₯ 69K Β· ⏱️ 27.08.2024): + ``` + conda install -c conda-forge flax + ``` +
+
ivy (πŸ₯ˆ36 Β· ⭐ 14K) - Convert Machine Learning Code Between Frameworks. Apache-2 -- [GitHub](https://github.com/Transpile-AI/ivy) (πŸ‘¨β€πŸ’» 1.5K Β· πŸ”€ 5.8K Β· πŸ“‹ 17K - 5% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/ivy-llc/ivy) (πŸ‘¨β€πŸ’» 1.5K Β· πŸ”€ 5.8K Β· πŸ“‹ 17K - 5% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/unifyai/ivy ``` -- [PyPi](https://pypi.org/project/ivy) (πŸ“₯ 1.5K / month Β· πŸ“¦ 12 Β· ⏱️ 05.06.2024): +- [PyPi](https://pypi.org/project/ivy) (πŸ“₯ 2K / month Β· πŸ“¦ 12 Β· ⏱️ 09.08.2024): ``` pip install ivy ```
Thinc (πŸ₯ˆ36 Β· ⭐ 2.8K) - A refreshing functional take on deep learning, compatible with your favorite.. MIT -- [GitHub](https://github.com/explosion/thinc) (πŸ‘¨β€πŸ’» 63 Β· πŸ”€ 280 Β· πŸ“¦ 48K Β· πŸ“‹ 140 - 13% open Β· ⏱️ 03.06.2024): +- [GitHub](https://github.com/explosion/thinc) (πŸ‘¨β€πŸ’» 63 Β· πŸ”€ 280 Β· πŸ“₯ 87 Β· πŸ“¦ 52K Β· πŸ“‹ 150 - 14% open Β· ⏱️ 02.09.2024): ``` git clone https://github.com/explosion/thinc ``` -- [PyPi](https://pypi.org/project/thinc) (πŸ“₯ 9.9M / month Β· πŸ“¦ 120 Β· ⏱️ 04.06.2024): +- [PyPi](https://pypi.org/project/thinc) (πŸ“₯ 9.9M / month Β· πŸ“¦ 130 Β· ⏱️ 02.09.2024): ``` pip install thinc ``` -- [Conda](https://anaconda.org/conda-forge/thinc) (πŸ“₯ 2.8M Β· ⏱️ 11.05.2024): +- [Conda](https://anaconda.org/conda-forge/thinc) (πŸ“₯ 3M Β· ⏱️ 14.07.2024): ``` conda install -c conda-forge thinc ```
-
Ludwig (πŸ₯ˆ34 Β· ⭐ 11K) - Low-code framework for building custom LLMs, neural networks, and.. Apache-2 - -- [GitHub](https://github.com/ludwig-ai/ludwig) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 1.2K Β· πŸ“¦ 260 Β· πŸ“‹ 1.1K - 32% open Β· ⏱️ 01.06.2024): - - ``` - git clone https://github.com/ludwig-ai/ludwig - ``` -- [PyPi](https://pypi.org/project/ludwig) (πŸ“₯ 4.7K / month Β· πŸ“¦ 6 Β· ⏱️ 08.04.2024): - ``` - pip install ludwig - ``` -
-
Vowpal Wabbit (πŸ₯ˆ34 Β· ⭐ 8.4K) - Vowpal Wabbit is a machine learning system which pushes the.. BSD-3 +
einops (πŸ₯ˆ35 Β· ⭐ 8.3K) - Flexible and powerful tensor operations for readable and reliable code.. MIT -- [GitHub](https://github.com/VowpalWabbit/vowpal_wabbit) (πŸ‘¨β€πŸ’» 340 Β· πŸ”€ 1.9K Β· πŸ“‹ 1.3K - 10% open Β· ⏱️ 23.05.2024): +- [GitHub](https://github.com/arogozhnikov/einops) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 340 Β· πŸ“¦ 44K Β· πŸ“‹ 180 - 19% open Β· ⏱️ 08.08.2024): ``` - git clone https://github.com/VowpalWabbit/vowpal_wabbit + git clone https://github.com/arogozhnikov/einops ``` -- [PyPi](https://pypi.org/project/vowpalwabbit) (πŸ“₯ 62K / month Β· πŸ“¦ 40 Β· ⏱️ 19.07.2023): +- [PyPi](https://pypi.org/project/einops) (πŸ“₯ 4.9M / month Β· πŸ“¦ 2K Β· ⏱️ 28.04.2024): ``` - pip install vowpalwabbit + pip install einops ``` -- [Conda](https://anaconda.org/conda-forge/vowpalwabbit) (πŸ“₯ 160K Β· ⏱️ 26.04.2024): +- [Conda](https://anaconda.org/conda-forge/einops) (πŸ“₯ 260K Β· ⏱️ 28.04.2024): ``` - conda install -c conda-forge vowpalwabbit + conda install -c conda-forge einops ```
-
einops (πŸ₯ˆ34 Β· ⭐ 8K) - Flexible and powerful tensor operations for readable and reliable code (for.. MIT +
mlpack (πŸ₯ˆ35 Β· ⭐ 5K) - mlpack: a fast, header-only C++ machine learning library. BSD-3 -- [GitHub](https://github.com/arogozhnikov/einops) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 340 Β· πŸ“¦ 36K Β· πŸ“‹ 170 - 19% open Β· ⏱️ 26.05.2024): +- [GitHub](https://github.com/mlpack/mlpack) (πŸ‘¨β€πŸ’» 320 Β· πŸ”€ 1.6K Β· πŸ“‹ 1.6K - 1% open Β· ⏱️ 03.09.2024): ``` - git clone https://github.com/arogozhnikov/einops + git clone https://github.com/mlpack/mlpack ``` -- [PyPi](https://pypi.org/project/einops) (πŸ“₯ 7.3M / month Β· πŸ“¦ 1.7K Β· ⏱️ 28.04.2024): +- [PyPi](https://pypi.org/project/mlpack) (πŸ“₯ 4.1K / month Β· πŸ“¦ 4 Β· ⏱️ 25.07.2024): ``` - pip install einops + pip install mlpack ``` -- [Conda](https://anaconda.org/conda-forge/einops) (πŸ“₯ 220K Β· ⏱️ 28.04.2024): +- [Conda](https://anaconda.org/conda-forge/mlpack) (πŸ“₯ 240K Β· ⏱️ 29.05.2024): ``` - conda install -c conda-forge einops + conda install -c conda-forge mlpack ```
-
Ignite (πŸ₯ˆ34 Β· ⭐ 4.5K) - High-level library to help with training and evaluating neural.. BSD-3 +
Ignite (πŸ₯ˆ35 Β· ⭐ 4.5K) - High-level library to help with training and evaluating neural.. BSD-3 -- [GitHub](https://github.com/pytorch/ignite) (πŸ‘¨β€πŸ’» 530 Β· πŸ”€ 600 Β· πŸ“¦ 2.9K Β· πŸ“‹ 1.4K - 10% open Β· ⏱️ 04.06.2024): +- [GitHub](https://github.com/pytorch/ignite) (πŸ‘¨β€πŸ’» 620 Β· πŸ”€ 610 Β· πŸ“¦ 3.2K Β· πŸ“‹ 1.4K - 11% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/pytorch/ignite ``` -- [PyPi](https://pypi.org/project/pytorch-ignite) (πŸ“₯ 260K / month Β· πŸ“¦ 84 Β· ⏱️ 06.06.2024): +- [PyPi](https://pypi.org/project/pytorch-ignite) (πŸ“₯ 170K / month Β· πŸ“¦ 95 Β· ⏱️ 05.09.2024): ``` pip install pytorch-ignite ``` -- [Conda](https://anaconda.org/pytorch/ignite) (πŸ“₯ 180K Β· ⏱️ 01.04.2024): +- [Conda](https://anaconda.org/pytorch/ignite) (πŸ“₯ 200K Β· ⏱️ 13.08.2024): ``` conda install -c pytorch ignite ```
-
mlpack (πŸ₯‰33 Β· ⭐ 4.9K) - mlpack: a fast, header-only C++ machine learning library. BSD-3 +
Vowpal Wabbit (πŸ₯ˆ34 Β· ⭐ 8.5K) - Vowpal Wabbit is a machine learning system which pushes the.. BSD-3 -- [GitHub](https://github.com/mlpack/mlpack) (πŸ‘¨β€πŸ’» 320 Β· πŸ”€ 1.6K Β· πŸ“‹ 1.6K - 1% open Β· ⏱️ 03.06.2024): +- [GitHub](https://github.com/VowpalWabbit/vowpal_wabbit) (πŸ‘¨β€πŸ’» 340 Β· πŸ”€ 1.9K Β· πŸ“‹ 1.3K - 10% open Β· ⏱️ 01.08.2024): ``` - git clone https://github.com/mlpack/mlpack + git clone https://github.com/VowpalWabbit/vowpal_wabbit ``` -- [PyPi](https://pypi.org/project/mlpack) (πŸ“₯ 2.3K / month Β· πŸ“¦ 2 Β· ⏱️ 28.05.2024): +- [PyPi](https://pypi.org/project/vowpalwabbit) (πŸ“₯ 52K / month Β· πŸ“¦ 40 Β· ⏱️ 08.08.2024): ``` - pip install mlpack + pip install vowpalwabbit ``` -- [Conda](https://anaconda.org/conda-forge/mlpack) (πŸ“₯ 190K Β· ⏱️ 29.05.2024): +- [Conda](https://anaconda.org/conda-forge/vowpalwabbit) (πŸ“₯ 210K Β· ⏱️ 05.09.2024): ``` - conda install -c conda-forge mlpack + conda install -c conda-forge vowpalwabbit ```
-
Sonnet (πŸ₯‰32 Β· ⭐ 9.7K) - TensorFlow-based neural network library. Apache-2 +
Ludwig (πŸ₯‰33 Β· ⭐ 11K) - Low-code framework for building custom LLMs, neural networks, and.. Apache-2 -- [GitHub](https://github.com/google-deepmind/sonnet) (πŸ‘¨β€πŸ’» 59 Β· πŸ”€ 1.3K Β· πŸ“¦ 1.3K Β· πŸ“‹ 190 - 16% open Β· ⏱️ 08.04.2024): +- [GitHub](https://github.com/ludwig-ai/ludwig) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 1.2K Β· πŸ“¦ 270 Β· πŸ“‹ 1.1K - 32% open Β· ⏱️ 21.08.2024): ``` - git clone https://github.com/deepmind/sonnet - ``` -- [PyPi](https://pypi.org/project/dm-sonnet) (πŸ“₯ 18K / month Β· πŸ“¦ 18 Β· ⏱️ 02.01.2024): - ``` - pip install dm-sonnet + git clone https://github.com/ludwig-ai/ludwig ``` -- [Conda](https://anaconda.org/conda-forge/sonnet) (πŸ“₯ 29K Β· ⏱️ 16.06.2023): +- [PyPi](https://pypi.org/project/ludwig) (πŸ“₯ 2.8K / month Β· πŸ“¦ 6 Β· ⏱️ 30.07.2024): ``` - conda install -c conda-forge sonnet + pip install ludwig ```
-
tensorpack (πŸ₯‰32 Β· ⭐ 6.3K Β· πŸ’€) - A Neural Net Training Interface on TensorFlow, with.. Apache-2 +
Sonnet (πŸ₯‰32 Β· ⭐ 9.7K) - TensorFlow-based neural network library. Apache-2 -- [GitHub](https://github.com/tensorpack/tensorpack) (πŸ‘¨β€πŸ’» 58 Β· πŸ”€ 1.8K Β· πŸ“₯ 170 Β· πŸ“¦ 1.6K Β· πŸ“‹ 1.4K - 0% open Β· ⏱️ 06.08.2023): +- [GitHub](https://github.com/google-deepmind/sonnet) (πŸ‘¨β€πŸ’» 59 Β· πŸ”€ 1.3K Β· πŸ“¦ 1.3K Β· πŸ“‹ 190 - 16% open Β· ⏱️ 08.04.2024): ``` - git clone https://github.com/tensorpack/tensorpack + git clone https://github.com/deepmind/sonnet ``` -- [PyPi](https://pypi.org/project/tensorpack) (πŸ“₯ 14K / month Β· πŸ“¦ 18 Β· ⏱️ 22.01.2021): +- [PyPi](https://pypi.org/project/dm-sonnet) (πŸ“₯ 17K / month Β· πŸ“¦ 19 Β· ⏱️ 02.01.2024): ``` - pip install tensorpack + pip install dm-sonnet ``` -- [Conda](https://anaconda.org/conda-forge/tensorpack) (πŸ“₯ 11K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/sonnet) (πŸ“₯ 33K Β· ⏱️ 16.06.2023): ``` - conda install -c conda-forge tensorpack + conda install -c conda-forge sonnet ```
-
skorch (πŸ₯‰31 Β· ⭐ 5.7K) - A scikit-learn compatible neural network library that wraps.. BSD-3 +
skorch (πŸ₯‰31 Β· ⭐ 5.8K) - A scikit-learn compatible neural network library that wraps.. BSD-3 -- [GitHub](https://github.com/skorch-dev/skorch) (πŸ‘¨β€πŸ’» 62 Β· πŸ”€ 380 Β· πŸ“¦ 1.3K Β· πŸ“‹ 520 - 11% open Β· ⏱️ 30.05.2024): +- [GitHub](https://github.com/skorch-dev/skorch) (πŸ‘¨β€πŸ’» 62 Β· πŸ”€ 380 Β· πŸ“¦ 1.4K Β· πŸ“‹ 520 - 11% open Β· ⏱️ 30.05.2024): ``` git clone https://github.com/skorch-dev/skorch ``` -- [PyPi](https://pypi.org/project/skorch) (πŸ“₯ 170K / month Β· πŸ“¦ 80 Β· ⏱️ 27.05.2024): +- [PyPi](https://pypi.org/project/skorch) (πŸ“₯ 140K / month Β· πŸ“¦ 85 Β· ⏱️ 27.05.2024): ``` pip install skorch ``` -- [Conda](https://anaconda.org/conda-forge/skorch) (πŸ“₯ 780K Β· ⏱️ 30.05.2024): +- [Conda](https://anaconda.org/conda-forge/skorch) (πŸ“₯ 790K Β· ⏱️ 30.05.2024): ``` conda install -c conda-forge skorch ```
dyNET (πŸ₯‰31 Β· ⭐ 3.4K Β· πŸ’€) - DyNet: The Dynamic Neural Network Toolkit. Apache-2 -- [GitHub](https://github.com/clab/dynet) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 700 Β· πŸ“₯ 16K Β· πŸ“¦ 260 Β· πŸ“‹ 940 - 29% open Β· ⏱️ 08.11.2023): +- [GitHub](https://github.com/clab/dynet) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 700 Β· πŸ“₯ 17K Β· πŸ“¦ 260 Β· πŸ“‹ 950 - 29% open Β· ⏱️ 08.11.2023): ``` git clone https://github.com/clab/dynet ``` -- [PyPi](https://pypi.org/project/dyNET) (πŸ“₯ 290K / month Β· πŸ“¦ 18 Β· ⏱️ 21.10.2020): +- [PyPi](https://pypi.org/project/dyNET) (πŸ“₯ 250K / month Β· πŸ“¦ 18 Β· ⏱️ 21.10.2020): ``` pip install dyNET ```
-
Haiku (πŸ₯‰31 Β· ⭐ 2.8K) - JAX-based neural network library. Apache-2 +
Determined (πŸ₯‰31 Β· ⭐ 3K) - Determined is an open-source machine learning platform.. Apache-2 -- [GitHub](https://github.com/google-deepmind/dm-haiku) (πŸ‘¨β€πŸ’» 81 Β· πŸ”€ 230 Β· πŸ“¦ 1.9K Β· πŸ“‹ 250 - 28% open Β· ⏱️ 22.05.2024): +- [GitHub](https://github.com/determined-ai/determined) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 350 Β· πŸ“₯ 9.6K Β· πŸ“‹ 450 - 23% open Β· ⏱️ 04.09.2024): ``` - git clone https://github.com/deepmind/dm-haiku - ``` -- [PyPi](https://pypi.org/project/dm-haiku) (πŸ“₯ 290K / month Β· πŸ“¦ 160 Β· ⏱️ 28.02.2024): - ``` - pip install dm-haiku + git clone https://github.com/determined-ai/determined ``` -- [Conda](https://anaconda.org/conda-forge/dm-haiku) (πŸ“₯ 17K Β· ⏱️ 28.02.2024): +- [PyPi](https://pypi.org/project/determined) (πŸ“₯ 30K / month Β· πŸ“¦ 4 Β· ⏱️ 23.08.2024): ``` - conda install -c conda-forge dm-haiku + pip install determined ```
tensorflow-upstream (πŸ₯‰31 Β· ⭐ 680) - TensorFlow ROCm port. Apache-2 -- [GitHub](https://github.com/ROCm/tensorflow-upstream) (πŸ‘¨β€πŸ’» 4.6K Β· πŸ”€ 91 Β· πŸ“₯ 21 Β· πŸ“‹ 370 - 23% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/ROCm/tensorflow-upstream) (πŸ‘¨β€πŸ’» 4.7K Β· πŸ”€ 93 Β· πŸ“₯ 23 Β· πŸ“‹ 380 - 23% open Β· ⏱️ 27.08.2024): ``` git clone https://github.com/ROCmSoftwarePlatform/tensorflow-upstream ``` -- [PyPi](https://pypi.org/project/tensorflow-rocm) (πŸ“₯ 4.1K / month Β· πŸ“¦ 6 Β· ⏱️ 10.01.2024): +- [PyPi](https://pypi.org/project/tensorflow-rocm) (πŸ“₯ 3.4K / month Β· πŸ“¦ 9 Β· ⏱️ 10.01.2024): ``` pip install tensorflow-rocm ```
-
Determined (πŸ₯‰30 Β· ⭐ 2.9K) - Determined is an open-source machine learning platform.. Apache-2 +
Haiku (πŸ₯‰30 Β· ⭐ 2.9K) - JAX-based neural network library. Apache-2 -- [GitHub](https://github.com/determined-ai/determined) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 340 Β· πŸ“₯ 8.1K Β· πŸ“‹ 460 - 26% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/google-deepmind/dm-haiku) (πŸ‘¨β€πŸ’» 82 Β· πŸ”€ 230 Β· πŸ“¦ 2K Β· πŸ“‹ 250 - 30% open Β· ⏱️ 30.08.2024): ``` - git clone https://github.com/determined-ai/determined - ``` -- [PyPi](https://pypi.org/project/determined) (πŸ“₯ 47K / month Β· πŸ“¦ 4 Β· ⏱️ 29.05.2024): - ``` - pip install determined + git clone https://github.com/deepmind/dm-haiku ``` -
-
ktrain (πŸ₯‰30 Β· ⭐ 1.2K) - ktrain is a Python library that makes deep learning and AI more.. Apache-2 - -- [GitHub](https://github.com/amaiya/ktrain) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 270 Β· πŸ“¦ 520 Β· πŸ“‹ 490 - 0% open Β· ⏱️ 05.04.2024): - +- [PyPi](https://pypi.org/project/dm-haiku) (πŸ“₯ 200K / month Β· πŸ“¦ 170 Β· ⏱️ 28.02.2024): ``` - git clone https://github.com/amaiya/ktrain + pip install dm-haiku ``` -- [PyPi](https://pypi.org/project/ktrain) (πŸ“₯ 10K / month Β· πŸ“¦ 3 Β· ⏱️ 05.04.2024): +- [Conda](https://anaconda.org/conda-forge/dm-haiku) (πŸ“₯ 21K Β· ⏱️ 28.02.2024): ``` - pip install ktrain + conda install -c conda-forge dm-haiku ```
Geomstats (πŸ₯‰30 Β· ⭐ 1.2K) - Computations and statistics on manifolds with geometric structures. MIT -- [GitHub](https://github.com/geomstats/geomstats) (πŸ‘¨β€πŸ’» 92 Β· πŸ”€ 230 Β· πŸ“¦ 110 Β· πŸ“‹ 560 - 37% open Β· ⏱️ 21.05.2024): +- [GitHub](https://github.com/geomstats/geomstats) (πŸ‘¨β€πŸ’» 92 Β· πŸ”€ 240 Β· πŸ“¦ 120 Β· πŸ“‹ 560 - 36% open Β· ⏱️ 30.08.2024): ``` git clone https://github.com/geomstats/geomstats ``` -- [PyPi](https://pypi.org/project/geomstats) (πŸ“₯ 3.4K / month Β· πŸ“¦ 3 Β· ⏱️ 30.08.2023): +- [PyPi](https://pypi.org/project/geomstats) (πŸ“₯ 3.2K / month Β· πŸ“¦ 3 Β· ⏱️ 30.08.2023): ``` pip install geomstats ``` -- [Conda](https://anaconda.org/conda-forge/geomstats) (πŸ“₯ 2.6K Β· ⏱️ 30.08.2023): +- [Conda](https://anaconda.org/conda-forge/geomstats) (πŸ“₯ 3.4K Β· ⏱️ 30.08.2023): ``` conda install -c conda-forge geomstats ```
-
Neural Network Libraries (πŸ₯‰29 Β· ⭐ 2.7K) - Neural Network Libraries. Apache-2 +
ktrain (πŸ₯‰29 Β· ⭐ 1.2K) - ktrain is a Python library that makes deep learning and AI more.. Apache-2 + +- [GitHub](https://github.com/amaiya/ktrain) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 270 Β· πŸ“¦ 550 Β· πŸ“‹ 500 - 0% open Β· ⏱️ 09.07.2024): + + ``` + git clone https://github.com/amaiya/ktrain + ``` +- [PyPi](https://pypi.org/project/ktrain) (πŸ“₯ 7.7K / month Β· πŸ“¦ 4 Β· ⏱️ 19.06.2024): + ``` + pip install ktrain + ``` +
+
Neural Network Libraries (πŸ₯‰27 Β· ⭐ 2.7K) - Neural Network Libraries. Apache-2 -- [GitHub](https://github.com/sony/nnabla) (πŸ‘¨β€πŸ’» 76 Β· πŸ”€ 330 Β· πŸ“₯ 920 Β· πŸ“‹ 95 - 36% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/sony/nnabla) (πŸ‘¨β€πŸ’» 76 Β· πŸ”€ 330 Β· πŸ“₯ 920 Β· πŸ“‹ 95 - 36% open Β· ⏱️ 20.06.2024): ``` git clone https://github.com/sony/nnabla ``` -- [PyPi](https://pypi.org/project/nnabla) (πŸ“₯ 4.2K / month Β· πŸ“¦ 44 Β· ⏱️ 29.05.2024): +- [PyPi](https://pypi.org/project/nnabla) (πŸ“₯ 3K / month Β· πŸ“¦ 44 Β· ⏱️ 29.05.2024): ``` pip install nnabla ```
-
EvaDB (πŸ₯‰28 Β· ⭐ 2.6K) - Database system for AI-powered apps. Apache-2 +
EvaDB (πŸ₯‰27 Β· ⭐ 2.6K Β· πŸ’€) - Database system for AI-powered apps. Apache-2 -- [GitHub](https://github.com/georgia-tech-db/evadb) (πŸ‘¨β€πŸ’» 73 Β· πŸ”€ 250 Β· πŸ“₯ 410K Β· πŸ“¦ 140 Β· πŸ“‹ 300 - 25% open Β· ⏱️ 03.12.2023): +- [GitHub](https://github.com/georgia-tech-db/evadb) (πŸ‘¨β€πŸ’» 73 Β· πŸ”€ 260 Β· πŸ“₯ 410K Β· πŸ“¦ 150 Β· πŸ“‹ 300 - 25% open Β· ⏱️ 03.12.2023): ``` git clone https://github.com/georgia-tech-db/eva ``` -- [PyPi](https://pypi.org/project/evadb) (πŸ“₯ 460 / month Β· ⏱️ 19.11.2023): +- [PyPi](https://pypi.org/project/evadb) (πŸ“₯ 540 / month Β· ⏱️ 19.11.2023): ``` pip install evadb ```
-
pyRiemann (πŸ₯‰27 Β· ⭐ 600) - Machine learning for multivariate data through the Riemannian.. BSD-3 +
pyRiemann (πŸ₯‰27 Β· ⭐ 620) - Machine learning for multivariate data through the Riemannian.. BSD-3 -- [GitHub](https://github.com/pyRiemann/pyRiemann) (πŸ‘¨β€πŸ’» 33 Β· πŸ”€ 160 Β· πŸ“¦ 350 Β· πŸ“‹ 100 - 3% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/pyRiemann/pyRiemann) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 160 Β· πŸ“¦ 380 Β· πŸ“‹ 110 - 3% open Β· ⏱️ 26.08.2024): ``` git clone https://github.com/pyRiemann/pyRiemann ``` -- [PyPi](https://pypi.org/project/pyriemann) (πŸ“₯ 34K / month Β· πŸ“¦ 26 Β· ⏱️ 10.04.2024): +- [PyPi](https://pypi.org/project/pyriemann) (πŸ“₯ 31K / month Β· πŸ“¦ 28 Β· ⏱️ 10.04.2024): ``` pip install pyriemann ``` -- [Conda](https://anaconda.org/conda-forge/pyriemann) (πŸ“₯ 6K Β· ⏱️ 10.04.2024): +- [Conda](https://anaconda.org/conda-forge/pyriemann) (πŸ“₯ 7.6K Β· ⏱️ 10.04.2024): ``` conda install -c conda-forge pyriemann ```
-
SHOGUN (πŸ₯‰26 Β· ⭐ 3K) - Unified and efficient Machine Learning. BSD-3 +
SHOGUN (πŸ₯‰26 Β· ⭐ 3K Β· πŸ’€) - Unified and efficient Machine Learning. BSD-3 - [GitHub](https://github.com/shogun-toolbox/shogun) (πŸ‘¨β€πŸ’» 250 Β· πŸ”€ 1K Β· πŸ“‹ 1.5K - 27% open Β· ⏱️ 19.12.2023): ``` git clone https://github.com/shogun-toolbox/shogun ``` -- [Conda](https://anaconda.org/conda-forge/shogun) (πŸ“₯ 130K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/shogun) (πŸ“₯ 140K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge shogun ``` @@ -655,43 +639,67 @@ _General-purpose machine learning and deep learning frameworks._ docker pull shogun/shogun ```
-
Towhee (πŸ₯‰24 Β· ⭐ 3K) - Towhee is a framework that is dedicated to making neural data.. Apache-2 +
Towhee (πŸ₯‰24 Β· ⭐ 3.2K Β· πŸ’€) - Towhee is a framework that is dedicated to making neural data.. Apache-2 -- [GitHub](https://github.com/towhee-io/towhee) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 250 Β· πŸ“₯ 2.6K Β· πŸ“‹ 660 - 0% open Β· ⏱️ 20.01.2024): +- [GitHub](https://github.com/towhee-io/towhee) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 250 Β· πŸ“₯ 2.7K Β· πŸ“‹ 660 - 0% open Β· ⏱️ 20.01.2024): ``` git clone https://github.com/towhee-io/towhee ``` -- [PyPi](https://pypi.org/project/towhee) (πŸ“₯ 18K / month Β· ⏱️ 04.12.2023): +- [PyPi](https://pypi.org/project/towhee) (πŸ“₯ 30K / month Β· ⏱️ 04.12.2023): ``` pip install towhee ```
-
Neural Tangents (πŸ₯‰24 Β· ⭐ 2.2K Β· πŸ“‰) - Fast and Easy Infinite Neural Networks in Python. Apache-2 +
Neural Tangents (πŸ₯‰24 Β· ⭐ 2.3K) - Fast and Easy Infinite Neural Networks in Python. Apache-2 -- [GitHub](https://github.com/google/neural-tangents) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 240 Β· πŸ“₯ 380 Β· πŸ“¦ 100 Β· πŸ“‹ 160 - 38% open Β· ⏱️ 01.03.2024): +- [GitHub](https://github.com/google/neural-tangents) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 240 Β· πŸ“₯ 460 Β· πŸ“¦ 110 Β· πŸ“‹ 160 - 38% open Β· ⏱️ 01.03.2024): ``` git clone https://github.com/google/neural-tangents ``` -- [PyPi](https://pypi.org/project/neural-tangents) (πŸ“₯ 2.3K / month Β· πŸ“¦ 1 Β· ⏱️ 11.12.2023): +- [PyPi](https://pypi.org/project/neural-tangents) (πŸ“₯ 2.4K / month Β· πŸ“¦ 1 Β· ⏱️ 11.12.2023): ``` pip install neural-tangents ```
-
fklearn (πŸ₯‰24 Β· ⭐ 1.5K Β· πŸ’€) - fklearn: Functional Machine Learning. Apache-2 +
fklearn (πŸ₯‰24 Β· ⭐ 1.5K) - fklearn: Functional Machine Learning. Apache-2 -- [GitHub](https://github.com/nubank/fklearn) (πŸ‘¨β€πŸ’» 55 Β· πŸ”€ 160 Β· πŸ“¦ 13 Β· πŸ“‹ 63 - 60% open Β· ⏱️ 08.11.2023): +- [GitHub](https://github.com/nubank/fklearn) (πŸ‘¨β€πŸ’» 56 Β· πŸ”€ 160 Β· πŸ“¦ 14 Β· πŸ“‹ 65 - 61% open Β· ⏱️ 14.08.2024): ``` git clone https://github.com/nubank/fklearn ``` -- [PyPi](https://pypi.org/project/fklearn) (πŸ“₯ 1.1K / month Β· ⏱️ 23.05.2024): +- [PyPi](https://pypi.org/project/fklearn) (πŸ“₯ 1.6K / month Β· ⏱️ 14.08.2024): ``` pip install fklearn ```
-
mace (πŸ₯‰23 Β· ⭐ 4.9K) - MACE is a deep learning inference framework optimized for mobile.. Apache-2 +
Runhouse (πŸ₯‰24 Β· ⭐ 960 Β· βž•) - Orchestrate heterogeneous ML workloads in Python, like PyTorch.. Apache-2 + +- [GitHub](https://github.com/run-house/runhouse) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 35 Β· πŸ“₯ 31 Β· πŸ“‹ 51 - 17% open Β· ⏱️ 05.09.2024): + + ``` + git clone https://github.com/run-house/runhouse + ``` +- [PyPi](https://pypi.org/project/runhouse) (πŸ“₯ 26K / month Β· πŸ“¦ 1 Β· ⏱️ 04.09.2024): + ``` + pip install runhouse + ``` +
+
chefboost (πŸ₯‰23 Β· ⭐ 450) - A Lightweight Decision Tree Framework supporting regular algorithms:.. MIT + +- [GitHub](https://github.com/serengil/chefboost) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 100 Β· πŸ“¦ 59 Β· πŸ“‹ 56 - 12% open Β· ⏱️ 12.08.2024): + + ``` + git clone https://github.com/serengil/chefboost + ``` +- [PyPi](https://pypi.org/project/chefboost) (πŸ“₯ 3.6K / month Β· ⏱️ 08.06.2024): + ``` + pip install chefboost + ``` +
+
mace (πŸ₯‰21 Β· ⭐ 4.9K) - MACE is a deep learning inference framework optimized for mobile.. Apache-2 - [GitHub](https://github.com/XiaoMi/mace) (πŸ‘¨β€πŸ’» 69 Β· πŸ”€ 820 Β· πŸ“₯ 1.5K Β· πŸ“‹ 680 - 8% open Β· ⏱️ 11.03.2024): @@ -699,95 +707,84 @@ _General-purpose machine learning and deep learning frameworks._ git clone https://github.com/XiaoMi/mace ```
-
ThunderSVM (πŸ₯‰22 Β· ⭐ 1.5K) - ThunderSVM: A Fast SVM Library on GPUs and CPUs. Apache-2 +
ThunderSVM (πŸ₯‰21 Β· ⭐ 1.6K) - ThunderSVM: A Fast SVM Library on GPUs and CPUs. Apache-2 - [GitHub](https://github.com/Xtra-Computing/thundersvm) (πŸ‘¨β€πŸ’» 37 Β· πŸ”€ 210 Β· πŸ“₯ 2.8K Β· πŸ“‹ 230 - 34% open Β· ⏱️ 01.04.2024): ``` git clone https://github.com/Xtra-Computing/thundersvm ``` -- [PyPi](https://pypi.org/project/thundersvm) (πŸ“₯ 840 / month Β· ⏱️ 13.03.2020): +- [PyPi](https://pypi.org/project/thundersvm) (πŸ“₯ 690 / month Β· ⏱️ 13.03.2020): ``` pip install thundersvm ```
-
Objax (πŸ₯‰21 Β· ⭐ 760) - Objax is a machine learning framework that provides an Object.. Apache-2 +
Objax (πŸ₯‰21 Β· ⭐ 770 Β· πŸ’€) - Objax is a machine learning framework that provides an Object.. Apache-2 -- [GitHub](https://github.com/google/objax) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 78 Β· πŸ“¦ 54 Β· πŸ“‹ 110 - 45% open Β· ⏱️ 27.01.2024): +- [GitHub](https://github.com/google/objax) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 78 Β· πŸ“¦ 55 Β· πŸ“‹ 110 - 45% open Β· ⏱️ 27.01.2024): ``` git clone https://github.com/google/objax ``` -- [PyPi](https://pypi.org/project/objax) (πŸ“₯ 630 / month Β· πŸ“¦ 4 Β· ⏱️ 06.11.2023): +- [PyPi](https://pypi.org/project/objax) (πŸ“₯ 560 / month Β· πŸ“¦ 4 Β· ⏱️ 06.11.2023): ``` pip install objax ```
NeoML (πŸ₯‰21 Β· ⭐ 760) - Machine learning framework for both deep learning and traditional.. Apache-2 -- [GitHub](https://github.com/neoml-lib/neoml) (πŸ‘¨β€πŸ’» 37 Β· πŸ”€ 120 Β· πŸ“‹ 87 - 42% open Β· ⏱️ 29.05.2024): +- [GitHub](https://github.com/neoml-lib/neoml) (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 130 Β· πŸ“¦ 1 Β· πŸ“‹ 91 - 40% open Β· ⏱️ 04.09.2024): ``` git clone https://github.com/neoml-lib/neoml ``` -- [PyPi](https://pypi.org/project/neoml) (πŸ“₯ 130 / month Β· ⏱️ 26.12.2023): +- [PyPi](https://pypi.org/project/neoml) (πŸ“₯ 480 / month Β· ⏱️ 26.12.2023): ``` pip install neoml ```
-
Torchbearer (πŸ₯‰21 Β· ⭐ 630) - torchbearer: A model fitting library for PyTorch. MIT +
Torchbearer (πŸ₯‰21 Β· ⭐ 630 Β· πŸ’€) - torchbearer: A model fitting library for PyTorch. MIT -- [GitHub](https://github.com/pytorchbearer/torchbearer) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 68 Β· πŸ“¦ 88 Β· πŸ“‹ 250 - 4% open Β· ⏱️ 04.12.2023): +- [GitHub](https://github.com/pytorchbearer/torchbearer) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 68 Β· πŸ“¦ 90 Β· πŸ“‹ 250 - 4% open Β· ⏱️ 04.12.2023): ``` git clone https://github.com/pytorchbearer/torchbearer ``` -- [PyPi](https://pypi.org/project/torchbearer) (πŸ“₯ 390 / month Β· πŸ“¦ 4 Β· ⏱️ 01.12.2023): +- [PyPi](https://pypi.org/project/torchbearer) (πŸ“₯ 340 / month Β· πŸ“¦ 4 Β· ⏱️ 01.12.2023): ``` pip install torchbearer ```
-
chefboost (πŸ₯‰20 Β· ⭐ 440) - A Lightweight Decision Tree Framework supporting regular algorithms:.. MIT - -- [GitHub](https://github.com/serengil/chefboost) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 100 Β· πŸ“¦ 53 Β· πŸ“‹ 49 - 14% open Β· ⏱️ 26.12.2023): - - ``` - git clone https://github.com/serengil/chefboost - ``` -- [PyPi](https://pypi.org/project/chefboost) (πŸ“₯ 2.6K / month Β· ⏱️ 16.02.2022): - ``` - pip install chefboost - ``` -
-
ThunderGBM (πŸ₯‰17 Β· ⭐ 690) - ThunderGBM: Fast GBDTs and Random Forests on GPUs. Apache-2 +
ThunderGBM (πŸ₯‰17 Β· ⭐ 690 Β· πŸ’€) - ThunderGBM: Fast GBDTs and Random Forests on GPUs. Apache-2 -- [GitHub](https://github.com/Xtra-Computing/thundergbm) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 87 Β· πŸ“¦ 2 Β· πŸ“‹ 81 - 48% open Β· ⏱️ 29.01.2024): +- [GitHub](https://github.com/Xtra-Computing/thundergbm) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 87 Β· πŸ“¦ 3 Β· πŸ“‹ 81 - 48% open Β· ⏱️ 29.01.2024): ``` git clone https://github.com/Xtra-Computing/thundergbm ``` -- [PyPi](https://pypi.org/project/thundergbm) (πŸ“₯ 220 / month Β· ⏱️ 19.09.2022): +- [PyPi](https://pypi.org/project/thundergbm) (πŸ“₯ 100 / month Β· ⏱️ 19.09.2022): ``` pip install thundergbm ```
-
Show 15 hidden projects... +
Show 16 hidden projects... -- dlib (πŸ₯ˆ41 Β· ⭐ 13K) - A toolkit for making real world machine learning and data analysis.. ❗️BSL-1.0 +- dlib (πŸ₯ˆ40 Β· ⭐ 13K) - A toolkit for making real world machine learning and data analysis.. ❗️BSL-1.0 - MXNet (πŸ₯ˆ38 Β· ⭐ 21K Β· πŸ’€) - Lightweight, Portable, Flexible Distributed/Mobile Deep.. Apache-2 -- MindsDB (πŸ₯ˆ34 Β· ⭐ 22K) - The platform for customizing AI from enterprise data. ❗️libpng-2.0 +- MindsDB (πŸ₯‰33 Β· ⭐ 26K) - The platform for building AI from enterprise data. ❗️libpng-2.0 - Chainer (πŸ₯‰33 Β· ⭐ 5.9K Β· πŸ’€) - A flexible framework of neural networks for deep learning. MIT - Turi Create (πŸ₯‰32 Β· ⭐ 11K Β· πŸ’€) - Turi Create simplifies the development of custom machine.. BSD-3 -- TFlearn (πŸ₯‰32 Β· ⭐ 9.6K Β· πŸ’€) - Deep learning library featuring a higher-level API for TensorFlow. MIT -- CNTK (πŸ₯‰30 Β· ⭐ 17K Β· πŸ’€) - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit. MIT +- tensorpack (πŸ₯‰32 Β· ⭐ 6.3K Β· πŸ’€) - A Neural Net Training Interface on TensorFlow, with.. Apache-2 +- TFlearn (πŸ₯‰31 Β· ⭐ 9.6K Β· πŸ’€) - Deep learning library featuring a higher-level API for TensorFlow. MIT +- CNTK (πŸ₯‰29 Β· ⭐ 17K Β· πŸ’€) - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit. MIT - Lasagne (πŸ₯‰28 Β· ⭐ 3.8K Β· πŸ’€) - Lightweight library to build and train neural networks in Theano. MIT -- NuPIC (πŸ₯‰27 Β· ⭐ 6.3K Β· πŸ’€) - Numenta Platform for Intelligent Computing is an implementation.. ❗️AGPL-3.0 +- NuPIC (πŸ₯‰27 Β· ⭐ 6.3K Β· πŸ’€) - Numenta Platform for Intelligent Computing is an implementation.. ❗️AGPL-3.0 - xLearn (πŸ₯‰24 Β· ⭐ 3.1K Β· πŸ’€) - High performance, easy-to-use, and scalable machine learning (ML).. Apache-2 - NeuPy (πŸ₯‰24 Β· ⭐ 740 Β· πŸ’€) - NeuPy is a Tensorflow based python library for prototyping and building.. MIT -- neon (πŸ₯‰22 Β· ⭐ 3.9K Β· πŸ’€) - Intel Nervana reference deep learning framework committed to best.. Apache-2 +- neon (πŸ₯‰23 Β· ⭐ 3.9K Β· πŸ’€) - Intel Nervana reference deep learning framework committed to best.. Apache-2 - elegy (πŸ₯‰19 Β· ⭐ 470 Β· πŸ’€) - A High Level API for Deep Learning in JAX. MIT - StarSpace (πŸ₯‰16 Β· ⭐ 3.9K Β· πŸ’€) - Learning embeddings for classification, retrieval and ranking. MIT -- nanodl (πŸ₯‰16 Β· ⭐ 260) - A Jax-based library for designing and training transformer models from.. MIT +- nanodl (πŸ₯‰16 Β· ⭐ 270) - A Jax-based library for designing and training transformer models from.. MIT

@@ -799,639 +796,647 @@ _General-purpose and task-specific data visualization libraries._
Matplotlib (πŸ₯‡48 Β· ⭐ 20K) - matplotlib: plotting with Python. ❗Unlicensed -- [GitHub](https://github.com/matplotlib/matplotlib) (πŸ‘¨β€πŸ’» 1.7K Β· πŸ”€ 7.4K Β· πŸ“¦ 1.2M Β· πŸ“‹ 11K - 14% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/matplotlib/matplotlib) (πŸ‘¨β€πŸ’» 1.7K Β· πŸ”€ 7.6K Β· πŸ“¦ 1.3M Β· πŸ“‹ 11K - 14% open Β· ⏱️ 03.09.2024): ``` git clone https://github.com/matplotlib/matplotlib ``` -- [PyPi](https://pypi.org/project/matplotlib) (πŸ“₯ 66M / month Β· πŸ“¦ 45K Β· ⏱️ 15.05.2024): +- [PyPi](https://pypi.org/project/matplotlib) (πŸ“₯ 72M / month Β· πŸ“¦ 49K Β· ⏱️ 13.08.2024): ``` pip install matplotlib ``` -- [Conda](https://anaconda.org/conda-forge/matplotlib) (πŸ“₯ 24M Β· ⏱️ 17.05.2024): +- [Conda](https://anaconda.org/conda-forge/matplotlib) (πŸ“₯ 26M Β· ⏱️ 22.08.2024): ``` conda install -c conda-forge matplotlib ```
Bokeh (πŸ₯‡45 Β· ⭐ 19K) - Interactive Data Visualization in the browser, from Python. BSD-3 -- [GitHub](https://github.com/bokeh/bokeh) (πŸ‘¨β€πŸ’» 690 Β· πŸ”€ 4.2K Β· πŸ“¦ 89K Β· πŸ“‹ 7.7K - 10% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/bokeh/bokeh) (πŸ‘¨β€πŸ’» 700 Β· πŸ”€ 4.2K Β· πŸ“¦ 92K Β· πŸ“‹ 7.7K - 9% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/bokeh/bokeh ``` -- [PyPi](https://pypi.org/project/bokeh) (πŸ“₯ 4M / month Β· πŸ“¦ 1.6K Β· ⏱️ 04.06.2024): +- [PyPi](https://pypi.org/project/bokeh) (πŸ“₯ 4.3M / month Β· πŸ“¦ 1.7K Β· ⏱️ 23.08.2024): ``` pip install bokeh ``` -- [Conda](https://anaconda.org/conda-forge/bokeh) (πŸ“₯ 14M Β· ⏱️ 12.04.2024): +- [Conda](https://anaconda.org/conda-forge/bokeh) (πŸ“₯ 15M Β· ⏱️ 23.08.2024): ``` conda install -c conda-forge bokeh ```
-
Plotly (πŸ₯‡44 Β· ⭐ 15K) - The interactive graphing library for Python This project now includes.. MIT +
Plotly (πŸ₯‡44 Β· ⭐ 16K) - The interactive graphing library for Python This project now includes.. MIT -- [GitHub](https://github.com/plotly/plotly.py) (πŸ‘¨β€πŸ’» 260 Β· πŸ”€ 2.5K Β· πŸ“¦ 270K Β· πŸ“‹ 2.9K - 51% open Β· ⏱️ 03.06.2024): +- [GitHub](https://github.com/plotly/plotly.py) (πŸ‘¨β€πŸ’» 260 Β· πŸ”€ 2.5K Β· πŸ“¦ 300K Β· πŸ“‹ 3K - 17% open Β· ⏱️ 29.08.2024): ``` git clone https://github.com/plotly/plotly.py ``` -- [PyPi](https://pypi.org/project/plotly) (πŸ“₯ 16M / month Β· πŸ“¦ 5.6K Β· ⏱️ 01.05.2024): +- [PyPi](https://pypi.org/project/plotly) (πŸ“₯ 18M / month Β· πŸ“¦ 6.1K Β· ⏱️ 29.08.2024): ``` pip install plotly ``` -- [Conda](https://anaconda.org/conda-forge/plotly) (πŸ“₯ 6M Β· ⏱️ 04.05.2024): +- [Conda](https://anaconda.org/conda-forge/plotly) (πŸ“₯ 6.8M Β· ⏱️ 30.08.2024): ``` conda install -c conda-forge plotly ``` -- [npm](https://www.npmjs.com/package/plotlywidget) (πŸ“₯ 14K / month Β· πŸ“¦ 9 Β· ⏱️ 12.01.2021): +- [npm](https://www.npmjs.com/package/plotlywidget) (πŸ“₯ 5.7K / month Β· πŸ“¦ 9 Β· ⏱️ 12.01.2021): ``` npm install plotlywidget ```
-
Seaborn (πŸ₯‡43 Β· ⭐ 12K) - Statistical data visualization in Python. BSD-3 +
dash (πŸ₯‡42 Β· ⭐ 21K) - Data Apps & Dashboards for Python. No JavaScript Required. MIT -- [GitHub](https://github.com/mwaskom/seaborn) (πŸ‘¨β€πŸ’» 210 Β· πŸ”€ 1.9K Β· πŸ“₯ 390 Β· πŸ“¦ 420K Β· πŸ“‹ 2.5K - 5% open Β· ⏱️ 25.04.2024): +- [GitHub](https://github.com/plotly/dash) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 2K Β· πŸ“₯ 76 Β· πŸ“¦ 68K Β· πŸ“‹ 1.8K - 25% open Β· ⏱️ 04.09.2024): ``` - git clone https://github.com/mwaskom/seaborn + git clone https://github.com/plotly/dash ``` -- [PyPi](https://pypi.org/project/seaborn) (πŸ“₯ 17M / month Β· πŸ“¦ 9.7K Β· ⏱️ 25.01.2024): +- [PyPi](https://pypi.org/project/dash) (πŸ“₯ 3.2M / month Β· πŸ“¦ 1.3K Β· ⏱️ 04.09.2024): ``` - pip install seaborn + pip install dash ``` -- [Conda](https://anaconda.org/conda-forge/seaborn) (πŸ“₯ 8.9M Β· ⏱️ 30.04.2024): +- [Conda](https://anaconda.org/conda-forge/dash) (πŸ“₯ 1.5M Β· ⏱️ 05.09.2024): ``` - conda install -c conda-forge seaborn + conda install -c conda-forge dash ```
-
dash (πŸ₯‡41 Β· ⭐ 21K) - Data Apps & Dashboards for Python. No JavaScript Required. MIT +
Seaborn (πŸ₯‡42 Β· ⭐ 12K) - Statistical data visualization in Python. BSD-3 -- [GitHub](https://github.com/plotly/dash) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 2K Β· πŸ“₯ 72 Β· πŸ“¦ 64K Β· πŸ“‹ 1.8K - 46% open Β· ⏱️ 03.06.2024): +- [GitHub](https://github.com/mwaskom/seaborn) (πŸ‘¨β€πŸ’» 210 Β· πŸ”€ 1.9K Β· πŸ“₯ 420 Β· πŸ“¦ 460K Β· πŸ“‹ 2.6K - 6% open Β· ⏱️ 22.07.2024): ``` - git clone https://github.com/plotly/dash + git clone https://github.com/mwaskom/seaborn ``` -- [PyPi](https://pypi.org/project/dash) (πŸ“₯ 2.9M / month Β· πŸ“¦ 1.2K Β· ⏱️ 03.05.2024): +- [PyPi](https://pypi.org/project/seaborn) (πŸ“₯ 18M / month Β· πŸ“¦ 11K Β· ⏱️ 25.01.2024): ``` - pip install dash + pip install seaborn ``` -- [Conda](https://anaconda.org/conda-forge/dash) (πŸ“₯ 1.3M Β· ⏱️ 04.05.2024): +- [Conda](https://anaconda.org/conda-forge/seaborn) (πŸ“₯ 10M Β· ⏱️ 30.04.2024): ``` - conda install -c conda-forge dash + conda install -c conda-forge seaborn ```
-
Altair (πŸ₯‡41 Β· ⭐ 9K) - Declarative statistical visualization library for Python. BSD-3 +
Altair (πŸ₯‡42 Β· ⭐ 9.2K) - Declarative statistical visualization library for Python. BSD-3 -- [GitHub](https://github.com/vega/altair) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 760 Β· πŸ“₯ 120 Β· πŸ“¦ 140K Β· πŸ“‹ 2K - 8% open Β· ⏱️ 23.05.2024): +- [GitHub](https://github.com/vega/altair) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 780 Β· πŸ“₯ 170 Β· πŸ“¦ 160K Β· πŸ“‹ 2K - 8% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/altair-viz/altair ``` -- [PyPi](https://pypi.org/project/altair) (πŸ“₯ 24M / month Β· πŸ“¦ 770 Β· ⏱️ 30.03.2024): +- [PyPi](https://pypi.org/project/altair) (πŸ“₯ 22M / month Β· πŸ“¦ 840 Β· ⏱️ 27.08.2024): ``` pip install altair ``` -- [Conda](https://anaconda.org/conda-forge/altair) (πŸ“₯ 2.3M Β· ⏱️ 30.03.2024): +- [Conda](https://anaconda.org/conda-forge/altair) (πŸ“₯ 2.4M Β· ⏱️ 27.08.2024): ``` conda install -c conda-forge altair ```
-
pandas-profiling (πŸ₯ˆ38 Β· ⭐ 12K) - 1 Line of code data quality profiling & exploratory.. MIT +
pyecharts (πŸ₯ˆ38 Β· ⭐ 15K) - Python Echarts Plotting Library. MIT -- [GitHub](https://github.com/ydataai/ydata-profiling) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 1.6K Β· πŸ“₯ 100 Β· πŸ“¦ 3.3K Β· πŸ“‹ 780 - 28% open Β· ⏱️ 31.05.2024): +- [GitHub](https://github.com/pyecharts/pyecharts) (πŸ‘¨β€πŸ’» 44 Β· πŸ”€ 2.8K Β· πŸ“₯ 68 Β· πŸ“¦ 4.4K Β· πŸ“‹ 1.9K - 0% open Β· ⏱️ 20.06.2024): ``` - git clone https://github.com/ydataai/pandas-profiling - ``` -- [PyPi](https://pypi.org/project/pandas-profiling) (πŸ“₯ 820K / month Β· πŸ“¦ 180 Β· ⏱️ 03.02.2023): - ``` - pip install pandas-profiling + git clone https://github.com/pyecharts/pyecharts ``` -- [Conda](https://anaconda.org/conda-forge/pandas-profiling) (πŸ“₯ 430K Β· ⏱️ 16.06.2023): +- [PyPi](https://pypi.org/project/pyecharts) (πŸ“₯ 130K / month Β· πŸ“¦ 210 Β· ⏱️ 20.06.2024): ``` - conda install -c conda-forge pandas-profiling + pip install pyecharts ```
-
HoloViews (πŸ₯ˆ38 Β· ⭐ 2.6K) - With Holoviews, your data visualizes itself. BSD-3 +
PyVista (πŸ₯ˆ38 Β· ⭐ 2.6K) - 3D plotting and mesh analysis through a streamlined interface for.. MIT -- [GitHub](https://github.com/holoviz/holoviews) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 390 Β· πŸ“¦ 11K Β· πŸ“‹ 3.3K - 33% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/pyvista/pyvista) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 470 Β· πŸ“₯ 810 Β· πŸ“¦ 3.4K Β· πŸ“‹ 1.7K - 34% open Β· ⏱️ 05.09.2024): ``` - git clone https://github.com/holoviz/holoviews - ``` -- [PyPi](https://pypi.org/project/holoviews) (πŸ“₯ 490K / month Β· πŸ“¦ 360 Β· ⏱️ 23.05.2024): - ``` - pip install holoviews + git clone https://github.com/pyvista/pyvista ``` -- [Conda](https://anaconda.org/conda-forge/holoviews) (πŸ“₯ 1.6M Β· ⏱️ 12.02.2024): +- [PyPi](https://pypi.org/project/pyvista) (πŸ“₯ 270K / month Β· πŸ“¦ 530 Β· ⏱️ 20.07.2024): ``` - conda install -c conda-forge holoviews + pip install pyvista ``` -- [npm](https://www.npmjs.com/package/@pyviz/jupyterlab_pyviz) (πŸ“₯ 200 / month Β· πŸ“¦ 5 Β· ⏱️ 22.03.2024): +- [Conda](https://anaconda.org/conda-forge/pyvista) (πŸ“₯ 540K Β· ⏱️ 20.07.2024): ``` - npm install @pyviz/jupyterlab_pyviz + conda install -c conda-forge pyvista ```
-
plotnine (πŸ₯ˆ37 Β· ⭐ 3.9K Β· πŸ“ˆ) - A Grammar of Graphics for Python. MIT +
pandas-profiling (πŸ₯ˆ37 Β· ⭐ 12K) - 1 Line of code data quality profiling & exploratory.. MIT -- [GitHub](https://github.com/has2k1/plotnine) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 200 Β· πŸ“¦ 7.8K Β· πŸ“‹ 640 - 11% open Β· ⏱️ 30.05.2024): +- [GitHub](https://github.com/ydataai/ydata-profiling) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 1.7K Β· πŸ“₯ 150 Β· πŸ“¦ 4K Β· πŸ“‹ 800 - 28% open Β· ⏱️ 03.09.2024): ``` - git clone https://github.com/has2k1/plotnine + git clone https://github.com/ydataai/pandas-profiling ``` -- [PyPi](https://pypi.org/project/plotnine) (πŸ“₯ 3.3M / month Β· πŸ“¦ 260 Β· ⏱️ 09.05.2024): +- [PyPi](https://pypi.org/project/pandas-profiling) (πŸ“₯ 330K / month Β· πŸ“¦ 180 Β· ⏱️ 03.02.2023): ``` - pip install plotnine + pip install pandas-profiling ``` -- [Conda](https://anaconda.org/conda-forge/plotnine) (πŸ“₯ 370K Β· ⏱️ 10.05.2024): +- [Conda](https://anaconda.org/conda-forge/pandas-profiling) (πŸ“₯ 460K Β· ⏱️ 16.06.2023): ``` - conda install -c conda-forge plotnine + conda install -c conda-forge pandas-profiling ```
-
PyQtGraph (πŸ₯ˆ37 Β· ⭐ 3.7K) - Fast data visualization and GUI tools for scientific / engineering.. MIT +
PyQtGraph (πŸ₯ˆ37 Β· ⭐ 3.8K) - Fast data visualization and GUI tools for scientific / engineering.. MIT -- [GitHub](https://github.com/pyqtgraph/pyqtgraph) (πŸ‘¨β€πŸ’» 280 Β· πŸ”€ 1.1K Β· πŸ“¦ 9.6K Β· πŸ“‹ 1.3K - 30% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/pyqtgraph/pyqtgraph) (πŸ‘¨β€πŸ’» 290 Β· πŸ”€ 1.1K Β· πŸ“¦ 10K Β· πŸ“‹ 1.3K - 31% open Β· ⏱️ 22.08.2024): ``` git clone https://github.com/pyqtgraph/pyqtgraph ``` -- [PyPi](https://pypi.org/project/pyqtgraph) (πŸ“₯ 230K / month Β· πŸ“¦ 940 Β· ⏱️ 29.04.2024): +- [PyPi](https://pypi.org/project/pyqtgraph) (πŸ“₯ 270K / month Β· πŸ“¦ 1K Β· ⏱️ 29.04.2024): ``` pip install pyqtgraph ``` -- [Conda](https://anaconda.org/conda-forge/pyqtgraph) (πŸ“₯ 540K Β· ⏱️ 02.05.2024): +- [Conda](https://anaconda.org/conda-forge/pyqtgraph) (πŸ“₯ 590K Β· ⏱️ 02.05.2024): ``` conda install -c conda-forge pyqtgraph ```
-
Graphviz (πŸ₯ˆ37 Β· ⭐ 1.6K) - Simple Python interface for Graphviz. MIT +
HoloViews (πŸ₯ˆ37 Β· ⭐ 2.7K) - With Holoviews, your data visualizes itself. BSD-3 -- [GitHub](https://github.com/xflr6/graphviz) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 210 Β· πŸ“¦ 67K Β· πŸ“‹ 180 - 7% open Β· ⏱️ 13.05.2024): +- [GitHub](https://github.com/holoviz/holoviews) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 400 Β· πŸ“¦ 12K Β· πŸ“‹ 3.3K - 33% open Β· ⏱️ 29.08.2024): ``` - git clone https://github.com/xflr6/graphviz - ``` -- [PyPi](https://pypi.org/project/graphviz) (πŸ“₯ 12M / month Β· πŸ“¦ 2.4K Β· ⏱️ 21.03.2024): - ``` - pip install graphviz + git clone https://github.com/holoviz/holoviews ``` -- [Conda](https://anaconda.org/anaconda/python-graphviz) (πŸ“₯ 46K Β· ⏱️ 08.04.2024): +- [PyPi](https://pypi.org/project/holoviews) (πŸ“₯ 640K / month Β· πŸ“¦ 380 Β· ⏱️ 31.07.2024): ``` - conda install -c anaconda python-graphviz + pip install holoviews ``` -
-
pyecharts (πŸ₯ˆ36 Β· ⭐ 15K) - Python Echarts Plotting Library. MIT - -- [GitHub](https://github.com/pyecharts/pyecharts) (πŸ‘¨β€πŸ’» 43 Β· πŸ”€ 2.8K Β· πŸ“₯ 58 Β· πŸ“¦ 4.2K Β· πŸ“‹ 1.9K - 0% open Β· ⏱️ 06.06.2024): - +- [Conda](https://anaconda.org/conda-forge/holoviews) (πŸ“₯ 1.7M Β· ⏱️ 07.07.2024): ``` - git clone https://github.com/pyecharts/pyecharts + conda install -c conda-forge holoviews ``` -- [PyPi](https://pypi.org/project/pyecharts) (πŸ“₯ 210K / month Β· πŸ“¦ 190 Β· ⏱️ 03.03.2024): +- [npm](https://www.npmjs.com/package/@pyviz/jupyterlab_pyviz) (πŸ“₯ 180 / month Β· πŸ“¦ 5 Β· ⏱️ 01.08.2024): ``` - pip install pyecharts + npm install @pyviz/jupyterlab_pyviz ```
-
PyVista (πŸ₯ˆ36 Β· ⭐ 2.4K) - 3D plotting and mesh analysis through a streamlined interface for.. MIT +
FiftyOne (πŸ₯ˆ35 Β· ⭐ 8.1K) - Visualize, create, and debug image and video datasets.. Apache-2 -- [GitHub](https://github.com/pyvista/pyvista) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 440 Β· πŸ“₯ 800 Β· πŸ“¦ 3K Β· πŸ“‹ 1.6K - 34% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/voxel51/fiftyone) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 540 Β· πŸ“¦ 680 Β· πŸ“‹ 1.6K - 33% open Β· ⏱️ 04.09.2024): ``` - git clone https://github.com/pyvista/pyvista - ``` -- [PyPi](https://pypi.org/project/pyvista) (πŸ“₯ 280K / month Β· πŸ“¦ 490 Β· ⏱️ 06.06.2024): - ``` - pip install pyvista + git clone https://github.com/voxel51/fiftyone ``` -- [Conda](https://anaconda.org/conda-forge/pyvista) (πŸ“₯ 490K Β· ⏱️ 06.06.2024): +- [PyPi](https://pypi.org/project/fiftyone) (πŸ“₯ 120K / month Β· πŸ“¦ 20 Β· ⏱️ 20.08.2024): ``` - conda install -c conda-forge pyvista + pip install fiftyone ```
-
FiftyOne (πŸ₯ˆ35 Β· ⭐ 6.9K) - Visualize, create, and debug image and video datasets.. Apache-2 +
plotnine (πŸ₯ˆ35 Β· ⭐ 4K) - A Grammar of Graphics for Python. MIT -- [GitHub](https://github.com/voxel51/fiftyone) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 510 Β· πŸ“¦ 590 Β· πŸ“‹ 1.5K - 32% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/has2k1/plotnine) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 210 Β· πŸ“¦ 8.6K Β· πŸ“‹ 670 - 13% open Β· ⏱️ 01.08.2024): ``` - git clone https://github.com/voxel51/fiftyone + git clone https://github.com/has2k1/plotnine ``` -- [PyPi](https://pypi.org/project/fiftyone) (πŸ“₯ 51K / month Β· πŸ“¦ 18 Β· ⏱️ 29.05.2024): +- [PyPi](https://pypi.org/project/plotnine) (πŸ“₯ 2.8M / month Β· πŸ“¦ 300 Β· ⏱️ 09.05.2024): ``` - pip install fiftyone + pip install plotnine + ``` +- [Conda](https://anaconda.org/conda-forge/plotnine) (πŸ“₯ 390K Β· ⏱️ 10.05.2024): + ``` + conda install -c conda-forge plotnine ```
-
VisPy (πŸ₯ˆ35 Β· ⭐ 3.2K) - High-performance interactive 2D/3D data visualization library. BSD-3 +
VisPy (πŸ₯ˆ35 Β· ⭐ 3.3K) - High-performance interactive 2D/3D data visualization library. BSD-3 -- [GitHub](https://github.com/vispy/vispy) (πŸ‘¨β€πŸ’» 200 Β· πŸ”€ 620 Β· πŸ“¦ 1.5K Β· πŸ“‹ 1.5K - 23% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/vispy/vispy) (πŸ‘¨β€πŸ’» 200 Β· πŸ”€ 620 Β· πŸ“¦ 1.7K Β· πŸ“‹ 1.5K - 24% open Β· ⏱️ 27.08.2024): ``` git clone https://github.com/vispy/vispy ``` -- [PyPi](https://pypi.org/project/vispy) (πŸ“₯ 90K / month Β· πŸ“¦ 150 Β· ⏱️ 14.03.2024): +- [PyPi](https://pypi.org/project/vispy) (πŸ“₯ 180K / month Β· πŸ“¦ 170 Β· ⏱️ 17.06.2024): ``` pip install vispy ``` -- [Conda](https://anaconda.org/conda-forge/vispy) (πŸ“₯ 500K Β· ⏱️ 17.05.2024): +- [Conda](https://anaconda.org/conda-forge/vispy) (πŸ“₯ 590K Β· ⏱️ 04.09.2024): ``` conda install -c conda-forge vispy ``` -- [npm](https://www.npmjs.com/package/vispy) (πŸ“₯ 13 / month Β· πŸ“¦ 3 Β· ⏱️ 15.03.2020): +- [npm](https://www.npmjs.com/package/vispy) (πŸ“₯ 8 / month Β· πŸ“¦ 3 Β· ⏱️ 15.03.2020): ``` npm install vispy ```
-
cartopy (πŸ₯ˆ35 Β· ⭐ 1.4K) - Cartopy - a cartographic python library with matplotlib support. BSD-3 +
UMAP (πŸ₯ˆ34 Β· ⭐ 7.3K) - Uniform Manifold Approximation and Projection. BSD-3 -- [GitHub](https://github.com/SciTools/cartopy) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 360 Β· πŸ“¦ 5K Β· πŸ“‹ 1.3K - 24% open Β· ⏱️ 21.05.2024): +- [GitHub](https://github.com/lmcinnes/umap) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 800 Β· πŸ“¦ 1 Β· πŸ“‹ 810 - 58% open Β· ⏱️ 18.08.2024): ``` - git clone https://github.com/SciTools/cartopy + git clone https://github.com/lmcinnes/umap ``` -- [PyPi](https://pypi.org/project/cartopy) (πŸ“₯ 220K / month Β· πŸ“¦ 590 Β· ⏱️ 10.04.2024): +- [PyPi](https://pypi.org/project/umap-learn) (πŸ“₯ 1.4M / month Β· πŸ“¦ 960 Β· ⏱️ 03.04.2024): ``` - pip install cartopy + pip install umap-learn ``` -- [Conda](https://anaconda.org/conda-forge/cartopy) (πŸ“₯ 3.6M Β· ⏱️ 16.05.2024): +- [Conda](https://anaconda.org/conda-forge/umap-learn) (πŸ“₯ 2.6M Β· ⏱️ 14.08.2024): ``` - conda install -c conda-forge cartopy + conda install -c conda-forge umap-learn ```
-
datashader (πŸ₯ˆ34 Β· ⭐ 3.2K) - Quickly and accurately render even the largest data. BSD-3 +
Graphviz (πŸ₯ˆ34 Β· ⭐ 1.6K Β· πŸ“‰) - Simple Python interface for Graphviz. MIT -- [GitHub](https://github.com/holoviz/datashader) (πŸ‘¨β€πŸ’» 55 Β· πŸ”€ 360 Β· πŸ“¦ 4.2K Β· πŸ“‹ 580 - 23% open Β· ⏱️ 31.05.2024): +- [GitHub](https://github.com/xflr6/graphviz) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 210 Β· πŸ“¦ 72K Β· πŸ“‹ 180 - 7% open Β· ⏱️ 13.05.2024): ``` - git clone https://github.com/holoviz/datashader + git clone https://github.com/xflr6/graphviz ``` -- [PyPi](https://pypi.org/project/datashader) (πŸ“₯ 120K / month Β· πŸ“¦ 180 Β· ⏱️ 31.05.2024): +- [PyPi](https://pypi.org/project/graphviz) (πŸ“₯ 13M / month Β· πŸ“¦ 2.6K Β· ⏱️ 21.03.2024): ``` - pip install datashader + pip install graphviz ``` -- [Conda](https://anaconda.org/conda-forge/datashader) (πŸ“₯ 910K Β· ⏱️ 31.05.2024): +- [Conda](https://anaconda.org/anaconda/python-graphviz) (πŸ“₯ 49K Β· ⏱️ 08.04.2024): ``` - conda install -c conda-forge datashader + conda install -c anaconda python-graphviz ```
-
UMAP (πŸ₯ˆ33 Β· ⭐ 7.1K) - Uniform Manifold Approximation and Projection. BSD-3 +
cartopy (πŸ₯ˆ34 Β· ⭐ 1.4K) - Cartopy - a cartographic python library with matplotlib support. BSD-3 -- [GitHub](https://github.com/lmcinnes/umap) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 760 Β· πŸ“¦ 1 Β· πŸ“‹ 790 - 57% open Β· ⏱️ 25.04.2024): +- [GitHub](https://github.com/SciTools/cartopy) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 360 Β· πŸ“¦ 5.5K Β· πŸ“‹ 1.3K - 24% open Β· ⏱️ 03.09.2024): ``` - git clone https://github.com/lmcinnes/umap + git clone https://github.com/SciTools/cartopy ``` -- [PyPi](https://pypi.org/project/umap-learn) (πŸ“₯ 1.4M / month Β· πŸ“¦ 830 Β· ⏱️ 03.04.2024): +- [PyPi](https://pypi.org/project/cartopy) (πŸ“₯ 300K / month Β· πŸ“¦ 680 Β· ⏱️ 10.04.2024): ``` - pip install umap-learn + pip install cartopy ``` -- [Conda](https://anaconda.org/conda-forge/umap-learn) (πŸ“₯ 2.4M Β· ⏱️ 04.02.2024): +- [Conda](https://anaconda.org/conda-forge/cartopy) (πŸ“₯ 4M Β· ⏱️ 16.05.2024): ``` - conda install -c conda-forge umap-learn + conda install -c conda-forge cartopy ```
-
wordcloud (πŸ₯ˆ32 Β· ⭐ 10K Β· πŸ“‰) - A little word cloud generator in Python. MIT +
wordcloud (πŸ₯ˆ33 Β· ⭐ 10K Β· πŸ’€) - A little word cloud generator in Python. MIT -- [GitHub](https://github.com/amueller/word_cloud) (πŸ‘¨β€πŸ’» 72 Β· πŸ”€ 2.3K Β· πŸ“¦ 21 Β· πŸ“‹ 540 - 22% open Β· ⏱️ 09.12.2023): +- [GitHub](https://github.com/amueller/word_cloud) (πŸ‘¨β€πŸ’» 72 Β· πŸ”€ 2.3K Β· πŸ“¦ 21 Β· πŸ“‹ 540 - 23% open Β· ⏱️ 09.12.2023): ``` git clone https://github.com/amueller/word_cloud ``` -- [PyPi](https://pypi.org/project/wordcloud) (πŸ“₯ 2M / month Β· πŸ“¦ 500 Β· ⏱️ 09.12.2023): +- [PyPi](https://pypi.org/project/wordcloud) (πŸ“₯ 1.4M / month Β· πŸ“¦ 520 Β· ⏱️ 09.12.2023): ``` pip install wordcloud ``` -- [Conda](https://anaconda.org/conda-forge/wordcloud) (πŸ“₯ 490K Β· ⏱️ 19.03.2024): +- [Conda](https://anaconda.org/conda-forge/wordcloud) (πŸ“₯ 530K Β· ⏱️ 19.03.2024): ``` conda install -c conda-forge wordcloud ```
-
Perspective (πŸ₯ˆ31 Β· ⭐ 7.7K) - A data visualization and analytics component, especially.. Apache-2 +
Perspective (πŸ₯ˆ33 Β· ⭐ 8.3K) - A data visualization and analytics component, especially.. Apache-2 -- [GitHub](https://github.com/finos/perspective) (πŸ‘¨β€πŸ’» 93 Β· πŸ”€ 1K Β· πŸ“₯ 2.9K Β· πŸ“¦ 120 Β· πŸ“‹ 760 - 13% open Β· ⏱️ 29.05.2024): +- [GitHub](https://github.com/finos/perspective) (πŸ‘¨β€πŸ’» 94 Β· πŸ”€ 1.1K Β· πŸ“₯ 3.8K Β· πŸ“¦ 140 Β· πŸ“‹ 790 - 12% open Β· ⏱️ 03.09.2024): ``` git clone https://github.com/finos/perspective ``` -- [PyPi](https://pypi.org/project/perspective-python) (πŸ“₯ 5.9K / month Β· πŸ“¦ 22 Β· ⏱️ 23.05.2024): +- [PyPi](https://pypi.org/project/perspective-python) (πŸ“₯ 8.1K / month Β· πŸ“¦ 24 Β· ⏱️ 03.09.2024): ``` pip install perspective-python ``` -- [Conda](https://anaconda.org/conda-forge/perspective) (πŸ“₯ 650K Β· ⏱️ 23.05.2024): +- [Conda](https://anaconda.org/conda-forge/perspective) (πŸ“₯ 1.1M Β· ⏱️ 24.08.2024): ``` conda install -c conda-forge perspective ``` -- [npm](https://www.npmjs.com/package/@finos/perspective-jupyterlab) (πŸ“₯ 3.8K / month Β· πŸ“¦ 6 Β· ⏱️ 23.05.2024): +- [npm](https://www.npmjs.com/package/@finos/perspective-jupyterlab) (πŸ“₯ 3.8K / month Β· πŸ“¦ 6 Β· ⏱️ 03.09.2024): ``` npm install @finos/perspective-jupyterlab ```
-
lets-plot (πŸ₯ˆ31 Β· ⭐ 1.5K) - Multiplatform plotting library based on the Grammar of Graphics. MIT +
datashader (πŸ₯ˆ33 Β· ⭐ 3.3K) - Quickly and accurately render even the largest data. BSD-3 -- [GitHub](https://github.com/JetBrains/lets-plot) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 47 Β· πŸ“₯ 720 Β· πŸ“¦ 79 Β· πŸ“‹ 560 - 24% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/holoviz/datashader) (πŸ‘¨β€πŸ’» 56 Β· πŸ”€ 360 Β· πŸ“¦ 4.7K Β· πŸ“‹ 580 - 23% open Β· ⏱️ 08.08.2024): ``` - git clone https://github.com/JetBrains/lets-plot + git clone https://github.com/holoviz/datashader ``` -- [PyPi](https://pypi.org/project/lets-plot) (πŸ“₯ 19K / month Β· πŸ“¦ 13 Β· ⏱️ 29.05.2024): +- [PyPi](https://pypi.org/project/datashader) (πŸ“₯ 110K / month Β· πŸ“¦ 190 Β· ⏱️ 04.07.2024): ``` - pip install lets-plot + pip install datashader ``` -
-
hvPlot (πŸ₯ˆ31 Β· ⭐ 980) - A high-level plotting API for pandas, dask, xarray, and networkx built on.. BSD-3 - -- [GitHub](https://github.com/holoviz/hvplot) (πŸ‘¨β€πŸ’» 46 Β· πŸ”€ 99 Β· πŸ“¦ 5.1K Β· πŸ“‹ 760 - 44% open Β· ⏱️ 06.05.2024): - +- [Conda](https://anaconda.org/conda-forge/datashader) (πŸ“₯ 1.1M Β· ⏱️ 08.07.2024): ``` - git clone https://github.com/holoviz/hvplot + conda install -c conda-forge datashader ``` -- [PyPi](https://pypi.org/project/hvplot) (πŸ“₯ 240K / month Β· πŸ“¦ 170 Β· ⏱️ 06.05.2024): +
+
lets-plot (πŸ₯ˆ31 Β· ⭐ 1.5K) - Multiplatform plotting library based on the Grammar of Graphics. MIT + +- [GitHub](https://github.com/JetBrains/lets-plot) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 49 Β· πŸ“₯ 930 Β· πŸ“¦ 120 Β· πŸ“‹ 590 - 23% open Β· ⏱️ 04.09.2024): + ``` - pip install hvplot + git clone https://github.com/JetBrains/lets-plot ``` -- [Conda](https://anaconda.org/conda-forge/hvplot) (πŸ“₯ 580K Β· ⏱️ 07.05.2024): +- [PyPi](https://pypi.org/project/lets-plot) (πŸ“₯ 19K / month Β· πŸ“¦ 13 Β· ⏱️ 21.08.2024): ``` - conda install -c conda-forge hvplot + pip install lets-plot ```
-
D-Tale (πŸ₯‰30 Β· ⭐ 4.6K) - Visualizer for pandas data structures. ❗️LGPL-2.1 +
hvPlot (πŸ₯ˆ31 Β· ⭐ 1.1K) - A high-level plotting API for pandas, dask, xarray, and networkx built.. BSD-3 -- [GitHub](https://github.com/man-group/dtale) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 380 Β· πŸ“¦ 1.1K Β· πŸ“‹ 580 - 10% open Β· ⏱️ 30.04.2024): +- [GitHub](https://github.com/holoviz/hvplot) (πŸ‘¨β€πŸ’» 47 Β· πŸ”€ 100 Β· πŸ“¦ 5.7K Β· πŸ“‹ 800 - 44% open Β· ⏱️ 29.08.2024): ``` - git clone https://github.com/man-group/dtale + git clone https://github.com/holoviz/hvplot ``` -- [PyPi](https://pypi.org/project/dtale) (πŸ“₯ 73K / month Β· πŸ“¦ 39 Β· ⏱️ 30.04.2024): +- [PyPi](https://pypi.org/project/hvplot) (πŸ“₯ 230K / month Β· πŸ“¦ 190 Β· ⏱️ 23.07.2024): ``` - pip install dtale + pip install hvplot ``` -- [Conda](https://anaconda.org/conda-forge/dtale) (πŸ“₯ 290K Β· ⏱️ 30.04.2024): +- [Conda](https://anaconda.org/conda-forge/hvplot) (πŸ“₯ 630K Β· ⏱️ 07.05.2024): ``` - conda install -c conda-forge dtale + conda install -c conda-forge hvplot ```
-
bqplot (πŸ₯‰30 Β· ⭐ 3.6K) - Plotting library for IPython/Jupyter notebooks. Apache-2 +
D-Tale (πŸ₯‰30 Β· ⭐ 4.7K) - Visualizer for pandas data structures. ❗️LGPL-2.1 -- [GitHub](https://github.com/bqplot/bqplot) (πŸ‘¨β€πŸ’» 64 Β· πŸ”€ 460 Β· πŸ“¦ 55 Β· πŸ“‹ 620 - 41% open Β· ⏱️ 21.05.2024): +- [GitHub](https://github.com/man-group/dtale) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 390 Β· πŸ“¦ 1.2K Β· πŸ“‹ 590 - 10% open Β· ⏱️ 05.09.2024): ``` - git clone https://github.com/bqplot/bqplot - ``` -- [PyPi](https://pypi.org/project/bqplot) (πŸ“₯ 120K / month Β· πŸ“¦ 92 Β· ⏱️ 25.03.2024): - ``` - pip install bqplot + git clone https://github.com/man-group/dtale ``` -- [Conda](https://anaconda.org/conda-forge/bqplot) (πŸ“₯ 1.3M Β· ⏱️ 19.02.2024): +- [PyPi](https://pypi.org/project/dtale) (πŸ“₯ 38K / month Β· πŸ“¦ 43 Β· ⏱️ 28.06.2024): ``` - conda install -c conda-forge bqplot + pip install dtale ``` -- [npm](https://www.npmjs.com/package/bqplot) (πŸ“₯ 3K / month Β· πŸ“¦ 21 Β· ⏱️ 25.03.2024): +- [Conda](https://anaconda.org/conda-forge/dtale) (πŸ“₯ 330K Β· ⏱️ 28.06.2024): ``` - npm install bqplot + conda install -c conda-forge dtale ```
-
mpld3 (πŸ₯‰30 Β· ⭐ 2.3K) - An interactive data visualization tool which brings matplotlib graphics to.. BSD-3 +
mpld3 (πŸ₯‰29 Β· ⭐ 2.3K Β· πŸ’€) - An interactive data visualization tool which brings matplotlib.. BSD-3 -- [GitHub](https://github.com/mpld3/mpld3) (πŸ‘¨β€πŸ’» 52 Β· πŸ”€ 360 Β· πŸ“¦ 6.1K Β· πŸ“‹ 360 - 59% open Β· ⏱️ 23.12.2023): +- [GitHub](https://github.com/mpld3/mpld3) (πŸ‘¨β€πŸ’» 52 Β· πŸ”€ 360 Β· πŸ“¦ 6.4K Β· πŸ“‹ 360 - 59% open Β· ⏱️ 23.12.2023): ``` git clone https://github.com/mpld3/mpld3 ``` -- [PyPi](https://pypi.org/project/mpld3) (πŸ“₯ 530K / month Β· πŸ“¦ 130 Β· ⏱️ 23.12.2023): +- [PyPi](https://pypi.org/project/mpld3) (πŸ“₯ 320K / month Β· πŸ“¦ 140 Β· ⏱️ 23.12.2023): ``` pip install mpld3 ``` -- [Conda](https://anaconda.org/conda-forge/mpld3) (πŸ“₯ 200K Β· ⏱️ 23.12.2023): +- [Conda](https://anaconda.org/conda-forge/mpld3) (πŸ“₯ 210K Β· ⏱️ 23.12.2023): ``` conda install -c conda-forge mpld3 ``` -- [npm](https://www.npmjs.com/package/mpld3) (πŸ“₯ 790 / month Β· πŸ“¦ 9 Β· ⏱️ 23.12.2023): +- [npm](https://www.npmjs.com/package/mpld3) (πŸ“₯ 1K / month Β· πŸ“¦ 9 Β· ⏱️ 23.12.2023): ``` npm install mpld3 ```
-
data-validation (πŸ₯‰30 Β· ⭐ 750) - Library for exploring and validating machine learning.. Apache-2 +
bqplot (πŸ₯‰28 Β· ⭐ 3.6K) - Plotting library for IPython/Jupyter notebooks. Apache-2 -- [GitHub](https://github.com/tensorflow/data-validation) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 170 Β· πŸ“₯ 650 Β· πŸ“¦ 900 Β· πŸ“‹ 180 - 20% open Β· ⏱️ 03.06.2024): +- [GitHub](https://github.com/bqplot/bqplot) (πŸ‘¨β€πŸ’» 65 Β· πŸ”€ 460 Β· πŸ“¦ 58 Β· πŸ“‹ 630 - 41% open Β· ⏱️ 03.09.2024): ``` - git clone https://github.com/tensorflow/data-validation + git clone https://github.com/bqplot/bqplot ``` -- [PyPi](https://pypi.org/project/tensorflow-data-validation) (πŸ“₯ 200K / month Β· πŸ“¦ 31 Β· ⏱️ 24.04.2024): +- [PyPi](https://pypi.org/project/bqplot) (πŸ“₯ 140K / month Β· πŸ“¦ 98 Β· ⏱️ 25.03.2024): ``` - pip install tensorflow-data-validation + pip install bqplot + ``` +- [Conda](https://anaconda.org/conda-forge/bqplot) (πŸ“₯ 1.4M Β· ⏱️ 19.02.2024): + ``` + conda install -c conda-forge bqplot + ``` +- [npm](https://www.npmjs.com/package/bqplot) (πŸ“₯ 2.5K / month Β· πŸ“¦ 21 Β· ⏱️ 25.03.2024): + ``` + npm install bqplot ```
-
AutoViz (πŸ₯‰28 Β· ⭐ 1.7K) - Automatically Visualize any dataset, any size with a single line of.. Apache-2 +
openTSNE (πŸ₯‰28 Β· ⭐ 1.4K) - Extensible, parallel implementations of t-SNE. BSD-3 -- [GitHub](https://github.com/AutoViML/AutoViz) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 200 Β· πŸ“¦ 690 Β· πŸ“‹ 92 - 2% open Β· ⏱️ 29.04.2024): +- [GitHub](https://github.com/pavlin-policar/openTSNE) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 160 Β· πŸ“¦ 860 Β· πŸ“‹ 140 - 3% open Β· ⏱️ 13.08.2024): ``` - git clone https://github.com/AutoViML/AutoViz + git clone https://github.com/pavlin-policar/openTSNE ``` -- [PyPi](https://pypi.org/project/autoviz) (πŸ“₯ 40K / month Β· πŸ“¦ 7 Β· ⏱️ 29.04.2024): +- [PyPi](https://pypi.org/project/opentsne) (πŸ“₯ 38K / month Β· πŸ“¦ 47 Β· ⏱️ 13.08.2024): ``` - pip install autoviz + pip install opentsne ``` -- [Conda](https://anaconda.org/conda-forge/autoviz) (πŸ“₯ 52K Β· ⏱️ 26.04.2024): +- [Conda](https://anaconda.org/conda-forge/opentsne) (πŸ“₯ 300K Β· ⏱️ 19.05.2024): ``` - conda install -c conda-forge autoviz + conda install -c conda-forge opentsne ```
-
Sweetviz (πŸ₯‰26 Β· ⭐ 2.8K Β· πŸ’€) - Visualize and compare datasets, target values and associations, with.. MIT +
Sweetviz (πŸ₯‰27 Β· ⭐ 2.9K Β· πŸ’€) - Visualize and compare datasets, target values and associations, with.. MIT -- [GitHub](https://github.com/fbdesignpro/sweetviz) (πŸ‘¨β€πŸ’» 11 Β· πŸ”€ 260 Β· πŸ“¦ 2.3K Β· πŸ“‹ 130 - 27% open Β· ⏱️ 29.11.2023): +- [GitHub](https://github.com/fbdesignpro/sweetviz) (πŸ‘¨β€πŸ’» 11 Β· πŸ”€ 270 Β· πŸ“¦ 2.4K Β· πŸ“‹ 140 - 29% open Β· ⏱️ 29.11.2023): ``` git clone https://github.com/fbdesignpro/sweetviz ``` -- [PyPi](https://pypi.org/project/sweetviz) (πŸ“₯ 67K / month Β· πŸ“¦ 29 Β· ⏱️ 29.11.2023): +- [PyPi](https://pypi.org/project/sweetviz) (πŸ“₯ 71K / month Β· πŸ“¦ 30 Β· ⏱️ 29.11.2023): ``` pip install sweetviz ``` -- [Conda](https://anaconda.org/conda-forge/sweetviz) (πŸ“₯ 30K Β· ⏱️ 04.12.2023): +- [Conda](https://anaconda.org/conda-forge/sweetviz) (πŸ“₯ 33K Β· ⏱️ 04.12.2023): ``` conda install -c conda-forge sweetviz ```
-
HyperTools (πŸ₯‰26 Β· ⭐ 1.8K) - A Python toolbox for gaining geometric insights into high-dimensional.. MIT +
data-validation (πŸ₯‰26 Β· ⭐ 760 Β· πŸ“‰) - Library for exploring and validating machine learning.. Apache-2 -- [GitHub](https://github.com/ContextLab/hypertools) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 160 Β· πŸ“₯ 36 Β· πŸ“¦ 420 Β· πŸ“‹ 200 - 33% open Β· ⏱️ 19.03.2024): +- [GitHub](https://github.com/tensorflow/data-validation) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 170 Β· πŸ“₯ 760 Β· πŸ“‹ 180 - 20% open Β· ⏱️ 04.09.2024): ``` - git clone https://github.com/ContextLab/hypertools + git clone https://github.com/tensorflow/data-validation ``` -- [PyPi](https://pypi.org/project/hypertools) (πŸ“₯ 760 / month Β· πŸ“¦ 2 Β· ⏱️ 12.02.2022): +- [PyPi](https://pypi.org/project/tensorflow-data-validation) (πŸ“₯ 210K / month Β· πŸ“¦ 31 Β· ⏱️ 24.04.2024): ``` - pip install hypertools + pip install tensorflow-data-validation ```
-
openTSNE (πŸ₯‰26 Β· ⭐ 1.4K) - Extensible, parallel implementations of t-SNE. BSD-3 +
HyperTools (πŸ₯‰25 Β· ⭐ 1.8K) - A Python toolbox for gaining geometric insights into high-dimensional.. MIT -- [GitHub](https://github.com/pavlin-policar/openTSNE) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 160 Β· πŸ“¦ 810 Β· πŸ“‹ 130 - 3% open Β· ⏱️ 23.05.2024): +- [GitHub](https://github.com/ContextLab/hypertools) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 160 Β· πŸ“₯ 41 Β· πŸ“¦ 470 Β· πŸ“‹ 200 - 33% open Β· ⏱️ 19.03.2024): ``` - git clone https://github.com/pavlin-policar/openTSNE - ``` -- [PyPi](https://pypi.org/project/opentsne) (πŸ“₯ 39K / month Β· πŸ“¦ 43 Β· ⏱️ 29.11.2023): - ``` - pip install opentsne + git clone https://github.com/ContextLab/hypertools ``` -- [Conda](https://anaconda.org/conda-forge/opentsne) (πŸ“₯ 260K Β· ⏱️ 19.05.2024): +- [PyPi](https://pypi.org/project/hypertools) (πŸ“₯ 650 / month Β· πŸ“¦ 2 Β· ⏱️ 12.02.2022): ``` - conda install -c conda-forge opentsne + pip install hypertools ```
-
Plotly-Resampler (πŸ₯‰26 Β· ⭐ 970) - Visualize large time series data with plotly.py. MIT +
AutoViz (πŸ₯‰25 Β· ⭐ 1.7K) - Automatically Visualize any dataset, any size with a single line of.. Apache-2 -- [GitHub](https://github.com/predict-idlab/plotly-resampler) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 63 Β· πŸ“¦ 1.1K Β· πŸ“‹ 160 - 28% open Β· ⏱️ 27.03.2024): +- [GitHub](https://github.com/AutoViML/AutoViz) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 200 Β· πŸ“¦ 740 Β· πŸ“‹ 94 - 3% open Β· ⏱️ 10.06.2024): ``` - git clone https://github.com/predict-idlab/plotly-resampler + git clone https://github.com/AutoViML/AutoViz ``` -- [PyPi](https://pypi.org/project/plotly-resampler) (πŸ“₯ 400K / month Β· πŸ“¦ 22 Β· ⏱️ 27.03.2024): +- [PyPi](https://pypi.org/project/autoviz) (πŸ“₯ 57K / month Β· πŸ“¦ 11 Β· ⏱️ 10.06.2024): ``` - pip install plotly-resampler + pip install autoviz ``` -- [Conda](https://anaconda.org/conda-forge/plotly-resampler) (πŸ“₯ 43K Β· ⏱️ 29.03.2024): +- [Conda](https://anaconda.org/conda-forge/autoviz) (πŸ“₯ 62K Β· ⏱️ 26.04.2024): ``` - conda install -c conda-forge plotly-resampler + conda install -c conda-forge autoviz ```
-
Chartify (πŸ₯‰25 Β· ⭐ 3.5K Β· πŸ’€) - Python library that makes it easy for data scientists to create.. Apache-2 +
Chartify (πŸ₯‰24 Β· ⭐ 3.5K Β· πŸ’€) - Python library that makes it easy for data scientists to create.. Apache-2 -- [GitHub](https://github.com/spotify/chartify) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 310 Β· πŸ“¦ 76 Β· πŸ“‹ 80 - 60% open Β· ⏱️ 12.10.2023): +- [GitHub](https://github.com/spotify/chartify) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 320 Β· πŸ“¦ 78 Β· πŸ“‹ 83 - 61% open Β· ⏱️ 12.10.2023): ``` git clone https://github.com/spotify/chartify ``` -- [PyPi](https://pypi.org/project/chartify) (πŸ“₯ 26K / month Β· πŸ“¦ 9 Β· ⏱️ 12.10.2023): +- [PyPi](https://pypi.org/project/chartify) (πŸ“₯ 2.2K / month Β· πŸ“¦ 9 Β· ⏱️ 12.10.2023): ``` pip install chartify ``` -- [Conda](https://anaconda.org/conda-forge/chartify) (πŸ“₯ 31K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/chartify) (πŸ“₯ 32K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge chartify ```
-
HiPlot (πŸ₯‰24 Β· ⭐ 2.7K Β· πŸ’€) - HiPlot makes understanding high dimensional data easy. MIT +
Plotly-Resampler (πŸ₯‰24 Β· ⭐ 1K) - Visualize large time series data with plotly.py. MIT -- [GitHub](https://github.com/facebookresearch/hiplot) (πŸ‘¨β€πŸ’» 9 Β· πŸ”€ 140 Β· πŸ“¦ 410 Β· πŸ“‹ 93 - 21% open Β· ⏱️ 19.07.2023): +- [GitHub](https://github.com/predict-idlab/plotly-resampler) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 67 Β· πŸ“¦ 1.4K Β· πŸ“‹ 170 - 30% open Β· ⏱️ 24.08.2024): ``` - git clone https://github.com/facebookresearch/hiplot + git clone https://github.com/predict-idlab/plotly-resampler ``` -- [PyPi](https://pypi.org/project/hiplot) (πŸ“₯ 19K / month Β· πŸ“¦ 26 Β· ⏱️ 05.07.2022): +- [PyPi](https://pypi.org/project/plotly-resampler) (πŸ“₯ 330K / month Β· πŸ“¦ 24 Β· ⏱️ 27.03.2024): ``` - pip install hiplot + pip install plotly-resampler ``` -- [Conda](https://anaconda.org/conda-forge/hiplot) (πŸ“₯ 190K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/plotly-resampler) (πŸ“₯ 63K Β· ⏱️ 29.03.2024): ``` - conda install -c conda-forge hiplot + conda install -c conda-forge plotly-resampler ```
-
python-ternary (πŸ₯‰24 Β· ⭐ 710) - Ternary plotting library for python with matplotlib. MIT +
Multicore-TSNE (πŸ₯‰23 Β· ⭐ 1.9K Β· πŸ’€) - Parallel t-SNE implementation with Python and Torch.. BSD-3 -- [GitHub](https://github.com/marcharper/python-ternary) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 160 Β· πŸ“₯ 25 Β· πŸ“¦ 170 Β· πŸ“‹ 140 - 24% open Β· ⏱️ 07.03.2024): +- [GitHub](https://github.com/DmitryUlyanov/Multicore-TSNE) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 230 Β· πŸ“¦ 460 Β· πŸ“‹ 69 - 65% open Β· ⏱️ 06.02.2024): ``` - git clone https://github.com/marcharper/python-ternary + git clone https://github.com/DmitryUlyanov/Multicore-TSNE ``` -- [PyPi](https://pypi.org/project/python-ternary) (πŸ“₯ 35K / month Β· πŸ“¦ 30 Β· ⏱️ 17.02.2021): +- [PyPi](https://pypi.org/project/MulticoreTSNE) (πŸ“₯ 1.9K / month Β· πŸ“¦ 22 Β· ⏱️ 09.01.2019): ``` - pip install python-ternary + pip install MulticoreTSNE ``` -- [Conda](https://anaconda.org/conda-forge/python-ternary) (πŸ“₯ 82K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/multicore-tsne) (πŸ“₯ 48K Β· ⏱️ 11.10.2023): ``` - conda install -c conda-forge python-ternary + conda install -c conda-forge multicore-tsne ```
-
Multicore-TSNE (πŸ₯‰23 Β· ⭐ 1.9K) - Parallel t-SNE implementation with Python and Torch.. BSD-3 +
python-ternary (πŸ₯‰23 Β· ⭐ 720) - Ternary plotting library for python with matplotlib. MIT -- [GitHub](https://github.com/DmitryUlyanov/Multicore-TSNE) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 230 Β· πŸ“¦ 450 Β· πŸ“‹ 69 - 65% open Β· ⏱️ 06.02.2024): +- [GitHub](https://github.com/marcharper/python-ternary) (πŸ‘¨β€πŸ’» 28 Β· πŸ”€ 160 Β· πŸ“₯ 30 Β· πŸ“¦ 180 Β· πŸ“‹ 140 - 24% open Β· ⏱️ 12.06.2024): ``` - git clone https://github.com/DmitryUlyanov/Multicore-TSNE + git clone https://github.com/marcharper/python-ternary ``` -- [PyPi](https://pypi.org/project/MulticoreTSNE) (πŸ“₯ 2.6K / month Β· πŸ“¦ 22 Β· ⏱️ 09.01.2019): +- [PyPi](https://pypi.org/project/python-ternary) (πŸ“₯ 16K / month Β· πŸ“¦ 32 Β· ⏱️ 17.02.2021): ``` - pip install MulticoreTSNE + pip install python-ternary ``` -- [Conda](https://anaconda.org/conda-forge/multicore-tsne) (πŸ“₯ 37K Β· ⏱️ 11.10.2023): +- [Conda](https://anaconda.org/conda-forge/python-ternary) (πŸ“₯ 88K Β· ⏱️ 16.06.2023): ``` - conda install -c conda-forge multicore-tsne + conda install -c conda-forge python-ternary ```
-
vega (πŸ₯‰21 Β· ⭐ 370) - IPython/Jupyter notebook module for Vega and Vega-Lite. BSD-3 +
vega (πŸ₯‰22 Β· ⭐ 370) - IPython/Jupyter notebook module for Vega and Vega-Lite. BSD-3 -- [GitHub](https://github.com/vega/ipyvega) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 65 Β· πŸ“¦ 4 Β· πŸ“‹ 110 - 19% open Β· ⏱️ 01.05.2024): +- [GitHub](https://github.com/vega/ipyvega) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 65 Β· πŸ“¦ 4 Β· πŸ“‹ 110 - 18% open Β· ⏱️ 01.09.2024): ``` git clone https://github.com/vega/ipyvega ``` -- [PyPi](https://pypi.org/project/vega) (πŸ“₯ 21K / month Β· πŸ“¦ 14 Β· ⏱️ 12.04.2023): +- [PyPi](https://pypi.org/project/vega) (πŸ“₯ 11K / month Β· πŸ“¦ 15 Β· ⏱️ 12.04.2023): ``` pip install vega ``` -- [Conda](https://anaconda.org/conda-forge/vega) (πŸ“₯ 600K Β· ⏱️ 18.05.2024): +- [Conda](https://anaconda.org/conda-forge/vega) (πŸ“₯ 640K Β· ⏱️ 18.05.2024): ``` conda install -c conda-forge vega ```
-
PDPbox (πŸ₯‰20 Β· ⭐ 830 Β· πŸ’€) - python partial dependence plot toolbox. MIT +
PyWaffle (πŸ₯‰20 Β· ⭐ 580) - Make Waffle Charts in Python. MIT -- [GitHub](https://github.com/SauceCat/PDPbox) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 130 Β· πŸ“‹ 67 - 41% open Β· ⏱️ 05.06.2023): +- [GitHub](https://github.com/gyli/PyWaffle) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 100 Β· πŸ“¦ 400 Β· πŸ“‹ 22 - 27% open Β· ⏱️ 16.06.2024): ``` - git clone https://github.com/SauceCat/PDPbox + git clone https://github.com/gyli/PyWaffle ``` -- [PyPi](https://pypi.org/project/pdpbox) (πŸ“₯ 21K / month Β· πŸ“¦ 26 Β· ⏱️ 14.03.2021): +- [PyPi](https://pypi.org/project/pywaffle) (πŸ“₯ 5.6K / month Β· πŸ“¦ 6 Β· ⏱️ 16.06.2024): ``` - pip install pdpbox + pip install pywaffle ``` -- [Conda](https://anaconda.org/conda-forge/pdpbox) (πŸ“₯ 21K Β· ⏱️ 10.06.2023): +- [Conda](https://anaconda.org/conda-forge/pywaffle) (πŸ“₯ 13K Β· ⏱️ 16.06.2023): ``` - conda install -c conda-forge pdpbox + conda install -c conda-forge pywaffle ```
-
Popmon (πŸ₯‰20 Β· ⭐ 490 Β· πŸ’€) - Monitor the stability of a Pandas or Spark dataframe. MIT +
animatplot (πŸ₯‰20 Β· ⭐ 410) - A python package for animating plots build on matplotlib. MIT -- [GitHub](https://github.com/ing-bank/popmon) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 35 Β· πŸ“₯ 150 Β· πŸ“¦ 20 Β· πŸ“‹ 55 - 27% open Β· ⏱️ 18.07.2023): +- [GitHub](https://github.com/t-makaro/animatplot) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 38 Β· πŸ“¦ 59 Β· πŸ“‹ 37 - 45% open Β· ⏱️ 29.08.2024): ``` - git clone https://github.com/ing-bank/popmon + git clone https://github.com/t-makaro/animatplot + ``` +- [PyPi](https://pypi.org/project/animatplot) (πŸ“₯ 300 / month Β· πŸ“¦ 4 Β· ⏱️ 29.08.2024): + ``` + pip install animatplot ``` -- [PyPi](https://pypi.org/project/popmon) (πŸ“₯ 10K / month Β· πŸ“¦ 2 Β· ⏱️ 18.07.2023): +- [Conda](https://anaconda.org/conda-forge/animatplot) (πŸ“₯ 14K Β· ⏱️ 01.09.2024): ``` - pip install popmon + conda install -c conda-forge animatplot ```
-
ivis (πŸ₯‰18 Β· ⭐ 320 Β· πŸ’€) - Dimensionality reduction in very large datasets using Siamese.. Apache-2 +
ivis (πŸ₯‰20 Β· ⭐ 330) - Dimensionality reduction in very large datasets using Siamese.. Apache-2 -- [GitHub](https://github.com/beringresearch/ivis) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 43 Β· πŸ“¦ 32 Β· πŸ“‹ 60 - 6% open Β· ⏱️ 09.11.2023): +- [GitHub](https://github.com/beringresearch/ivis) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 43 Β· πŸ“¦ 35 Β· πŸ“‹ 60 - 5% open Β· ⏱️ 13.06.2024): ``` git clone https://github.com/beringresearch/ivis ``` -- [PyPi](https://pypi.org/project/ivis) (πŸ“₯ 1.1K / month Β· πŸ“¦ 2 Β· ⏱️ 10.03.2022): +- [PyPi](https://pypi.org/project/ivis) (πŸ“₯ 1.4K / month Β· πŸ“¦ 2 Β· ⏱️ 13.06.2024): ``` pip install ivis ```
+
vegafusion (πŸ₯‰20 Β· ⭐ 320) - Serverside scaling for Vega and Altair visualizations. BSD-3 + +- [GitHub](https://github.com/vega/vegafusion) (πŸ‘¨β€πŸ’» 4 Β· πŸ”€ 18 Β· πŸ“₯ 5.8K Β· πŸ“‹ 130 - 35% open Β· ⏱️ 14.08.2024): + + ``` + git clone https://github.com/vegafusion/vegafusion + ``` +- [PyPi](https://pypi.org/project/vegafusion-jupyter) (πŸ“₯ 930 / month Β· πŸ“¦ 2 Β· ⏱️ 09.05.2024): + ``` + pip install vegafusion-jupyter + ``` +- [Conda](https://anaconda.org/conda-forge/vegafusion-python-embed) (πŸ“₯ 220K Β· ⏱️ 10.05.2024): + ``` + conda install -c conda-forge vegafusion-python-embed + ``` +- [npm](https://www.npmjs.com/package/vegafusion-jupyter) (πŸ“₯ 140 / month Β· πŸ“¦ 3 Β· ⏱️ 09.05.2024): + ``` + npm install vegafusion-jupyter + ``` +
Show 15 hidden projects... -- missingno (πŸ₯‰29 Β· ⭐ 3.8K Β· πŸ’€) - Missing data visualization module for Python. MIT +- missingno (πŸ₯‰29 Β· ⭐ 3.9K Β· πŸ’€) - Missing data visualization module for Python. MIT - Cufflinks (πŸ₯‰29 Β· ⭐ 3K Β· πŸ’€) - Productivity Tools for Plotly + Pandas. MIT - Facets Overview (πŸ₯‰28 Β· ⭐ 7.3K Β· πŸ’€) - Visualizations for machine learning datasets. Apache-2 -- pythreejs (πŸ₯‰27 Β· ⭐ 930 Β· πŸ’€) - A Jupyter - Three.js bridge. BSD-3 -- Pandas-Bokeh (πŸ₯‰24 Β· ⭐ 880 Β· πŸ’€) - Bokeh Plotting Backend for Pandas and GeoPandas. MIT -- PandasGUI (πŸ₯‰23 Β· ⭐ 3.1K) - A GUI for Pandas DataFrames. ❗️MIT-0 +- pythreejs (πŸ₯‰28 Β· ⭐ 940 Β· πŸ’€) - A Jupyter - Three.js bridge. BSD-3 +- HiPlot (πŸ₯‰24 Β· ⭐ 2.7K Β· πŸ’€) - HiPlot makes understanding high dimensional data easy. MIT +- PandasGUI (πŸ₯‰23 Β· ⭐ 3.2K Β· πŸ’€) - A GUI for Pandas DataFrames. ❗️MIT-0 +- Pandas-Bokeh (πŸ₯‰23 Β· ⭐ 880 Β· πŸ’€) - Bokeh Plotting Backend for Pandas and GeoPandas. MIT - pivottablejs (πŸ₯‰22 Β· ⭐ 680 Β· πŸ’€) - Dragndrop Pivot Tables and Charts for Jupyter/IPython.. MIT -- joypy (πŸ₯‰21 Β· ⭐ 540 Β· πŸ’€) - Joyplots in Python with matplotlib & pandas. MIT -- vegafusion (πŸ₯‰21 Β· ⭐ 300) - Serverside scaling for Vega and Altair visualizations. BSD-3 -- PyWaffle (πŸ₯‰20 Β· ⭐ 570 Β· πŸ’€) - Make Waffle Charts in Python. MIT -- animatplot (πŸ₯‰18 Β· ⭐ 400 Β· πŸ’€) - A python package for animating plots build on matplotlib. MIT +- PDPbox (πŸ₯‰21 Β· ⭐ 840 Β· πŸ’€) - python partial dependence plot toolbox. MIT +- joypy (πŸ₯‰21 Β· ⭐ 550 Β· πŸ’€) - Joyplots in Python with matplotlib & pandas. MIT +- Popmon (πŸ₯‰20 Β· ⭐ 490 Β· πŸ’€) - Monitor the stability of a Pandas or Spark dataframe. MIT - pdvega (πŸ₯‰16 Β· ⭐ 340 Β· πŸ’€) - Interactive plotting for Pandas using Vega-Lite. MIT -- data-describe (πŸ₯‰15 Β· ⭐ 290 Β· πŸ’€) - datadescribe: Pythonic EDA Accelerator for Data Science. Apache-2 +- data-describe (πŸ₯‰15 Β· ⭐ 300 Β· πŸ’€) - datadescribe: Pythonic EDA Accelerator for Data Science. Apache-2 - nx-altair (πŸ₯‰15 Β· ⭐ 220 Β· πŸ’€) - Draw interactive NetworkX graphs with Altair. MIT - nptsne (πŸ₯‰12 Β· ⭐ 32 Β· πŸ’€) - nptsne is a numpy compatible python binary package that offers a.. Apache-2
@@ -1445,752 +1450,741 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we
transformers (πŸ₯‡52 Β· ⭐ 130K) - Transformers: State-of-the-art Machine Learning for.. Apache-2 -- [GitHub](https://github.com/huggingface/transformers) (πŸ‘¨β€πŸ’» 2.6K Β· πŸ”€ 25K Β· πŸ“¦ 180K Β· πŸ“‹ 15K - 7% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/huggingface/transformers) (πŸ‘¨β€πŸ’» 2.8K Β· πŸ”€ 26K Β· πŸ“¦ 210K Β· πŸ“‹ 16K - 8% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/huggingface/transformers ``` -- [PyPi](https://pypi.org/project/transformers) (πŸ“₯ 29M / month Β· πŸ“¦ 5.2K Β· ⏱️ 30.05.2024): +- [PyPi](https://pypi.org/project/transformers) (πŸ“₯ 36M / month Β· πŸ“¦ 6.1K Β· ⏱️ 22.08.2024): ``` pip install transformers ``` -- [Conda](https://anaconda.org/conda-forge/transformers) (πŸ“₯ 1.7M Β· ⏱️ 31.05.2024): +- [Conda](https://anaconda.org/conda-forge/transformers) (πŸ“₯ 2M Β· ⏱️ 23.08.2024): ``` conda install -c conda-forge transformers ```
-
spaCy (πŸ₯‡44 Β· ⭐ 29K) - Industrial-strength Natural Language Processing (NLP) in Python. MIT +
nltk (πŸ₯‡45 Β· ⭐ 13K Β· πŸ“ˆ) - Suite of libraries and programs for symbolic and statistical natural.. Apache-2 + +- [GitHub](https://github.com/nltk/nltk) (πŸ‘¨β€πŸ’» 460 Β· πŸ”€ 2.9K Β· πŸ“¦ 300K Β· πŸ“‹ 1.8K - 15% open Β· ⏱️ 04.09.2024): + + ``` + git clone https://github.com/nltk/nltk + ``` +- [PyPi](https://pypi.org/project/nltk) (πŸ“₯ 21M / month Β· πŸ“¦ 4.6K Β· ⏱️ 18.08.2024): + ``` + pip install nltk + ``` +- [Conda](https://anaconda.org/conda-forge/nltk) (πŸ“₯ 2.7M Β· ⏱️ 18.08.2024): + ``` + conda install -c conda-forge nltk + ``` +
+
spaCy (πŸ₯‡43 Β· ⭐ 30K) - Industrial-strength Natural Language Processing (NLP) in Python. MIT -- [GitHub](https://github.com/explosion/spaCy) (πŸ‘¨β€πŸ’» 750 Β· πŸ”€ 4.3K Β· πŸ“¦ 90K Β· πŸ“‹ 5.6K - 2% open Β· ⏱️ 31.05.2024): +- [GitHub](https://github.com/explosion/spaCy) (πŸ‘¨β€πŸ’» 750 Β· πŸ”€ 4.3K Β· πŸ“₯ 120 Β· πŸ“¦ 98K Β· πŸ“‹ 5.6K - 2% open Β· ⏱️ 20.08.2024): ``` git clone https://github.com/explosion/spaCy ``` -- [PyPi](https://pypi.org/project/spacy) (πŸ“₯ 13M / month Β· πŸ“¦ 2.4K Β· ⏱️ 05.06.2024): +- [PyPi](https://pypi.org/project/spacy) (πŸ“₯ 12M / month Β· πŸ“¦ 2.6K Β· ⏱️ 20.08.2024): ``` pip install spacy ``` -- [Conda](https://anaconda.org/conda-forge/spacy) (πŸ“₯ 3.5M Β· ⏱️ 05.06.2024): +- [Conda](https://anaconda.org/conda-forge/spacy) (πŸ“₯ 4M Β· ⏱️ 29.07.2024): ``` conda install -c conda-forge spacy ```
-
litellm (πŸ₯‡42 Β· ⭐ 9.5K) - Call all LLM APIs using the OpenAI format. Use.. MIT o t h e r s +
litellm (πŸ₯‡43 Β· ⭐ 12K) - Python SDK, Proxy Server to call 100+ LLM APIs using.. MIT o t h e r s -- [GitHub](https://github.com/BerriAI/litellm) (πŸ‘¨β€πŸ’» 250 Β· πŸ”€ 1K Β· πŸ“₯ 250 Β· πŸ“¦ 2K Β· πŸ“‹ 2.5K - 23% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/BerriAI/litellm) (πŸ‘¨β€πŸ’» 320 Β· πŸ”€ 1.4K Β· πŸ“₯ 240 Β· πŸ“¦ 3.2K Β· πŸ“‹ 3.1K - 17% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/BerriAI/litellm ``` -- [PyPi](https://pypi.org/project/litellm) (πŸ“₯ 610K / month Β· πŸ“¦ 220 Β· ⏱️ 06.06.2024): +- [PyPi](https://pypi.org/project/litellm) (πŸ“₯ 1.6M / month Β· πŸ“¦ 380 Β· ⏱️ 05.09.2024): ``` pip install litellm ```
-
sentence-transformers (πŸ₯‡41 Β· ⭐ 14K) - Multilingual Sentence & Image Embeddings with BERT. Apache-2 +
gensim (πŸ₯‡41 Β· ⭐ 16K) - Topic Modelling for Humans. ❗️LGPL-2.1 -- [GitHub](https://github.com/UKPLab/sentence-transformers) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 2.4K Β· πŸ“¦ 35K Β· πŸ“‹ 2K - 53% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/piskvorky/gensim) (πŸ‘¨β€πŸ’» 460 Β· πŸ”€ 4.4K Β· πŸ“₯ 4.7K Β· πŸ“¦ 64K Β· πŸ“‹ 1.8K - 20% open Β· ⏱️ 10.08.2024): ``` - git clone https://github.com/UKPLab/sentence-transformers + git clone https://github.com/RaRe-Technologies/gensim ``` -- [PyPi](https://pypi.org/project/sentence-transformers) (πŸ“₯ 4.3M / month Β· πŸ“¦ 1.3K Β· ⏱️ 28.05.2024): +- [PyPi](https://pypi.org/project/gensim) (πŸ“₯ 4.2M / month Β· πŸ“¦ 1.4K Β· ⏱️ 19.07.2024): ``` - pip install sentence-transformers + pip install gensim ``` -- [Conda](https://anaconda.org/conda-forge/sentence-transformers) (πŸ“₯ 260K Β· ⏱️ 28.05.2024): +- [Conda](https://anaconda.org/conda-forge/gensim) (πŸ“₯ 1.4M Β· ⏱️ 03.09.2024): ``` - conda install -c conda-forge sentence-transformers + conda install -c conda-forge gensim ```
-
nltk (πŸ₯‡41 Β· ⭐ 13K) - Suite of libraries and programs for symbolic and statistical natural.. Apache-2 +
sentence-transformers (πŸ₯‡41 Β· ⭐ 15K) - State-of-the-Art Text Embeddings. Apache-2 -- [GitHub](https://github.com/nltk/nltk) (πŸ‘¨β€πŸ’» 450 Β· πŸ”€ 2.8K Β· πŸ“¦ 280K Β· πŸ“‹ 1.8K - 15% open Β· ⏱️ 05.04.2024): +- [GitHub](https://github.com/UKPLab/sentence-transformers) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 2.4K Β· πŸ“¦ 46K Β· πŸ“‹ 2.2K - 54% open Β· ⏱️ 30.08.2024): ``` - git clone https://github.com/nltk/nltk + git clone https://github.com/UKPLab/sentence-transformers ``` -- [PyPi](https://pypi.org/project/nltk) (πŸ“₯ 20M / month Β· πŸ“¦ 4.3K Β· ⏱️ 20.07.2023): +- [PyPi](https://pypi.org/project/sentence-transformers) (πŸ“₯ 4.9M / month Β· πŸ“¦ 1.6K Β· ⏱️ 07.06.2024): ``` - pip install nltk + pip install sentence-transformers ``` -- [Conda](https://anaconda.org/conda-forge/nltk) (πŸ“₯ 2.6M Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/sentence-transformers) (πŸ“₯ 370K Β· ⏱️ 07.06.2024): ``` - conda install -c conda-forge nltk + conda install -c conda-forge sentence-transformers ```
-
Tokenizers (πŸ₯‡40 Β· ⭐ 8.6K) - Fast State-of-the-Art Tokenizers optimized for Research and.. Apache-2 +
Tokenizers (πŸ₯‡40 Β· ⭐ 8.9K) - Fast State-of-the-Art Tokenizers optimized for Research and.. Apache-2 -- [GitHub](https://github.com/huggingface/tokenizers) (πŸ‘¨β€πŸ’» 88 Β· πŸ”€ 740 Β· πŸ“₯ 47 Β· πŸ“¦ 81K Β· πŸ“‹ 960 - 6% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/huggingface/tokenizers) (πŸ‘¨β€πŸ’» 93 Β· πŸ”€ 760 Β· πŸ“₯ 57 Β· πŸ“¦ 99K Β· πŸ“‹ 980 - 3% open Β· ⏱️ 12.08.2024): ``` git clone https://github.com/huggingface/tokenizers ``` -- [PyPi](https://pypi.org/project/tokenizers) (πŸ“₯ 26M / month Β· πŸ“¦ 750 Β· ⏱️ 17.04.2024): +- [PyPi](https://pypi.org/project/tokenizers) (πŸ“₯ 29M / month Β· πŸ“¦ 910 Β· ⏱️ 08.08.2024): ``` pip install tokenizers ``` -- [Conda](https://anaconda.org/conda-forge/tokenizers) (πŸ“₯ 1.7M Β· ⏱️ 18.04.2024): +- [Conda](https://anaconda.org/conda-forge/tokenizers) (πŸ“₯ 2M Β· ⏱️ 12.08.2024): ``` conda install -c conda-forge tokenizers ```
-
gensim (πŸ₯‡39 Β· ⭐ 15K) - Topic Modelling for Humans. ❗️LGPL-2.1 - -- [GitHub](https://github.com/piskvorky/gensim) (πŸ‘¨β€πŸ’» 450 Β· πŸ”€ 4.3K Β· πŸ“₯ 4.6K Β· πŸ“¦ 60K Β· πŸ“‹ 1.8K - 20% open Β· ⏱️ 02.06.2024): - - ``` - git clone https://github.com/RaRe-Technologies/gensim - ``` -- [PyPi](https://pypi.org/project/gensim) (πŸ“₯ 4.7M / month Β· πŸ“¦ 1.3K Β· ⏱️ 24.08.2023): - ``` - pip install gensim - ``` -- [Conda](https://anaconda.org/conda-forge/gensim) (πŸ“₯ 1.3M Β· ⏱️ 08.02.2024): - ``` - conda install -c conda-forge gensim - ``` -
-
Rasa (πŸ₯‡38 Β· ⭐ 18K) - Open source machine learning framework to automate text- and voice-.. Apache-2 +
Rasa (πŸ₯‡39 Β· ⭐ 19K) - Open source machine learning framework to automate text- and voice-.. Apache-2 -- [GitHub](https://github.com/RasaHQ/rasa) (πŸ‘¨β€πŸ’» 590 Β· πŸ”€ 4.5K Β· πŸ“¦ 4.2K Β· πŸ“‹ 6.8K - 1% open Β· ⏱️ 21.03.2024): +- [GitHub](https://github.com/RasaHQ/rasa) (πŸ‘¨β€πŸ’» 600 Β· πŸ”€ 4.6K Β· πŸ“¦ 4.4K Β· πŸ“‹ 6.8K - 1% open Β· ⏱️ 21.03.2024): ``` git clone https://github.com/RasaHQ/rasa ``` -- [PyPi](https://pypi.org/project/rasa) (πŸ“₯ 120K / month Β· πŸ“¦ 59 Β· ⏱️ 18.04.2024): +- [PyPi](https://pypi.org/project/rasa) (πŸ“₯ 140K / month Β· πŸ“¦ 60 Β· ⏱️ 18.04.2024): ``` pip install rasa ```
-
sentencepiece (πŸ₯‡38 Β· ⭐ 9.7K) - Unsupervised text tokenizer for Neural Network-based text.. Apache-2 +
flair (πŸ₯‡39 Β· ⭐ 14K) - A very simple framework for state-of-the-art Natural Language Processing.. MIT -- [GitHub](https://github.com/google/sentencepiece) (πŸ‘¨β€πŸ’» 88 Β· πŸ”€ 1.1K Β· πŸ“₯ 38K Β· πŸ“¦ 67K Β· πŸ“‹ 720 - 3% open Β· ⏱️ 04.06.2024): +- [GitHub](https://github.com/flairNLP/flair) (πŸ‘¨β€πŸ’» 270 Β· πŸ”€ 2.1K Β· πŸ“¦ 3.5K Β· πŸ“‹ 2.3K - 4% open Β· ⏱️ 30.08.2024): ``` - git clone https://github.com/google/sentencepiece + git clone https://github.com/flairNLP/flair ``` -- [PyPi](https://pypi.org/project/sentencepiece) (πŸ“₯ 21M / month Β· πŸ“¦ 1.5K Β· ⏱️ 19.02.2024): +- [PyPi](https://pypi.org/project/flair) (πŸ“₯ 86K / month Β· πŸ“¦ 140 Β· ⏱️ 25.07.2024): ``` - pip install sentencepiece + pip install flair ``` -- [Conda](https://anaconda.org/conda-forge/sentencepiece) (πŸ“₯ 820K Β· ⏱️ 27.05.2024): +- [Conda](https://anaconda.org/conda-forge/python-flair) (πŸ“₯ 30K Β· ⏱️ 05.01.2024): ``` - conda install -c conda-forge sentencepiece + conda install -c conda-forge python-flair ```
-
flair (πŸ₯‡37 Β· ⭐ 14K Β· πŸ“‰) - A very simple framework for state-of-the-art Natural Language.. MIT +
sentencepiece (πŸ₯‡38 Β· ⭐ 10K) - Unsupervised text tokenizer for Neural Network-based text.. Apache-2 -- [GitHub](https://github.com/flairNLP/flair) (πŸ‘¨β€πŸ’» 260 Β· πŸ”€ 2.1K Β· πŸ“¦ 3.3K Β· πŸ“‹ 2.3K - 3% open Β· ⏱️ 24.05.2024): +- [GitHub](https://github.com/google/sentencepiece) (πŸ‘¨β€πŸ’» 89 Β· πŸ”€ 1.2K Β· πŸ“₯ 41K Β· πŸ“¦ 76K Β· πŸ“‹ 740 - 4% open Β· ⏱️ 18.08.2024): ``` - git clone https://github.com/flairNLP/flair + git clone https://github.com/google/sentencepiece ``` -- [PyPi](https://pypi.org/project/flair) (πŸ“₯ 290K / month Β· πŸ“¦ 130 Β· ⏱️ 18.12.2023): +- [PyPi](https://pypi.org/project/sentencepiece) (πŸ“₯ 22M / month Β· πŸ“¦ 1.7K Β· ⏱️ 19.02.2024): ``` - pip install flair + pip install sentencepiece ``` -- [Conda](https://anaconda.org/conda-forge/python-flair) (πŸ“₯ 25K Β· ⏱️ 05.01.2024): +- [Conda](https://anaconda.org/conda-forge/sentencepiece) (πŸ“₯ 1M Β· ⏱️ 23.08.2024): ``` - conda install -c conda-forge python-flair + conda install -c conda-forge sentencepiece ```
-
TextBlob (πŸ₯‡37 Β· ⭐ 9K) - Simple, Pythonic, text processing--Sentiment analysis, part-of-speech.. MIT +
TextBlob (πŸ₯‡37 Β· ⭐ 9.1K) - Simple, Pythonic, text processing--Sentiment analysis, part-of-speech.. MIT -- [GitHub](https://github.com/sloria/TextBlob) (πŸ‘¨β€πŸ’» 37 Β· πŸ”€ 1.1K Β· πŸ“₯ 120 Β· πŸ“¦ 39K Β· πŸ“‹ 280 - 39% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/sloria/TextBlob) (πŸ‘¨β€πŸ’» 37 Β· πŸ”€ 1.1K Β· πŸ“₯ 120 Β· πŸ“¦ 42K Β· πŸ“‹ 280 - 38% open Β· ⏱️ 07.08.2024): ``` git clone https://github.com/sloria/TextBlob ``` -- [PyPi](https://pypi.org/project/textblob) (πŸ“₯ 1.1M / month Β· πŸ“¦ 340 Β· ⏱️ 22.10.2021): +- [PyPi](https://pypi.org/project/textblob) (πŸ“₯ 2.1M / month Β· πŸ“¦ 370 Β· ⏱️ 15.02.2024): ``` pip install textblob ``` -- [Conda](https://anaconda.org/conda-forge/textblob) (πŸ“₯ 250K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/textblob) (πŸ“₯ 260K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge textblob ```
-
haystack (πŸ₯ˆ36 Β· ⭐ 14K) - LLM orchestration framework to build customizable, production-ready.. Apache-2 +
NeMo (πŸ₯ˆ36 Β· ⭐ 11K) - A scalable generative AI framework built for researchers and.. Apache-2 -- [GitHub](https://github.com/deepset-ai/haystack) (πŸ‘¨β€πŸ’» 240 Β· πŸ”€ 1.7K Β· πŸ“₯ 24 Β· πŸ“¦ 290 Β· πŸ“‹ 3.3K - 3% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/NVIDIA/NeMo) (πŸ‘¨β€πŸ’» 340 Β· πŸ”€ 2.4K Β· πŸ“₯ 230K Β· πŸ“¦ 21 Β· πŸ“‹ 2.3K - 5% open Β· ⏱️ 05.09.2024): ``` - git clone https://github.com/deepset-ai/haystack + git clone https://github.com/NVIDIA/NeMo ``` -- [PyPi](https://pypi.org/project/haystack) (πŸ“₯ 4.6K / month Β· πŸ“¦ 5 Β· ⏱️ 15.12.2021): +- [PyPi](https://pypi.org/project/nemo-toolkit) (πŸ“₯ 80K / month Β· πŸ“¦ 13 Β· ⏱️ 15.08.2024): ``` - pip install haystack + pip install nemo-toolkit ```
fairseq (πŸ₯ˆ35 Β· ⭐ 30K) - Facebook AI Research Sequence-to-Sequence Toolkit written in Python. MIT -- [GitHub](https://github.com/facebookresearch/fairseq) (πŸ‘¨β€πŸ’» 420 Β· πŸ”€ 6.3K Β· πŸ“₯ 330 Β· πŸ“¦ 3.2K Β· πŸ“‹ 4.3K - 29% open Β· ⏱️ 30.05.2024): +- [GitHub](https://github.com/facebookresearch/fairseq) (πŸ‘¨β€πŸ’» 430 Β· πŸ”€ 6.4K Β· πŸ“₯ 350 Β· πŸ“¦ 3.5K Β· πŸ“‹ 4.3K - 29% open Β· ⏱️ 22.07.2024): ``` git clone https://github.com/facebookresearch/fairseq ``` -- [PyPi](https://pypi.org/project/fairseq) (πŸ“₯ 270K / month Β· πŸ“¦ 110 Β· ⏱️ 27.06.2022): +- [PyPi](https://pypi.org/project/fairseq) (πŸ“₯ 180K / month Β· πŸ“¦ 120 Β· ⏱️ 27.06.2022): ``` pip install fairseq ``` -- [Conda](https://anaconda.org/conda-forge/fairseq) (πŸ“₯ 69K Β· ⏱️ 17.05.2024): +- [Conda](https://anaconda.org/conda-forge/fairseq) (πŸ“₯ 89K Β· ⏱️ 17.05.2024): ``` conda install -c conda-forge fairseq ```
-
NeMo (πŸ₯ˆ35 Β· ⭐ 10K) - A scalable generative AI framework built for researchers and.. Apache-2 +
fastText (πŸ₯ˆ35 Β· ⭐ 26K) - Library for fast text representation and classification. MIT -- [GitHub](https://github.com/NVIDIA/NeMo) (πŸ‘¨β€πŸ’» 320 Β· πŸ”€ 2.2K Β· πŸ“₯ 180K Β· πŸ“¦ 21 Β· πŸ“‹ 2.2K - 6% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/facebookresearch/fastText) (πŸ‘¨β€πŸ’» 68 Β· πŸ”€ 4.7K Β· πŸ“¦ 6.5K Β· πŸ“‹ 1.2K - 47% open Β· ⏱️ 13.03.2024): ``` - git clone https://github.com/NVIDIA/NeMo + git clone https://github.com/facebookresearch/fastText ``` -- [PyPi](https://pypi.org/project/nemo-toolkit) (πŸ“₯ 49K / month Β· πŸ“¦ 13 Β· ⏱️ 06.06.2024): +- [PyPi](https://pypi.org/project/fasttext) (πŸ“₯ 1.7M / month Β· πŸ“¦ 240 Β· ⏱️ 12.06.2024): ``` - pip install nemo-toolkit + pip install fasttext + ``` +- [Conda](https://anaconda.org/conda-forge/fasttext) (πŸ“₯ 98K Β· ⏱️ 19.05.2024): + ``` + conda install -c conda-forge fasttext ```
-
OpenNMT (πŸ₯ˆ35 Β· ⭐ 6.6K) - Open Source Neural Machine Translation and (Large) Language Models.. MIT +
haystack (πŸ₯ˆ35 Β· ⭐ 17K) - LLM orchestration framework to build customizable, production-ready.. Apache-2 -- [GitHub](https://github.com/OpenNMT/OpenNMT-py) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 2.2K Β· πŸ“¦ 280 Β· πŸ“‹ 1.4K - 1% open Β· ⏱️ 15.05.2024): +- [GitHub](https://github.com/deepset-ai/haystack) (πŸ‘¨β€πŸ’» 260 Β· πŸ”€ 1.8K Β· πŸ“¦ 470 Β· πŸ“‹ 3.5K - 3% open Β· ⏱️ 04.09.2024): ``` - git clone https://github.com/OpenNMT/OpenNMT-py + git clone https://github.com/deepset-ai/haystack ``` -- [PyPi](https://pypi.org/project/OpenNMT-py) (πŸ“₯ 11K / month Β· πŸ“¦ 18 Β· ⏱️ 18.03.2024): +- [PyPi](https://pypi.org/project/haystack) (πŸ“₯ 5.6K / month Β· πŸ“¦ 5 Β· ⏱️ 15.12.2021): ``` - pip install OpenNMT-py + pip install haystack ```
-
spark-nlp (πŸ₯ˆ35 Β· ⭐ 3.7K) - State of the Art Natural Language Processing. Apache-2 +
spark-nlp (πŸ₯ˆ35 Β· ⭐ 3.8K) - State of the Art Natural Language Processing. Apache-2 -- [GitHub](https://github.com/JohnSnowLabs/spark-nlp) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 700 Β· πŸ“¦ 440 Β· πŸ“‹ 880 - 5% open Β· ⏱️ 27.05.2024): +- [GitHub](https://github.com/JohnSnowLabs/spark-nlp) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 710 Β· πŸ“¦ 500 Β· πŸ“‹ 890 - 4% open Β· ⏱️ 01.09.2024): ``` git clone https://github.com/JohnSnowLabs/spark-nlp ``` -- [PyPi](https://pypi.org/project/spark-nlp) (πŸ“₯ 4.2M / month Β· πŸ“¦ 37 Β· ⏱️ 05.06.2024): +- [PyPi](https://pypi.org/project/spark-nlp) (πŸ“₯ 4M / month Β· πŸ“¦ 37 Β· ⏱️ 28.08.2024): ``` pip install spark-nlp ```
-
fastText (πŸ₯ˆ34 Β· ⭐ 26K) - Library for fast text representation and classification. MIT +
TensorFlow Text (πŸ₯ˆ35 Β· ⭐ 1.2K) - Making text a first-class citizen in TensorFlow. Apache-2 -- [GitHub](https://github.com/facebookresearch/fastText) (πŸ‘¨β€πŸ’» 68 Β· πŸ”€ 4.7K Β· πŸ“¦ 6K Β· πŸ“‹ 1.2K - 47% open Β· ⏱️ 13.03.2024): +- [GitHub](https://github.com/tensorflow/text) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 340 Β· πŸ“¦ 7.3K Β· πŸ“‹ 350 - 52% open Β· ⏱️ 05.09.2024): ``` - git clone https://github.com/facebookresearch/fastText + git clone https://github.com/tensorflow/text ``` -- [PyPi](https://pypi.org/project/fasttext) (πŸ“₯ 1.3M / month Β· πŸ“¦ 230 Β· ⏱️ 28.04.2020): +- [PyPi](https://pypi.org/project/tensorflow-text) (πŸ“₯ 6.4M / month Β· πŸ“¦ 210 Β· ⏱️ 15.07.2024): ``` - pip install fasttext + pip install tensorflow-text ``` -- [Conda](https://anaconda.org/conda-forge/fasttext) (πŸ“₯ 83K Β· ⏱️ 19.05.2024): +
+
rubrix (πŸ₯ˆ34 Β· ⭐ 3.8K) - Argilla is a collaboration tool for AI engineers and domain experts.. Apache-2 + +- [GitHub](https://github.com/argilla-io/argilla) (πŸ‘¨β€πŸ’» 95 Β· πŸ”€ 350 Β· πŸ“¦ 2.7K Β· πŸ“‹ 2.1K - 6% open Β· ⏱️ 05.09.2024): + ``` - conda install -c conda-forge fasttext + git clone https://github.com/recognai/rubrix + ``` +- [PyPi](https://pypi.org/project/rubrix) (πŸ“₯ 690 / month Β· ⏱️ 24.10.2022): + ``` + pip install rubrix + ``` +- [Conda](https://anaconda.org/conda-forge/rubrix) (πŸ“₯ 35K Β· ⏱️ 16.06.2023): + ``` + conda install -c conda-forge rubrix ```
-
stanza (πŸ₯ˆ34 Β· ⭐ 7.1K) - Stanford NLP Python library for tokenization, sentence segmentation,.. Apache-2 +
qdrant (πŸ₯ˆ33 Β· ⭐ 20K) - Qdrant - High-performance, massive-scale Vector Database for the next.. Apache-2 -- [GitHub](https://github.com/stanfordnlp/stanza) (πŸ‘¨β€πŸ’» 68 Β· πŸ”€ 870 Β· πŸ“¦ 2.8K Β· πŸ“‹ 880 - 10% open Β· ⏱️ 20.04.2024): +- [GitHub](https://github.com/qdrant/qdrant) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 1.3K Β· πŸ“₯ 140K Β· πŸ“¦ 110 Β· πŸ“‹ 1.3K - 22% open Β· ⏱️ 29.08.2024): ``` - git clone https://github.com/stanfordnlp/stanza + git clone https://github.com/qdrant/qdrant + ``` +
+
ftfy (πŸ₯ˆ33 Β· ⭐ 3.8K) - Fixes mojibake and other glitches in Unicode text, after the fact. Apache-2 + +- [GitHub](https://github.com/rspeer/python-ftfy) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 120 Β· πŸ“₯ 6 Β· πŸ“¦ 22K Β· πŸ“‹ 140 - 9% open Β· ⏱️ 06.08.2024): + ``` -- [PyPi](https://pypi.org/project/stanza) (πŸ“₯ 310K / month Β· πŸ“¦ 170 Β· ⏱️ 20.04.2024): + git clone https://github.com/rspeer/python-ftfy ``` - pip install stanza +- [PyPi](https://pypi.org/project/ftfy) (πŸ“₯ 5.4M / month Β· πŸ“¦ 550 Β· ⏱️ 06.08.2024): ``` -- [Conda](https://anaconda.org/stanfordnlp/stanza) (πŸ“₯ 7.4K Β· ⏱️ 16.06.2023): + pip install ftfy ``` - conda install -c stanfordnlp stanza +- [Conda](https://anaconda.org/conda-forge/ftfy) (πŸ“₯ 300K Β· ⏱️ 06.08.2024): + ``` + conda install -c conda-forge ftfy ```
-
torchtext (πŸ₯ˆ34 Β· ⭐ 3.5K) - Models, data loaders and abstractions for language processing,.. BSD-3 +
torchtext (πŸ₯ˆ33 Β· ⭐ 3.5K) - Models, data loaders and abstractions for language processing,.. BSD-3 -- [GitHub](https://github.com/pytorch/text) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 810 Β· πŸ“‹ 840 - 38% open Β· ⏱️ 24.04.2024): +- [GitHub](https://github.com/pytorch/text) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 810 Β· πŸ“‹ 850 - 38% open Β· ⏱️ 14.08.2024): ``` git clone https://github.com/pytorch/text ``` -- [PyPi](https://pypi.org/project/torchtext) (πŸ“₯ 680K / month Β· πŸ“¦ 260 Β· ⏱️ 24.04.2024): +- [PyPi](https://pypi.org/project/torchtext) (πŸ“₯ 1M / month Β· πŸ“¦ 280 Β· ⏱️ 24.04.2024): ``` pip install torchtext ```
-
jellyfish (πŸ₯ˆ34 Β· ⭐ 2K) - a python library for doing approximate and phonetic matching of strings. MIT +
jellyfish (πŸ₯ˆ33 Β· ⭐ 2K) - a python library for doing approximate and phonetic matching of strings. MIT -- [GitHub](https://github.com/jamesturk/jellyfish) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 160 Β· πŸ“¦ 9.1K Β· πŸ“‹ 130 - 3% open Β· ⏱️ 28.05.2024): +- [GitHub](https://github.com/jamesturk/jellyfish) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 160 Β· πŸ“¦ 10K Β· πŸ“‹ 140 - 5% open Β· ⏱️ 28.07.2024): ``` git clone https://github.com/jamesturk/jellyfish ``` -- [PyPi](https://pypi.org/project/jellyfish) (πŸ“₯ 4.2M / month Β· πŸ“¦ 240 Β· ⏱️ 28.05.2024): +- [PyPi](https://pypi.org/project/jellyfish) (πŸ“₯ 5.4M / month Β· πŸ“¦ 260 Β· ⏱️ 28.07.2024): ``` pip install jellyfish ``` -- [Conda](https://anaconda.org/conda-forge/jellyfish) (πŸ“₯ 880K Β· ⏱️ 29.05.2024): +- [Conda](https://anaconda.org/conda-forge/jellyfish) (πŸ“₯ 990K Β· ⏱️ 30.07.2024): ``` conda install -c conda-forge jellyfish ```
-
TensorFlow Text (πŸ₯ˆ34 Β· ⭐ 1.2K) - Making text a first-class citizen in TensorFlow. Apache-2 +
ParlAI (πŸ₯ˆ32 Β· ⭐ 10K Β· πŸ’€) - A framework for training and evaluating AI models on a variety of.. MIT -- [GitHub](https://github.com/tensorflow/text) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 330 Β· πŸ“¦ 6.9K Β· πŸ“‹ 340 - 49% open Β· ⏱️ 04.06.2024): +- [GitHub](https://github.com/facebookresearch/ParlAI) (πŸ‘¨β€πŸ’» 220 Β· πŸ”€ 2.1K Β· πŸ“¦ 250 Β· πŸ“‹ 1.5K - 3% open Β· ⏱️ 03.11.2023): ``` - git clone https://github.com/tensorflow/text + git clone https://github.com/facebookresearch/ParlAI ``` -- [PyPi](https://pypi.org/project/tensorflow-text) (πŸ“₯ 7M / month Β· πŸ“¦ 200 Β· ⏱️ 11.03.2024): +- [PyPi](https://pypi.org/project/parlai) (πŸ“₯ 3.7K / month Β· πŸ“¦ 5 Β· ⏱️ 20.09.2022): ``` - pip install tensorflow-text - ``` -
-
qdrant (πŸ₯ˆ33 Β· ⭐ 18K) - Qdrant - High-performance, massive-scale Vector Database for the next.. Apache-2 - -- [GitHub](https://github.com/qdrant/qdrant) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 1.2K Β· πŸ“₯ 43K Β· πŸ“¦ 110 Β· πŸ“‹ 1.1K - 20% open Β· ⏱️ 28.05.2024): - - ``` - git clone https://github.com/qdrant/qdrant + pip install parlai ```
-
rubrix (πŸ₯ˆ33 Β· ⭐ 3.2K) - Argilla is a collaboration platform for AI engineers and domain.. Apache-2 +
stanza (πŸ₯ˆ32 Β· ⭐ 7.2K) - Stanford NLP Python library for tokenization, sentence segmentation,.. Apache-2 -- [GitHub](https://github.com/argilla-io/argilla) (πŸ‘¨β€πŸ’» 89 Β· πŸ”€ 310 Β· πŸ“¦ 2.5K Β· πŸ“‹ 2K - 8% open Β· ⏱️ 03.06.2024): +- [GitHub](https://github.com/stanfordnlp/stanza) (πŸ‘¨β€πŸ’» 68 Β· πŸ”€ 880 Β· πŸ“¦ 3K Β· πŸ“‹ 890 - 10% open Β· ⏱️ 20.04.2024): ``` - git clone https://github.com/recognai/rubrix + git clone https://github.com/stanfordnlp/stanza ``` -- [PyPi](https://pypi.org/project/rubrix) (πŸ“₯ 500 / month Β· ⏱️ 24.10.2022): +- [PyPi](https://pypi.org/project/stanza) (πŸ“₯ 430K / month Β· πŸ“¦ 170 Β· ⏱️ 20.04.2024): ``` - pip install rubrix + pip install stanza ``` -- [Conda](https://anaconda.org/conda-forge/rubrix) (πŸ“₯ 31K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/stanfordnlp/stanza) (πŸ“₯ 7.9K Β· ⏱️ 16.06.2023): ``` - conda install -c conda-forge rubrix + conda install -c stanfordnlp stanza ```
-
ParlAI (πŸ₯ˆ32 Β· ⭐ 10K Β· πŸ’€) - A framework for training and evaluating AI models on a variety of.. MIT +
OpenNMT (πŸ₯ˆ32 Β· ⭐ 6.7K Β· πŸ“‰) - Open Source Neural Machine Translation and (Large) Language.. MIT -- [GitHub](https://github.com/facebookresearch/ParlAI) (πŸ‘¨β€πŸ’» 220 Β· πŸ”€ 2.1K Β· πŸ“¦ 240 Β· πŸ“‹ 1.5K - 3% open Β· ⏱️ 03.11.2023): +- [GitHub](https://github.com/OpenNMT/OpenNMT-py) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 2.2K Β· πŸ“¦ 290 Β· πŸ“‹ 1.5K - 1% open Β· ⏱️ 27.06.2024): ``` - git clone https://github.com/facebookresearch/ParlAI + git clone https://github.com/OpenNMT/OpenNMT-py ``` -- [PyPi](https://pypi.org/project/parlai) (πŸ“₯ 2.5K / month Β· πŸ“¦ 5 Β· ⏱️ 20.09.2022): +- [PyPi](https://pypi.org/project/OpenNMT-py) (πŸ“₯ 8.4K / month Β· πŸ“¦ 23 Β· ⏱️ 18.03.2024): ``` - pip install parlai + pip install OpenNMT-py ```
-
ftfy (πŸ₯ˆ32 Β· ⭐ 3.7K) - Fixes mojibake and other glitches in Unicode text, after the fact. Apache-2 +
Dedupe (πŸ₯ˆ32 Β· ⭐ 4.1K) - A python library for accurate and scalable fuzzy matching, record.. MIT -- [GitHub](https://github.com/rspeer/python-ftfy) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 120 Β· πŸ“¦ 20K Β· πŸ“‹ 140 - 13% open Β· ⏱️ 15.03.2024): +- [GitHub](https://github.com/dedupeio/dedupe) (πŸ‘¨β€πŸ’» 72 Β· πŸ”€ 550 Β· πŸ“¦ 330 Β· πŸ“‹ 820 - 8% open Β· ⏱️ 15.08.2024): ``` - git clone https://github.com/rspeer/python-ftfy + git clone https://github.com/dedupeio/dedupe ``` -- [PyPi](https://pypi.org/project/ftfy) (πŸ“₯ 5.1M / month Β· πŸ“¦ 500 Β· ⏱️ 15.03.2024): +- [PyPi](https://pypi.org/project/dedupe) (πŸ“₯ 76K / month Β· πŸ“¦ 19 Β· ⏱️ 15.08.2024): ``` - pip install ftfy + pip install dedupe ``` -- [Conda](https://anaconda.org/conda-forge/ftfy) (πŸ“₯ 290K Β· ⏱️ 22.11.2023): +- [Conda](https://anaconda.org/conda-forge/dedupe) (πŸ“₯ 70K Β· ⏱️ 16.06.2023): ``` - conda install -c conda-forge ftfy + conda install -c conda-forge dedupe ```
DeepPavlov (πŸ₯ˆ31 Β· ⭐ 6.6K) - An open source library for deep learning end-to-end dialog.. Apache-2 -- [GitHub](https://github.com/deeppavlov/DeepPavlov) (πŸ‘¨β€πŸ’» 77 Β· πŸ”€ 1.1K Β· πŸ“¦ 390 Β· πŸ“‹ 640 - 3% open Β· ⏱️ 13.03.2024): +- [GitHub](https://github.com/deeppavlov/DeepPavlov) (πŸ‘¨β€πŸ’» 77 Β· πŸ”€ 1.1K Β· πŸ“¦ 400 Β· πŸ“‹ 640 - 3% open Β· ⏱️ 12.08.2024): ``` git clone https://github.com/deepmipt/DeepPavlov ``` -- [PyPi](https://pypi.org/project/deeppavlov) (πŸ“₯ 10K / month Β· πŸ“¦ 4 Β· ⏱️ 13.03.2024): +- [PyPi](https://pypi.org/project/deeppavlov) (πŸ“₯ 10K / month Β· πŸ“¦ 4 Β· ⏱️ 12.08.2024): ``` pip install deeppavlov ```
TextDistance (πŸ₯ˆ30 Β· ⭐ 3.3K) - Compute distance between sequences. 30+ algorithms, pure python.. MIT -- [GitHub](https://github.com/life4/textdistance) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 240 Β· πŸ“₯ 1K Β· πŸ“¦ 6.4K Β· ⏱️ 24.04.2024): +- [GitHub](https://github.com/life4/textdistance) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 250 Β· πŸ“₯ 1K Β· πŸ“¦ 7K Β· ⏱️ 03.09.2024): ``` git clone https://github.com/life4/textdistance ``` -- [PyPi](https://pypi.org/project/textdistance) (πŸ“₯ 810K / month Β· πŸ“¦ 93 Β· ⏱️ 24.04.2024): +- [PyPi](https://pypi.org/project/textdistance) (πŸ“₯ 840K / month Β· πŸ“¦ 99 Β· ⏱️ 16.07.2024): ``` pip install textdistance ``` -- [Conda](https://anaconda.org/conda-forge/textdistance) (πŸ“₯ 560K Β· ⏱️ 25.04.2024): +- [Conda](https://anaconda.org/conda-forge/textdistance) (πŸ“₯ 610K Β· ⏱️ 17.07.2024): ``` conda install -c conda-forge textdistance ```
-
spacy-transformers (πŸ₯ˆ30 Β· ⭐ 1.3K) - Use pretrained transformers like BERT, XLNet and GPT-2.. MIT spacy +
snowballstemmer (πŸ₯ˆ30 Β· ⭐ 750) - Snowball compiler and stemming algorithms. BSD-3 -- [GitHub](https://github.com/explosion/spacy-transformers) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 160 Β· πŸ“¦ 1.7K Β· ⏱️ 05.06.2024): - - ``` - git clone https://github.com/explosion/spacy-transformers - ``` -- [PyPi](https://pypi.org/project/spacy-transformers) (πŸ“₯ 280K / month Β· πŸ“¦ 51 Β· ⏱️ 25.04.2024): - ``` - pip install spacy-transformers - ``` -- [Conda](https://anaconda.org/conda-forge/spacy-transformers) (πŸ“₯ 37K Β· ⏱️ 19.12.2023): - ``` - conda install -c conda-forge spacy-transformers - ``` -
-
snowballstemmer (πŸ₯ˆ30 Β· ⭐ 720) - Snowball compiler and stemming algorithms. BSD-3 - -- [GitHub](https://github.com/snowballstem/snowball) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 170 Β· πŸ“¦ 5 Β· πŸ“‹ 88 - 30% open Β· ⏱️ 02.05.2024): +- [GitHub](https://github.com/snowballstem/snowball) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 170 Β· πŸ“¦ 9 Β· πŸ“‹ 89 - 30% open Β· ⏱️ 02.09.2024): ``` git clone https://github.com/snowballstem/snowball ``` -- [PyPi](https://pypi.org/project/snowballstemmer) (πŸ“₯ 15M / month Β· πŸ“¦ 410 Β· ⏱️ 16.11.2021): +- [PyPi](https://pypi.org/project/snowballstemmer) (πŸ“₯ 20M / month Β· πŸ“¦ 440 Β· ⏱️ 16.11.2021): ``` pip install snowballstemmer ``` -- [Conda](https://anaconda.org/conda-forge/snowballstemmer) (πŸ“₯ 8.1M Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/snowballstemmer) (πŸ“₯ 8.6M Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge snowballstemmer ```
-
Dedupe (πŸ₯ˆ29 Β· ⭐ 4K) - A python library for accurate and scalable fuzzy matching, record.. MIT +
spacy-transformers (πŸ₯ˆ29 Β· ⭐ 1.3K) - Use pretrained transformers like BERT, XLNet and GPT-2.. MIT spacy -- [GitHub](https://github.com/dedupeio/dedupe) (πŸ‘¨β€πŸ’» 70 Β· πŸ”€ 540 Β· πŸ“¦ 330 Β· πŸ“‹ 810 - 9% open Β· ⏱️ 19.12.2023): +- [GitHub](https://github.com/explosion/spacy-transformers) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 160 Β· πŸ“¦ 1.8K Β· ⏱️ 05.06.2024): ``` - git clone https://github.com/dedupeio/dedupe + git clone https://github.com/explosion/spacy-transformers ``` -- [PyPi](https://pypi.org/project/dedupe) (πŸ“₯ 67K / month Β· πŸ“¦ 18 Β· ⏱️ 17.02.2023): +- [PyPi](https://pypi.org/project/spacy-transformers) (πŸ“₯ 250K / month Β· πŸ“¦ 87 Β· ⏱️ 25.04.2024): ``` - pip install dedupe + pip install spacy-transformers ``` -- [Conda](https://anaconda.org/conda-forge/dedupe) (πŸ“₯ 52K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/spacy-transformers) (πŸ“₯ 59K Β· ⏱️ 19.12.2023): ``` - conda install -c conda-forge dedupe + conda install -c conda-forge spacy-transformers ```
-
Sumy (πŸ₯ˆ29 Β· ⭐ 3.4K) - Module for automatic summarization of text documents and HTML pages. Apache-2 +
Sumy (πŸ₯ˆ28 Β· ⭐ 3.5K) - Module for automatic summarization of text documents and HTML pages. Apache-2 -- [GitHub](https://github.com/miso-belica/sumy) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 520 Β· πŸ“¦ 2.8K Β· πŸ“‹ 120 - 17% open Β· ⏱️ 16.05.2024): +- [GitHub](https://github.com/miso-belica/sumy) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 530 Β· πŸ“¦ 3K Β· πŸ“‹ 120 - 18% open Β· ⏱️ 16.05.2024): ``` git clone https://github.com/miso-belica/sumy ``` -- [PyPi](https://pypi.org/project/sumy) (πŸ“₯ 530K / month Β· πŸ“¦ 27 Β· ⏱️ 23.10.2022): +- [PyPi](https://pypi.org/project/sumy) (πŸ“₯ 430K / month Β· πŸ“¦ 28 Β· ⏱️ 23.10.2022): ``` pip install sumy ``` -- [Conda](https://anaconda.org/conda-forge/sumy) (πŸ“₯ 8.1K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/sumy) (πŸ“₯ 9.1K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge sumy ```
-
SciSpacy (πŸ₯ˆ28 Β· ⭐ 1.6K Β· πŸ“‰) - A full spaCy pipeline and models for scientific/biomedical.. Apache-2 +
SciSpacy (πŸ₯ˆ28 Β· ⭐ 1.7K) - A full spaCy pipeline and models for scientific/biomedical documents. Apache-2 -- [GitHub](https://github.com/allenai/scispacy) (πŸ‘¨β€πŸ’» 33 Β· πŸ”€ 220 Β· πŸ“¦ 910 Β· πŸ“‹ 310 - 10% open Β· ⏱️ 30.03.2024): +- [GitHub](https://github.com/allenai/scispacy) (πŸ‘¨β€πŸ’» 33 Β· πŸ”€ 220 Β· πŸ“¦ 950 Β· πŸ“‹ 320 - 10% open Β· ⏱️ 30.03.2024): ``` git clone https://github.com/allenai/scispacy ``` -- [PyPi](https://pypi.org/project/scispacy) (πŸ“₯ 26K / month Β· πŸ“¦ 34 Β· ⏱️ 08.03.2024): +- [PyPi](https://pypi.org/project/scispacy) (πŸ“₯ 24K / month Β· πŸ“¦ 34 Β· ⏱️ 08.03.2024): ``` pip install scispacy ```
-
CLTK (πŸ₯ˆ28 Β· ⭐ 820) - The Classical Language Toolkit. MIT +
CLTK (πŸ₯ˆ28 Β· ⭐ 830) - The Classical Language Toolkit. MIT -- [GitHub](https://github.com/cltk/cltk) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 320 Β· πŸ“₯ 64 Β· πŸ“¦ 260 Β· πŸ“‹ 570 - 6% open Β· ⏱️ 12.05.2024): +- [GitHub](https://github.com/cltk/cltk) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 330 Β· πŸ“₯ 83 Β· πŸ“¦ 270 Β· πŸ“‹ 570 - 6% open Β· ⏱️ 12.05.2024): ``` git clone https://github.com/cltk/cltk ``` -- [PyPi](https://pypi.org/project/cltk) (πŸ“₯ 1.9K / month Β· πŸ“¦ 15 Β· ⏱️ 12.05.2024): +- [PyPi](https://pypi.org/project/cltk) (πŸ“₯ 1.6K / month Β· πŸ“¦ 15 Β· ⏱️ 12.05.2024): ``` pip install cltk ```
-
DeepKE (πŸ₯‰27 Β· ⭐ 3.1K) - [EMNLP 2022] An Open Toolkit for Knowledge Graph Extraction and.. MIT +
Ciphey (πŸ₯ˆ27 Β· ⭐ 18K Β· πŸ’€) - Automatically decrypt encryptions without knowing the key or cipher,.. MIT -- [GitHub](https://github.com/zjunlp/DeepKE) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 640 Β· πŸ“¦ 21 Β· πŸ“‹ 490 - 0% open Β· ⏱️ 03.06.2024): - - ``` - git clone https://github.com/zjunlp/deepke - ``` -- [PyPi](https://pypi.org/project/deepke) (πŸ“₯ 440 / month Β· ⏱️ 21.09.2023): - ``` - pip install deepke - ``` -
-
Ciphey (πŸ₯‰26 Β· ⭐ 17K Β· πŸ’€) - Automatically decrypt encryptions without knowing the key or cipher,.. MIT - -- [GitHub](https://github.com/Ciphey/Ciphey) (πŸ‘¨β€πŸ’» 48 Β· πŸ”€ 1.1K Β· πŸ“‹ 330 - 20% open Β· ⏱️ 12.10.2023): +- [GitHub](https://github.com/Ciphey/Ciphey) (πŸ‘¨β€πŸ’» 48 Β· πŸ”€ 1.1K Β· πŸ“‹ 340 - 21% open Β· ⏱️ 12.10.2023): ``` git clone https://github.com/Ciphey/Ciphey ``` -- [PyPi](https://pypi.org/project/ciphey) (πŸ“₯ 41K / month Β· ⏱️ 06.06.2021): +- [PyPi](https://pypi.org/project/ciphey) (πŸ“₯ 36K / month Β· ⏱️ 06.06.2021): ``` pip install ciphey ``` -- [Docker Hub](https://hub.docker.com/r/remnux/ciphey) (πŸ“₯ 24K Β· ⭐ 17 Β· ⏱️ 14.10.2023): +- [Docker Hub](https://hub.docker.com/r/remnux/ciphey) (πŸ“₯ 25K Β· ⭐ 17 Β· ⏱️ 14.10.2023): ``` docker pull remnux/ciphey ```
-
scattertext (πŸ₯‰26 Β· ⭐ 2.2K) - Beautiful visualizations of how language differs among document.. Apache-2 +
DeepKE (πŸ₯ˆ27 Β· ⭐ 3.4K) - [EMNLP 2022] An Open Toolkit for Knowledge Graph Extraction and.. MIT -- [GitHub](https://github.com/JasonKessler/scattertext) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 280 Β· πŸ“¦ 560 Β· πŸ“‹ 100 - 21% open Β· ⏱️ 06.03.2024): +- [GitHub](https://github.com/zjunlp/DeepKE) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 670 Β· πŸ“¦ 23 Β· πŸ“‹ 560 - 1% open Β· ⏱️ 04.09.2024): ``` - git clone https://github.com/JasonKessler/scattertext - ``` -- [PyPi](https://pypi.org/project/scattertext) (πŸ“₯ 12K / month Β· πŸ“¦ 5 Β· ⏱️ 06.03.2024): - ``` - pip install scattertext + git clone https://github.com/zjunlp/deepke ``` -- [Conda](https://anaconda.org/conda-forge/scattertext) (πŸ“₯ 90K Β· ⏱️ 16.06.2023): +- [PyPi](https://pypi.org/project/deepke) (πŸ“₯ 1.4K / month Β· ⏱️ 21.09.2023): ``` - conda install -c conda-forge scattertext + pip install deepke ```
-
PyTextRank (πŸ₯‰26 Β· ⭐ 2.1K) - Python implementation of TextRank algorithms (textgraphs) for phrase.. MIT +
english-words (πŸ₯‰26 Β· ⭐ 10K) - A text file containing 479k English words for all your.. Unlicense -- [GitHub](https://github.com/DerwenAI/pytextrank) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 340 Β· πŸ“¦ 660 Β· πŸ“‹ 100 - 8% open Β· ⏱️ 21.05.2024): +- [GitHub](https://github.com/dwyl/english-words) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 1.8K Β· πŸ“¦ 2 Β· πŸ“‹ 150 - 75% open Β· ⏱️ 16.06.2024): ``` - git clone https://github.com/DerwenAI/pytextrank + git clone https://github.com/dwyl/english-words ``` -- [PyPi](https://pypi.org/project/pytextrank) (πŸ“₯ 42K / month Β· πŸ“¦ 18 Β· ⏱️ 21.02.2024): +- [PyPi](https://pypi.org/project/english-words) (πŸ“₯ 64K / month Β· πŸ“¦ 14 Β· ⏱️ 24.05.2023): ``` - pip install pytextrank + pip install english-words ```
-
promptsource (πŸ₯‰24 Β· ⭐ 2.5K Β· πŸ’€) - Toolkit for creating, sharing and using natural language.. Apache-2 +
PyTextRank (πŸ₯‰26 Β· ⭐ 2.1K) - Python implementation of TextRank algorithms (textgraphs) for phrase.. MIT -- [GitHub](https://github.com/bigscience-workshop/promptsource) (πŸ‘¨β€πŸ’» 65 Β· πŸ”€ 340 Β· πŸ“¦ 96 Β· πŸ“‹ 190 - 22% open Β· ⏱️ 23.10.2023): +- [GitHub](https://github.com/DerwenAI/pytextrank) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 340 Β· πŸ“¦ 700 Β· πŸ“‹ 100 - 12% open Β· ⏱️ 21.05.2024): ``` - git clone https://github.com/bigscience-workshop/promptsource + git clone https://github.com/DerwenAI/pytextrank ``` -- [PyPi](https://pypi.org/project/promptsource) (πŸ“₯ 640 / month Β· πŸ“¦ 4 Β· ⏱️ 18.04.2022): +- [PyPi](https://pypi.org/project/pytextrank) (πŸ“₯ 51K / month Β· πŸ“¦ 19 Β· ⏱️ 21.02.2024): ``` - pip install promptsource + pip install pytextrank ```
-
pytorch-nlp (πŸ₯‰24 Β· ⭐ 2.2K Β· πŸ’€) - Basic Utilities for PyTorch Natural Language Processing.. BSD-3 +
scattertext (πŸ₯‰25 Β· ⭐ 2.2K) - Beautiful visualizations of how language differs among document.. Apache-2 -- [GitHub](https://github.com/PetrochukM/PyTorch-NLP) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 250 Β· πŸ“¦ 690 Β· πŸ“‹ 69 - 27% open Β· ⏱️ 04.07.2023): +- [GitHub](https://github.com/JasonKessler/scattertext) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 290 Β· πŸ“¦ 610 Β· πŸ“‹ 100 - 21% open Β· ⏱️ 06.03.2024): ``` - git clone https://github.com/PetrochukM/PyTorch-NLP - ``` -- [PyPi](https://pypi.org/project/pytorch-nlp) (πŸ“₯ 5.2K / month Β· πŸ“¦ 19 Β· ⏱️ 04.11.2019): - ``` - pip install pytorch-nlp + git clone https://github.com/JasonKessler/scattertext ``` -
-
detoxify (πŸ₯‰24 Β· ⭐ 870) - Trained models & code to predict toxic comments on all 3 Jigsaw.. Apache-2 - -- [GitHub](https://github.com/unitaryai/detoxify) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 110 Β· πŸ“₯ 500K Β· πŸ“¦ 600 Β· πŸ“‹ 62 - 56% open Β· ⏱️ 16.05.2024): - +- [PyPi](https://pypi.org/project/scattertext) (πŸ“₯ 17K / month Β· πŸ“¦ 5 Β· ⏱️ 06.03.2024): ``` - git clone https://github.com/unitaryai/detoxify + pip install scattertext ``` -- [PyPi](https://pypi.org/project/detoxify) (πŸ“₯ 30K / month Β· πŸ“¦ 15 Β· ⏱️ 01.02.2024): +- [Conda](https://anaconda.org/conda-forge/scattertext) (πŸ“₯ 97K Β· ⏱️ 16.06.2023): ``` - pip install detoxify + conda install -c conda-forge scattertext ```
-
T5 (πŸ₯‰23 Β· ⭐ 6K) - Code for the paper Exploring the Limits of Transfer Learning with a.. Apache-2 +
promptsource (πŸ₯‰24 Β· ⭐ 2.6K Β· πŸ’€) - Toolkit for creating, sharing and using natural language.. Apache-2 -- [GitHub](https://github.com/google-research/text-to-text-transfer-transformer) (πŸ‘¨β€πŸ’» 59 Β· πŸ”€ 740 Β· πŸ“‹ 450 - 23% open Β· ⏱️ 23.01.2024): +- [GitHub](https://github.com/bigscience-workshop/promptsource) (πŸ‘¨β€πŸ’» 65 Β· πŸ”€ 340 Β· πŸ“¦ 110 Β· πŸ“‹ 190 - 22% open Β· ⏱️ 23.10.2023): ``` - git clone https://github.com/google-research/text-to-text-transfer-transformer + git clone https://github.com/bigscience-workshop/promptsource ``` -- [PyPi](https://pypi.org/project/t5) (πŸ“₯ 38K / month Β· πŸ“¦ 2 Β· ⏱️ 18.10.2021): +- [PyPi](https://pypi.org/project/promptsource) (πŸ“₯ 360 / month Β· πŸ“¦ 4 Β· ⏱️ 18.04.2022): ``` - pip install t5 + pip install promptsource ```
-
Texthero (πŸ₯‰23 Β· ⭐ 2.9K Β· πŸ’€) - Text preprocessing, representation and visualization from zero to.. MIT +
T5 (πŸ₯‰23 Β· ⭐ 6.1K) - Code for the paper Exploring the Limits of Transfer Learning with a.. Apache-2 -- [GitHub](https://github.com/jbesomi/texthero) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 240 Β· πŸ“₯ 120 Β· πŸ“‹ 140 - 55% open Β· ⏱️ 29.08.2023): +- [GitHub](https://github.com/google-research/text-to-text-transfer-transformer) (πŸ‘¨β€πŸ’» 59 Β· πŸ”€ 740 Β· πŸ“‹ 450 - 23% open Β· ⏱️ 28.06.2024): ``` - git clone https://github.com/jbesomi/texthero + git clone https://github.com/google-research/text-to-text-transfer-transformer ``` -- [PyPi](https://pypi.org/project/texthero) (πŸ“₯ 8.8K / month Β· πŸ“¦ 6 Β· ⏱️ 01.07.2021): +- [PyPi](https://pypi.org/project/t5) (πŸ“₯ 67K / month Β· πŸ“¦ 2 Β· ⏱️ 18.10.2021): ``` - pip install texthero + pip install t5 ```
-
happy-transformer (πŸ₯‰22 Β· ⭐ 510) - Happy Transformer makes it easy to fine-tune and.. Apache-2 huggingface +
happy-transformer (πŸ₯‰23 Β· ⭐ 520) - Happy Transformer makes it easy to fine-tune and.. Apache-2 huggingface -- [GitHub](https://github.com/EricFillion/happy-transformer) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 67 Β· πŸ“¦ 260 Β· πŸ“‹ 130 - 14% open Β· ⏱️ 19.03.2024): +- [GitHub](https://github.com/EricFillion/happy-transformer) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 66 Β· πŸ“¦ 280 Β· πŸ“‹ 130 - 15% open Β· ⏱️ 19.03.2024): ``` git clone https://github.com/EricFillion/happy-transformer ``` -- [PyPi](https://pypi.org/project/happytransformer) (πŸ“₯ 2.5K / month Β· πŸ“¦ 5 Β· ⏱️ 05.08.2023): +- [PyPi](https://pypi.org/project/happytransformer) (πŸ“₯ 2.3K / month Β· πŸ“¦ 5 Β· ⏱️ 05.08.2023): ``` pip install happytransformer ```
-
fast-bert (πŸ₯‰21 Β· ⭐ 1.8K) - Super easy library for BERT based NLP models. Apache-2 +
fast-bert (πŸ₯‰22 Β· ⭐ 1.9K) - Super easy library for BERT based NLP models. Apache-2 -- [GitHub](https://github.com/utterworks/fast-bert) (πŸ‘¨β€πŸ’» 36 Β· πŸ”€ 340 Β· πŸ“‹ 260 - 63% open Β· ⏱️ 30.01.2024): +- [GitHub](https://github.com/utterworks/fast-bert) (πŸ‘¨β€πŸ’» 37 Β· πŸ”€ 340 Β· πŸ“‹ 260 - 63% open Β· ⏱️ 19.08.2024): ``` git clone https://github.com/utterworks/fast-bert ``` -- [PyPi](https://pypi.org/project/fast-bert) (πŸ“₯ 790 / month Β· ⏱️ 30.01.2024): +- [PyPi](https://pypi.org/project/fast-bert) (πŸ“₯ 1.4K / month Β· ⏱️ 19.08.2024): ``` pip install fast-bert ```
-
Sockeye (πŸ₯‰21 Β· ⭐ 1.2K) - Sequence-to-sequence framework with a focus on Neural Machine.. Apache-2 +
detoxify (πŸ₯‰22 Β· ⭐ 920) - Trained models & code to predict toxic comments on all 3 Jigsaw.. Apache-2 -- [GitHub](https://github.com/awslabs/sockeye) (πŸ‘¨β€πŸ’» 60 Β· πŸ”€ 330 Β· πŸ“₯ 18 Β· πŸ“‹ 310 - 3% open Β· ⏱️ 22.05.2024): +- [GitHub](https://github.com/unitaryai/detoxify) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 120 Β· πŸ“₯ 640K Β· πŸ“¦ 670 Β· πŸ“‹ 67 - 56% open Β· ⏱️ 17.08.2024): ``` - git clone https://github.com/awslabs/sockeye + git clone https://github.com/unitaryai/detoxify ``` -- [PyPi](https://pypi.org/project/sockeye) (πŸ“₯ 1K / month Β· ⏱️ 03.03.2023): +- [PyPi](https://pypi.org/project/detoxify) (πŸ“₯ 27K / month Β· πŸ“¦ 30 Β· ⏱️ 01.02.2024): ``` - pip install sockeye + pip install detoxify ```
-
finetune (πŸ₯‰21 Β· ⭐ 700) - Scikit-learn style model finetuning for NLP. MPL-2.0 +
finetune (πŸ₯‰22 Β· ⭐ 700) - Scikit-learn style model finetuning for NLP. MPL-2.0 -- [GitHub](https://github.com/IndicoDataSolutions/finetune) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 80 Β· πŸ“¦ 11 Β· πŸ“‹ 140 - 15% open Β· ⏱️ 27.03.2024): +- [GitHub](https://github.com/IndicoDataSolutions/finetune) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 80 Β· πŸ“¦ 12 Β· πŸ“‹ 140 - 15% open Β· ⏱️ 23.07.2024): ``` git clone https://github.com/IndicoDataSolutions/finetune ``` -- [PyPi](https://pypi.org/project/finetune) (πŸ“₯ 150 / month Β· πŸ“¦ 2 Β· ⏱️ 29.09.2023): +- [PyPi](https://pypi.org/project/finetune) (πŸ“₯ 270 / month Β· πŸ“¦ 2 Β· ⏱️ 29.09.2023): ``` pip install finetune ```
-
UForm (πŸ₯‰20 Β· ⭐ 930) - Pocket-Sized Multimodal AI for content understanding and.. Apache-2 +
small-text (πŸ₯‰22 Β· ⭐ 540) - Active Learning for Text Classification in Python. MIT -- [GitHub](https://github.com/unum-cloud/uform) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 56 Β· πŸ“₯ 290 Β· πŸ“¦ 6 Β· πŸ“‹ 24 - 20% open Β· ⏱️ 25.04.2024): +- [GitHub](https://github.com/webis-de/small-text) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 60 Β· πŸ“¦ 30 Β· πŸ“‹ 57 - 22% open Β· ⏱️ 18.08.2024): ``` - git clone https://github.com/unum-cloud/uform + git clone https://github.com/webis-de/small-text ``` -- [PyPi](https://pypi.org/project/uform) (πŸ“₯ 730 / month Β· πŸ“¦ 1 Β· ⏱️ 25.04.2024): +- [PyPi](https://pypi.org/project/small-text) (πŸ“₯ 710 / month Β· ⏱️ 18.08.2024): ``` - pip install uform + pip install small-text + ``` +- [Conda](https://anaconda.org/conda-forge/small-text) (πŸ“₯ 8.7K Β· ⏱️ 18.08.2024): + ``` + conda install -c conda-forge small-text ```
-
small-text (πŸ₯‰20 Β· ⭐ 520) - Active Learning for Text Classification in Python. MIT +
Sockeye (πŸ₯‰21 Β· ⭐ 1.2K) - Sequence-to-sequence framework with a focus on Neural Machine.. Apache-2 -- [GitHub](https://github.com/webis-de/small-text) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 57 Β· πŸ“¦ 28 Β· πŸ“‹ 54 - 29% open Β· ⏱️ 29.12.2023): +- [GitHub](https://github.com/awslabs/sockeye) (πŸ‘¨β€πŸ’» 60 Β· πŸ”€ 320 Β· πŸ“₯ 19 Β· πŸ“‹ 310 - 3% open Β· ⏱️ 07.06.2024): ``` - git clone https://github.com/webis-de/small-text + git clone https://github.com/awslabs/sockeye + ``` +- [PyPi](https://pypi.org/project/sockeye) (πŸ“₯ 760 / month Β· ⏱️ 03.03.2023): ``` -- [PyPi](https://pypi.org/project/small-text) (πŸ“₯ 720 / month Β· ⏱️ 29.12.2023): + pip install sockeye + ``` +
+
UForm (πŸ₯‰18 Β· ⭐ 1K) - Pocket-Sized Multimodal AI for content understanding and generation.. Apache-2 + +- [GitHub](https://github.com/unum-cloud/uform) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 60 Β· πŸ“₯ 380 Β· πŸ“¦ 6 Β· πŸ“‹ 29 - 27% open Β· ⏱️ 25.04.2024): + ``` - pip install small-text + git clone https://github.com/unum-cloud/uform ``` -- [Conda](https://anaconda.org/conda-forge/small-text) (πŸ“₯ 6.3K Β· ⏱️ 29.12.2023): +- [PyPi](https://pypi.org/project/uform) (πŸ“₯ 940 / month Β· πŸ“¦ 1 Β· ⏱️ 25.04.2024): ``` - conda install -c conda-forge small-text + pip install uform ```
-
textaugment (πŸ₯‰18 Β· ⭐ 380 Β· πŸ’€) - TextAugment: Text Augmentation Library. MIT +
textaugment (πŸ₯‰18 Β· ⭐ 390 Β· πŸ’€) - TextAugment: Text Augmentation Library. MIT -- [GitHub](https://github.com/dsfsi/textaugment) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 59 Β· πŸ“₯ 69 Β· πŸ“¦ 99 Β· πŸ“‹ 29 - 37% open Β· ⏱️ 17.11.2023): +- [GitHub](https://github.com/dsfsi/textaugment) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 60 Β· πŸ“₯ 92 Β· πŸ“¦ 120 Β· πŸ“‹ 29 - 37% open Β· ⏱️ 17.11.2023): ``` git clone https://github.com/dsfsi/textaugment ``` -- [PyPi](https://pypi.org/project/textaugment) (πŸ“₯ 5K / month Β· πŸ“¦ 4 Β· ⏱️ 16.11.2023): +- [PyPi](https://pypi.org/project/textaugment) (πŸ“₯ 6.1K / month Β· πŸ“¦ 4 Β· ⏱️ 16.11.2023): ``` pip install textaugment ```
-
OpenNRE (πŸ₯‰17 Β· ⭐ 4.3K) - An Open-Source Package for Neural Relation Extraction (NRE). MIT +
OpenNRE (πŸ₯‰16 Β· ⭐ 4.3K Β· πŸ’€) - An Open-Source Package for Neural Relation Extraction (NRE). MIT -- [GitHub](https://github.com/thunlp/OpenNRE) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 1.1K Β· πŸ“¦ 3 Β· πŸ“‹ 370 - 4% open Β· ⏱️ 10.01.2024): +- [GitHub](https://github.com/thunlp/OpenNRE) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 1.1K Β· πŸ“‹ 370 - 4% open Β· ⏱️ 10.01.2024): ``` git clone https://github.com/thunlp/OpenNRE ```
-
VizSeq (πŸ₯‰15 Β· ⭐ 440) - An Analysis Toolkit for Natural Language Generation (Translation,.. MIT +
VizSeq (πŸ₯‰14 Β· ⭐ 440) - An Analysis Toolkit for Natural Language Generation (Translation,.. MIT -- [GitHub](https://github.com/facebookresearch/vizseq) (πŸ‘¨β€πŸ’» 4 Β· πŸ”€ 61 Β· πŸ“¦ 9 Β· πŸ“‹ 16 - 43% open Β· ⏱️ 21.04.2024): +- [GitHub](https://github.com/facebookresearch/vizseq) (πŸ‘¨β€πŸ’» 4 Β· πŸ”€ 61 Β· πŸ“¦ 11 Β· πŸ“‹ 16 - 43% open Β· ⏱️ 18.06.2024): ``` git clone https://github.com/facebookresearch/vizseq ``` -- [PyPi](https://pypi.org/project/vizseq) (πŸ“₯ 130 / month Β· ⏱️ 07.08.2020): +- [PyPi](https://pypi.org/project/vizseq) (πŸ“₯ 110 / month Β· ⏱️ 07.08.2020): ``` pip install vizseq ```
-
Show 51 hidden projects... +
Show 52 hidden projects... -- ChatterBot (πŸ₯ˆ35 Β· ⭐ 14K Β· πŸ’€) - ChatterBot is a machine learning, conversational dialog engine.. BSD-3 -- AllenNLP (πŸ₯ˆ35 Β· ⭐ 12K Β· πŸ’€) - An open-source NLP research library, built on PyTorch. Apache-2 -- fuzzywuzzy (πŸ₯ˆ33 Β· ⭐ 9.1K Β· πŸ’€) - Fuzzy String Matching in Python. ❗️GPL-2.0 -- nlpaug (πŸ₯ˆ29 Β· ⭐ 4.3K Β· πŸ’€) - Data augmentation for NLP. MIT +- AllenNLP (πŸ₯ˆ36 Β· ⭐ 12K Β· πŸ’€) - An open-source NLP research library, built on PyTorch. Apache-2 +- ChatterBot (πŸ₯ˆ34 Β· ⭐ 14K Β· πŸ’€) - ChatterBot is a machine learning, conversational dialog engine.. BSD-3 +- fuzzywuzzy (πŸ₯ˆ31 Β· ⭐ 9.2K Β· πŸ’€) - Fuzzy String Matching in Python. ❗️GPL-2.0 +- nlpaug (πŸ₯ˆ29 Β· ⭐ 4.4K Β· πŸ’€) - Data augmentation for NLP. MIT +- fastNLP (πŸ₯ˆ29 Β· ⭐ 3.1K Β· πŸ’€) - fastNLP: A Modularized and Extensible NLP Framework. Currently.. Apache-2 - GluonNLP (πŸ₯ˆ29 Β· ⭐ 2.6K Β· πŸ’€) - Toolkit that enables easy text preprocessing, datasets.. Apache-2 -- english-words (πŸ₯ˆ28 Β· ⭐ 10K Β· πŸ’€) - A text file containing 479k English words for all your.. Unlicense -- fastNLP (πŸ₯ˆ28 Β· ⭐ 3K Β· πŸ’€) - fastNLP: A Modularized and Extensible NLP Framework. Currently.. Apache-2 - langid (πŸ₯ˆ28 Β· ⭐ 2.3K Β· πŸ’€) - Stand-alone language identification system. BSD-3 -- vaderSentiment (πŸ₯‰27 Β· ⭐ 4.3K Β· πŸ’€) - VADER Sentiment Analysis. VADER (Valence Aware Dictionary.. MIT -- polyglot (πŸ₯‰27 Β· ⭐ 2.3K Β· πŸ’€) - Multilingual text (NLP) processing toolkit. ❗️GPL-3.0 -- textacy (πŸ₯‰27 Β· ⭐ 2.2K Β· πŸ’€) - NLP, before and after spaCy. ❗Unlicensed -- flashtext (πŸ₯‰26 Β· ⭐ 5.6K Β· πŸ’€) - Extract Keywords from sentence or Replace keywords in sentences. MIT -- underthesea (πŸ₯‰26 Β· ⭐ 1.3K Β· πŸ’€) - Underthesea - Vietnamese NLP Toolkit. ❗️GPL-3.0 -- Snips NLU (πŸ₯‰25 Β· ⭐ 3.9K Β· πŸ’€) - Snips Python library to extract meaning from text. Apache-2 +- flashtext (πŸ₯ˆ27 Β· ⭐ 5.6K Β· πŸ’€) - Extract Keywords from sentence or Replace keywords in sentences. MIT +- vaderSentiment (πŸ₯ˆ27 Β· ⭐ 4.4K Β· πŸ’€) - VADER Sentiment Analysis. VADER (Valence Aware Dictionary.. MIT +- textacy (πŸ₯ˆ27 Β· ⭐ 2.2K Β· πŸ’€) - NLP, before and after spaCy. ❗Unlicensed +- underthesea (πŸ₯ˆ27 Β· ⭐ 1.4K) - Underthesea - Vietnamese NLP Toolkit. ❗️GPL-3.0 +- polyglot (πŸ₯‰26 Β· ⭐ 2.3K Β· πŸ’€) - Multilingual text (NLP) processing toolkit. ❗️GPL-3.0 +- FARM (πŸ₯‰26 Β· ⭐ 1.7K Β· πŸ’€) - Fast & easy transfer learning for NLP. Harvesting language.. Apache-2 +- pySBD (πŸ₯‰26 Β· ⭐ 780 Β· πŸ’€) - pySBD (Python Sentence Boundary Disambiguation) is a rule-based sentence.. MIT +- OpenPrompt (πŸ₯‰25 Β· ⭐ 4.3K Β· πŸ’€) - An Open-Source Framework for Prompt-Learning. Apache-2 +- MatchZoo (πŸ₯‰25 Β· ⭐ 3.8K Β· πŸ’€) - Facilitating the design, comparison and sharing of deep.. Apache-2 - neuralcoref (πŸ₯‰25 Β· ⭐ 2.8K Β· πŸ’€) - Fast Coreference Resolution in spaCy with Neural Networks. MIT -- pySBD (πŸ₯‰25 Β· ⭐ 740 Β· πŸ’€) - pySBD (Python Sentence Boundary Disambiguation) is a rule-based sentence.. MIT -- whoosh (πŸ₯‰25 Β· ⭐ 540 Β· πŸ’€) - Pure-Python full-text search library. ❗️BSD-1-Clause -- PyText (πŸ₯‰24 Β· ⭐ 6.4K Β· πŸ’€) - A natural language modeling framework based on PyTorch. BSD-3 +- pytorch-nlp (πŸ₯‰25 Β· ⭐ 2.2K Β· πŸ’€) - Basic Utilities for PyTorch Natural Language Processing.. BSD-3 +- whoosh (πŸ₯‰25 Β· ⭐ 570 Β· πŸ’€) - Pure-Python full-text search library. ❗️BSD-1-Clause +- PyText (πŸ₯‰24 Β· ⭐ 6.3K Β· πŸ’€) - A natural language modeling framework based on PyTorch. BSD-3 - textgenrnn (πŸ₯‰24 Β· ⭐ 4.9K Β· πŸ’€) - Easily train your own text-generating neural network of any.. MIT -- OpenPrompt (πŸ₯‰24 Β· ⭐ 4.2K Β· πŸ’€) - An Open-Source Framework for Prompt-Learning. Apache-2 -- MatchZoo (πŸ₯‰24 Β· ⭐ 3.8K Β· πŸ’€) - Facilitating the design, comparison and sharing of deep.. Apache-2 +- Snips NLU (πŸ₯‰24 Β· ⭐ 3.9K Β· πŸ’€) - Snips Python library to extract meaning from text. Apache-2 +- Kashgari (πŸ₯‰24 Β· ⭐ 2.4K Β· πŸ’€) - Kashgari is a production-level NLP Transfer learning.. Apache-2 - sense2vec (πŸ₯‰24 Β· ⭐ 1.6K Β· πŸ’€) - Contextually-keyed word vectors. MIT -- DeepMatcher (πŸ₯‰23 Β· ⭐ 5K Β· πŸ’€) - Python package for performing Entity and Text Matching using.. BSD-3 -- Kashgari (πŸ₯‰23 Β· ⭐ 2.4K Β· πŸ’€) - Kashgari is a production-level NLP Transfer learning.. Apache-2 -- FARM (πŸ₯‰23 Β· ⭐ 1.7K Β· πŸ’€) - Fast & easy transfer learning for NLP. Harvesting language.. Apache-2 - gpt-2-simple (πŸ₯‰22 Β· ⭐ 3.4K Β· πŸ’€) - Python package to easily retrain OpenAIs GPT-2 text-.. MIT +- NLP Architect (πŸ₯‰22 Β· ⭐ 2.9K Β· πŸ’€) - A model library for exploring state-of-the-art deep.. Apache-2 +- Texthero (πŸ₯‰22 Β· ⭐ 2.9K Β· πŸ’€) - Text preprocessing, representation and visualization from zero to.. MIT - Texar (πŸ₯‰22 Β· ⭐ 2.4K Β· πŸ’€) - Toolkit for Machine Learning, Natural Language Processing, and.. Apache-2 - jiant (πŸ₯‰22 Β· ⭐ 1.6K Β· πŸ’€) - jiant is an nlp toolkit. MIT - YouTokenToMe (πŸ₯‰22 Β· ⭐ 950 Β· πŸ’€) - Unsupervised text tokenizer focused on computational efficiency. MIT - stop-words (πŸ₯‰22 Β· ⭐ 160 Β· πŸ’€) - Get list of common stop words in various languages in Python. BSD-3 -- DELTA (πŸ₯‰21 Β· ⭐ 1.6K Β· πŸ’€) - DELTA is a deep learning based natural language and speech.. Apache-2 -- lightseq (πŸ₯‰20 Β· ⭐ 3.1K Β· πŸ’€) - LightSeq: A High Performance Library for Sequence Processing.. Apache-2 -- NLP Architect (πŸ₯‰20 Β· ⭐ 2.9K Β· πŸ’€) - A model library for exploring state-of-the-art deep.. Apache-2 -- anaGo (πŸ₯‰20 Β· ⭐ 1.5K Β· πŸ’€) - Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition,.. MIT -- pyfasttext (πŸ₯‰19 Β· ⭐ 230 Β· πŸ’€) - Yet another Python binding for fastText. ❗️GPL-3.0 +- anaGo (πŸ₯‰21 Β· ⭐ 1.5K Β· πŸ’€) - Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition,.. MIT +- DeepMatcher (πŸ₯‰20 Β· ⭐ 5.1K Β· πŸ’€) - Python package for performing Entity and Text Matching using.. BSD-3 +- lightseq (πŸ₯‰20 Β· ⭐ 3.2K Β· πŸ’€) - LightSeq: A High Performance Library for Sequence Processing.. Apache-2 +- DELTA (πŸ₯‰20 Β· ⭐ 1.6K Β· πŸ’€) - DELTA is a deep learning based natural language and speech.. Apache-2 +- textpipe (πŸ₯‰20 Β· ⭐ 300 Β· πŸ’€) - Textpipe: clean and extract metadata from text. MIT +- pyfasttext (πŸ₯‰20 Β· ⭐ 230 Β· πŸ’€) - Yet another Python binding for fastText. ❗️GPL-3.0 +- fastT5 (πŸ₯‰19 Β· ⭐ 560 Β· πŸ’€) - boost inference speed of T5 models by 5x & reduce the model size.. Apache-2 - numerizer (πŸ₯‰19 Β· ⭐ 210 Β· πŸ’€) - A Python module to convert natural language numerics into ints and.. MIT -- nboost (πŸ₯‰18 Β· ⭐ 670 Β· πŸ’€) - NBoost is a scalable, search-api-boosting platform for deploying.. Apache-2 -- fastT5 (πŸ₯‰18 Β· ⭐ 540 Β· πŸ’€) - boost inference speed of T5 models by 5x & reduce the model size.. Apache-2 +- nboost (πŸ₯‰18 Β· ⭐ 680 Β· πŸ’€) - NBoost is a scalable, search-api-boosting platform for deploying.. Apache-2 - Camphr (πŸ₯‰18 Β· ⭐ 340 Β· πŸ’€) - Camphr - NLP libary for creating pipeline components. Apache-2 spacy -- textpipe (πŸ₯‰18 Β· ⭐ 300 Β· πŸ’€) - Textpipe: clean and extract metadata from text. MIT - NeuroNER (πŸ₯‰17 Β· ⭐ 1.7K Β· πŸ’€) - Named-entity recognition using neural networks. Easy-to-use and.. MIT -- TextBox (πŸ₯‰16 Β· ⭐ 1.1K Β· πŸ’€) - TextBox 2.0 is a text generation library with pre-trained language.. MIT +- Translate (πŸ₯‰16 Β· ⭐ 820 Β· πŸ’€) - Translate - a PyTorch Language Library. BSD-3 - skift (πŸ₯‰16 Β· ⭐ 240 Β· πŸ’€) - scikit-learn wrappers for Python fastText. MIT -- BLINK (πŸ₯‰15 Β· ⭐ 1.1K Β· πŸ’€) - Entity Linker solution. MIT -- Translate (πŸ₯‰15 Β· ⭐ 820 Β· πŸ’€) - Translate - a PyTorch Language Library. BSD-3 +- BLINK (πŸ₯‰15 Β· ⭐ 1.2K Β· πŸ’€) - Entity Linker solution. MIT +- TextBox (πŸ₯‰15 Β· ⭐ 1.1K Β· πŸ’€) - TextBox 2.0 is a text generation library with pre-trained language.. MIT +- Headliner (πŸ₯‰15 Β· ⭐ 230 Β· πŸ’€) - Easy training and deployment of seq2seq models. MIT +- TransferNLP (πŸ₯‰14 Β· ⭐ 290 Β· πŸ’€) - NLP library designed for reproducible experimentation.. MIT - NeuralQA (πŸ₯‰14 Β· ⭐ 230 Β· πŸ’€) - NeuralQA: A Usable Library for Question Answering on Large Datasets.. MIT -- Headliner (πŸ₯‰14 Β· ⭐ 230 Β· πŸ’€) - Easy training and deployment of seq2seq models. MIT -- TransferNLP (πŸ₯‰13 Β· ⭐ 290 Β· πŸ’€) - NLP library designed for reproducible experimentation.. MIT - ONNX-T5 (πŸ₯‰13 Β· ⭐ 250 Β· πŸ’€) - Summarization, translation, sentiment-analysis, text-generation.. Apache-2 -- textvec (πŸ₯‰13 Β· ⭐ 190) - Text vectorization tool to outperform TFIDF for classification tasks. MIT +- textvec (πŸ₯‰13 Β· ⭐ 190 Β· πŸ’€) - Text vectorization tool to outperform TFIDF for classification.. MIT - spacy-dbpedia-spotlight (πŸ₯‰12 Β· ⭐ 100 Β· πŸ’€) - A spaCy wrapper for DBpedia Spotlight. MIT spacy

@@ -2203,503 +2197,503 @@ _Libraries for image & video processing, manipulation, and augmentation as well
Pillow (πŸ₯‡48 Β· ⭐ 12K) - Python Imaging Library (Fork). ❗️PIL -- [GitHub](https://github.com/python-pillow/Pillow) (πŸ‘¨β€πŸ’» 470 Β· πŸ”€ 2.1K Β· πŸ“¦ 1.7M Β· πŸ“‹ 3.1K - 3% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/python-pillow/Pillow) (πŸ‘¨β€πŸ’» 480 Β· πŸ”€ 2.2K Β· πŸ“¦ 1.8M Β· πŸ“‹ 3.2K - 4% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/python-pillow/Pillow ``` -- [PyPi](https://pypi.org/project/Pillow) (πŸ“₯ 99M / month Β· πŸ“¦ 4.2K Β· ⏱️ 01.04.2024): +- [PyPi](https://pypi.org/project/Pillow) (πŸ“₯ 110M / month Β· πŸ“¦ 7.7K Β· ⏱️ 01.07.2024): ``` pip install Pillow ``` -- [Conda](https://anaconda.org/conda-forge/pillow) (πŸ“₯ 40M Β· ⏱️ 03.04.2024): +- [Conda](https://anaconda.org/conda-forge/pillow) (πŸ“₯ 44M Β· ⏱️ 02.07.2024): ``` conda install -c conda-forge pillow ```
-
torchvision (πŸ₯‡42 Β· ⭐ 16K) - Datasets, Transforms and Models specific to Computer Vision. BSD-3 - -- [GitHub](https://github.com/pytorch/vision) (πŸ‘¨β€πŸ’» 600 Β· πŸ”€ 6.9K Β· πŸ“₯ 38K Β· πŸ“¦ 21 Β· πŸ“‹ 3.4K - 29% open Β· ⏱️ 06.06.2024): - - ``` - git clone https://github.com/pytorch/vision - ``` -- [PyPi](https://pypi.org/project/torchvision) (πŸ“₯ 13M / month Β· πŸ“¦ 5K Β· ⏱️ 05.06.2024): - ``` - pip install torchvision - ``` -- [Conda](https://anaconda.org/conda-forge/torchvision) (πŸ“₯ 1.2M Β· ⏱️ 16.05.2024): - ``` - conda install -c conda-forge torchvision - ``` -
-
PyTorch Image Models (πŸ₯‡41 Β· ⭐ 30K) - The largest collection of PyTorch image encoders /.. Apache-2 +
PyTorch Image Models (πŸ₯‡42 Β· ⭐ 31K) - The largest collection of PyTorch image encoders /.. Apache-2 -- [GitHub](https://github.com/huggingface/pytorch-image-models) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 4.6K Β· πŸ“₯ 6.6M Β· πŸ“¦ 30K Β· πŸ“‹ 880 - 6% open Β· ⏱️ 27.05.2024): +- [GitHub](https://github.com/huggingface/pytorch-image-models) (πŸ‘¨β€πŸ’» 150 Β· πŸ”€ 4.7K Β· πŸ“₯ 7M Β· πŸ“¦ 36K Β· πŸ“‹ 900 - 4% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/rwightman/pytorch-image-models ``` -- [PyPi](https://pypi.org/project/timm) (πŸ“₯ 5.1M / month Β· πŸ“¦ 760 Β· ⏱️ 15.05.2024): +- [PyPi](https://pypi.org/project/timm) (πŸ“₯ 5.8M / month Β· πŸ“¦ 900 Β· ⏱️ 23.08.2024): ``` pip install timm ``` -- [Conda](https://anaconda.org/conda-forge/timm) (πŸ“₯ 160K Β· ⏱️ 16.05.2024): +- [Conda](https://anaconda.org/conda-forge/timm) (πŸ“₯ 220K Β· ⏱️ 24.08.2024): ``` conda install -c conda-forge timm ```
-
MMDetection (πŸ₯‡38 Β· ⭐ 28K) - OpenMMLab Detection Toolbox and Benchmark. Apache-2 +
torchvision (πŸ₯‡42 Β· ⭐ 16K) - Datasets, Transforms and Models specific to Computer Vision. BSD-3 -- [GitHub](https://github.com/open-mmlab/mmdetection) (πŸ‘¨β€πŸ’» 480 Β· πŸ”€ 9.2K Β· πŸ“¦ 2.6K Β· πŸ“‹ 8.3K - 19% open Β· ⏱️ 05.02.2024): +- [GitHub](https://github.com/pytorch/vision) (πŸ‘¨β€πŸ’» 610 Β· πŸ”€ 6.9K Β· πŸ“₯ 39K Β· πŸ“¦ 21 Β· πŸ“‹ 3.4K - 29% open Β· ⏱️ 04.09.2024): ``` - git clone https://github.com/open-mmlab/mmdetection + git clone https://github.com/pytorch/vision ``` -- [PyPi](https://pypi.org/project/mmdet) (πŸ“₯ 260K / month Β· πŸ“¦ 64 Β· ⏱️ 05.01.2024): +- [PyPi](https://pypi.org/project/torchvision) (πŸ“₯ 13M / month Β· πŸ“¦ 5.5K Β· ⏱️ 04.09.2024): ``` - pip install mmdet + pip install torchvision + ``` +- [Conda](https://anaconda.org/conda-forge/torchvision) (πŸ“₯ 1.6M Β· ⏱️ 25.08.2024): + ``` + conda install -c conda-forge torchvision ```
-
Albumentations (πŸ₯‡38 Β· ⭐ 14K) - Fast and flexible image augmentation library. Paper about.. MIT +
Albumentations (πŸ₯‡40 Β· ⭐ 14K) - Fast and flexible image augmentation library. Paper about.. MIT -- [GitHub](https://github.com/albumentations-team/albumentations) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 1.6K Β· πŸ“¦ 24K Β· πŸ“‹ 960 - 44% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/albumentations-team/albumentations) (πŸ‘¨β€πŸ’» 150 Β· πŸ”€ 1.6K Β· πŸ“¦ 27K Β· πŸ“‹ 1K - 36% open Β· ⏱️ 02.09.2024): ``` git clone https://github.com/albumentations-team/albumentations ``` -- [PyPi](https://pypi.org/project/albumentations) (πŸ“₯ 2.1M / month Β· πŸ“¦ 510 Β· ⏱️ 28.05.2024): +- [PyPi](https://pypi.org/project/albumentations) (πŸ“₯ 4.5M / month Β· πŸ“¦ 550 Β· ⏱️ 16.08.2024): ``` pip install albumentations ``` -- [Conda](https://anaconda.org/conda-forge/albumentations) (πŸ“₯ 170K Β· ⏱️ 05.03.2024): +- [Conda](https://anaconda.org/conda-forge/albumentations) (πŸ“₯ 190K Β· ⏱️ 20.08.2024): ``` conda install -c conda-forge albumentations ```
MoviePy (πŸ₯‡38 Β· ⭐ 12K) - Video editing with Python. MIT -- [GitHub](https://github.com/Zulko/moviepy) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 1.5K Β· πŸ“¦ 40K Β· πŸ“‹ 1.5K - 28% open Β· ⏱️ 27.05.2024): +- [GitHub](https://github.com/Zulko/moviepy) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 1.5K Β· πŸ“¦ 44K Β· πŸ“‹ 1.5K - 30% open Β· ⏱️ 27.05.2024): ``` git clone https://github.com/Zulko/moviepy ``` -- [PyPi](https://pypi.org/project/moviepy) (πŸ“₯ 1.2M / month Β· πŸ“¦ 820 Β· ⏱️ 15.12.2021): +- [PyPi](https://pypi.org/project/moviepy) (πŸ“₯ 1.3M / month Β· πŸ“¦ 910 Β· ⏱️ 15.12.2021): ``` pip install moviepy ``` -- [Conda](https://anaconda.org/conda-forge/moviepy) (πŸ“₯ 250K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/moviepy) (πŸ“₯ 260K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge moviepy ```
-
Kornia (πŸ₯‡38 Β· ⭐ 9.5K) - Geometric Computer Vision Library for Spatial AI. Apache-2 +
Kornia (πŸ₯‡38 Β· ⭐ 9.8K) - Geometric Computer Vision Library for Spatial AI. Apache-2 -- [GitHub](https://github.com/kornia/kornia) (πŸ‘¨β€πŸ’» 260 Β· πŸ”€ 940 Β· πŸ“₯ 1.1K Β· πŸ“¦ 10K Β· πŸ“‹ 910 - 29% open Β· ⏱️ 28.05.2024): +- [GitHub](https://github.com/kornia/kornia) (πŸ‘¨β€πŸ’» 270 Β· πŸ”€ 960 Β· πŸ“₯ 1.4K Β· πŸ“¦ 11K Β· πŸ“‹ 940 - 30% open Β· ⏱️ 02.09.2024): ``` git clone https://github.com/kornia/kornia ``` -- [PyPi](https://pypi.org/project/kornia) (πŸ“₯ 1.4M / month Β· πŸ“¦ 240 Β· ⏱️ 14.03.2024): +- [PyPi](https://pypi.org/project/kornia) (πŸ“₯ 1.9M / month Β· πŸ“¦ 260 Β· ⏱️ 28.06.2024): ``` pip install kornia ``` -- [Conda](https://anaconda.org/conda-forge/kornia) (πŸ“₯ 130K Β· ⏱️ 20.02.2024): +- [Conda](https://anaconda.org/conda-forge/kornia) (πŸ“₯ 140K Β· ⏱️ 28.06.2024): ``` conda install -c conda-forge kornia ```
-
imageio (πŸ₯‡38 Β· ⭐ 1.4K Β· πŸ“ˆ) - Python library for reading and writing image data. BSD-2 +
imageio (πŸ₯‡38 Β· ⭐ 1.5K) - Python library for reading and writing image data. BSD-2 -- [GitHub](https://github.com/imageio/imageio) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 290 Β· πŸ“₯ 1.1K Β· πŸ“¦ 130K Β· πŸ“‹ 600 - 17% open Β· ⏱️ 03.06.2024): +- [GitHub](https://github.com/imageio/imageio) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 290 Β· πŸ“₯ 1.2K Β· πŸ“¦ 140K Β· πŸ“‹ 600 - 16% open Β· ⏱️ 19.08.2024): ``` git clone https://github.com/imageio/imageio ``` -- [PyPi](https://pypi.org/project/imageio) (πŸ“₯ 22M / month Β· πŸ“¦ 2.2K Β· ⏱️ 22.04.2024): +- [PyPi](https://pypi.org/project/imageio) (πŸ“₯ 26M / month Β· πŸ“¦ 2.4K Β· ⏱️ 19.08.2024): ``` pip install imageio ``` -- [Conda](https://anaconda.org/conda-forge/imageio) (πŸ“₯ 6.4M Β· ⏱️ 22.04.2024): +- [Conda](https://anaconda.org/conda-forge/imageio) (πŸ“₯ 6.8M Β· ⏱️ 19.08.2024): ``` conda install -c conda-forge imageio ```
-
deepface (πŸ₯ˆ37 Β· ⭐ 11K Β· πŸ“ˆ) - A Lightweight Face Recognition and Facial Attribute Analysis (Age,.. MIT +
MMDetection (πŸ₯ˆ37 Β· ⭐ 29K Β· πŸ’€) - OpenMMLab Detection Toolbox and Benchmark. Apache-2 -- [GitHub](https://github.com/serengil/deepface) (πŸ‘¨β€πŸ’» 62 Β· πŸ”€ 1.9K Β· πŸ“¦ 3.3K Β· πŸ“‹ 1K - 0% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/open-mmlab/mmdetection) (πŸ‘¨β€πŸ’» 480 Β· πŸ”€ 9.4K Β· πŸ“¦ 2.9K Β· πŸ“‹ 8.5K - 20% open Β· ⏱️ 05.02.2024): ``` - git clone https://github.com/serengil/deepface + git clone https://github.com/open-mmlab/mmdetection ``` -- [PyPi](https://pypi.org/project/deepface) (πŸ“₯ 66K / month Β· πŸ“¦ 36 Β· ⏱️ 02.05.2024): +- [PyPi](https://pypi.org/project/mmdet) (πŸ“₯ 190K / month Β· πŸ“¦ 81 Β· ⏱️ 05.01.2024): ``` - pip install deepface + pip install mmdet ```
-
InsightFace (πŸ₯ˆ36 Β· ⭐ 22K) - State-of-the-art 2D and 3D Face Analysis Project. MIT +
InsightFace (πŸ₯ˆ37 Β· ⭐ 23K) - State-of-the-art 2D and 3D Face Analysis Project. MIT -- [GitHub](https://github.com/deepinsight/insightface) (πŸ‘¨β€πŸ’» 60 Β· πŸ”€ 5.2K Β· πŸ“₯ 3.4M Β· πŸ“¦ 2.2K Β· πŸ“‹ 2.4K - 44% open Β· ⏱️ 08.05.2024): +- [GitHub](https://github.com/deepinsight/insightface) (πŸ‘¨β€πŸ’» 61 Β· πŸ”€ 5.3K Β· πŸ“₯ 4.5M Β· πŸ“¦ 2.6K Β· πŸ“‹ 2.5K - 44% open Β· ⏱️ 30.08.2024): ``` git clone https://github.com/deepinsight/insightface ``` -- [PyPi](https://pypi.org/project/insightface) (πŸ“₯ 360K / month Β· πŸ“¦ 22 Β· ⏱️ 17.12.2022): +- [PyPi](https://pypi.org/project/insightface) (πŸ“₯ 350K / month Β· πŸ“¦ 29 Β· ⏱️ 17.12.2022): ``` pip install insightface ```
-
opencv-python (πŸ₯ˆ36 Β· ⭐ 4.2K) - Automated CI toolchain to produce precompiled opencv-python,.. MIT +
deepface (πŸ₯ˆ37 Β· ⭐ 12K) - A Lightweight Face Recognition and Facial Attribute Analysis (Age,.. MIT -- [GitHub](https://github.com/opencv/opencv-python) (πŸ‘¨β€πŸ’» 48 Β· πŸ”€ 800 Β· πŸ“¦ 400K Β· πŸ“‹ 780 - 14% open Β· ⏱️ 03.06.2024): +- [GitHub](https://github.com/serengil/deepface) (πŸ‘¨β€πŸ’» 66 Β· πŸ”€ 2K Β· πŸ“¦ 3.9K Β· πŸ“‹ 1.1K - 0% open Β· ⏱️ 03.09.2024): ``` - git clone https://github.com/opencv/opencv-python + git clone https://github.com/serengil/deepface ``` -- [PyPi](https://pypi.org/project/opencv-python) (πŸ“₯ 15M / month Β· πŸ“¦ 9.5K Β· ⏱️ 03.06.2024): +- [PyPi](https://pypi.org/project/deepface) (πŸ“₯ 98K / month Β· πŸ“¦ 42 Β· ⏱️ 17.08.2024): ``` - pip install opencv-python + pip install deepface ```
-
detectron2 (πŸ₯ˆ34 Β· ⭐ 29K) - Detectron2 is a platform for object detection, segmentation.. Apache-2 +
opencv-python (πŸ₯ˆ36 Β· ⭐ 4.4K) - Automated CI toolchain to produce precompiled opencv-python,.. MIT -- [GitHub](https://github.com/facebookresearch/detectron2) (πŸ‘¨β€πŸ’» 270 Β· πŸ”€ 7.3K Β· πŸ“¦ 1.8K Β· πŸ“‹ 3.5K - 13% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/opencv/opencv-python) (πŸ‘¨β€πŸ’» 49 Β· πŸ”€ 830 Β· πŸ“¦ 440K Β· πŸ“‹ 810 - 15% open Β· ⏱️ 24.07.2024): ``` - git clone https://github.com/facebookresearch/detectron2 - ``` -- [PyPi](https://pypi.org/project/detectron2) (πŸ“¦ 11 Β· ⏱️ 06.02.2020): - ``` - pip install detectron2 + git clone https://github.com/opencv/opencv-python ``` -- [Conda](https://anaconda.org/conda-forge/detectron2) (πŸ“₯ 280K Β· ⏱️ 19.05.2024): +- [PyPi](https://pypi.org/project/opencv-python) (πŸ“₯ 17M / month Β· πŸ“¦ 10K Β· ⏱️ 17.06.2024): ``` - conda install -c conda-forge detectron2 + pip install opencv-python ```
-
Wand (πŸ₯ˆ33 Β· ⭐ 1.4K) - The ctypes-based simple ImageMagick binding for Python. MIT +
Wand (πŸ₯ˆ34 Β· ⭐ 1.4K Β· πŸ’€) - The ctypes-based simple ImageMagick binding for Python. MIT -- [GitHub](https://github.com/emcconville/wand) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 200 Β· πŸ“₯ 47K Β· πŸ“¦ 19K Β· πŸ“‹ 420 - 6% open Β· ⏱️ 11.02.2024): +- [GitHub](https://github.com/emcconville/wand) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 200 Β· πŸ“₯ 49K Β· πŸ“¦ 20K Β· πŸ“‹ 430 - 6% open Β· ⏱️ 11.02.2024): ``` git clone https://github.com/emcconville/wand ``` -- [PyPi](https://pypi.org/project/wand) (πŸ“₯ 870K / month Β· πŸ“¦ 240 Β· ⏱️ 03.11.2023): +- [PyPi](https://pypi.org/project/wand) (πŸ“₯ 750K / month Β· πŸ“¦ 250 Β· ⏱️ 03.11.2023): ``` pip install wand ``` -- [Conda](https://anaconda.org/conda-forge/wand) (πŸ“₯ 49K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/wand) (πŸ“₯ 70K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge wand ```
-
imageai (πŸ₯ˆ31 Β· ⭐ 8.5K) - A python library built to empower developers to build applications and.. MIT +
detectron2 (πŸ₯ˆ33 Β· ⭐ 30K) - Detectron2 is a platform for object detection, segmentation.. Apache-2 -- [GitHub](https://github.com/OlafenwaMoses/ImageAI) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 2.2K Β· πŸ“₯ 930K Β· πŸ“¦ 1.6K Β· πŸ“‹ 760 - 40% open Β· ⏱️ 20.02.2024): +- [GitHub](https://github.com/facebookresearch/detectron2) (πŸ‘¨β€πŸ’» 270 Β· πŸ”€ 7.4K Β· πŸ“¦ 2K Β· πŸ“‹ 3.6K - 14% open Β· ⏱️ 22.08.2024): ``` - git clone https://github.com/OlafenwaMoses/ImageAI + git clone https://github.com/facebookresearch/detectron2 ``` -- [PyPi](https://pypi.org/project/imageai) (πŸ“₯ 11K / month Β· πŸ“¦ 19 Β· ⏱️ 02.01.2023): +- [PyPi](https://pypi.org/project/detectron2) (πŸ“¦ 13 Β· ⏱️ 06.02.2020): ``` - pip install imageai + pip install detectron2 ``` -- [Conda](https://anaconda.org/conda-forge/imageai) (πŸ“₯ 7.2K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/detectron2) (πŸ“₯ 400K Β· ⏱️ 26.08.2024): ``` - conda install -c conda-forge imageai + conda install -c conda-forge detectron2 ```
-
PaddleSeg (πŸ₯ˆ31 Β· ⭐ 8.4K) - Easy-to-use image segmentation library with awesome pre-.. Apache-2 +
PaddleSeg (πŸ₯ˆ32 Β· ⭐ 8.5K) - Easy-to-use image segmentation library with awesome pre-.. Apache-2 -- [GitHub](https://github.com/PaddlePaddle/PaddleSeg) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 1.6K Β· πŸ“¦ 1.2K Β· πŸ“‹ 2.1K - 10% open Β· ⏱️ 20.05.2024): +- [GitHub](https://github.com/PaddlePaddle/PaddleSeg) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 1.7K Β· πŸ“¦ 1.3K Β· πŸ“‹ 2.1K - 10% open Β· ⏱️ 23.08.2024): ``` git clone https://github.com/PaddlePaddle/PaddleSeg ``` -- [PyPi](https://pypi.org/project/paddleseg) (πŸ“₯ 2.4K / month Β· πŸ“¦ 7 Β· ⏱️ 30.11.2022): +- [PyPi](https://pypi.org/project/paddleseg) (πŸ“₯ 1.7K / month Β· πŸ“¦ 7 Β· ⏱️ 30.11.2022): ``` pip install paddleseg ```
-
lightly (πŸ₯ˆ31 Β· ⭐ 2.8K) - A python library for self-supervised learning on images. MIT +
lightly (πŸ₯ˆ32 Β· ⭐ 2.9K) - A python library for self-supervised learning on images. MIT -- [GitHub](https://github.com/lightly-ai/lightly) (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 240 Β· πŸ“¦ 260 Β· πŸ“‹ 520 - 19% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/lightly-ai/lightly) (πŸ‘¨β€πŸ’» 42 Β· πŸ”€ 240 Β· πŸ“¦ 310 Β· πŸ“‹ 580 - 15% open Β· ⏱️ 20.08.2024): ``` git clone https://github.com/lightly-ai/lightly ``` -- [PyPi](https://pypi.org/project/lightly) (πŸ“₯ 32K / month Β· πŸ“¦ 13 Β· ⏱️ 29.05.2024): +- [PyPi](https://pypi.org/project/lightly) (πŸ“₯ 32K / month Β· πŸ“¦ 14 Β· ⏱️ 20.08.2024): ``` pip install lightly ```
-
vit-pytorch (πŸ₯ˆ30 Β· ⭐ 18K) - Implementation of Vision Transformer, a simple way to achieve.. MIT +
vit-pytorch (πŸ₯ˆ31 Β· ⭐ 20K) - Implementation of Vision Transformer, a simple way to achieve.. MIT -- [GitHub](https://github.com/lucidrains/vit-pytorch) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 2.8K Β· πŸ“¦ 480 Β· πŸ“‹ 260 - 46% open Β· ⏱️ 11.05.2024): +- [GitHub](https://github.com/lucidrains/vit-pytorch) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 2.9K Β· πŸ“¦ 520 Β· πŸ“‹ 270 - 48% open Β· ⏱️ 28.08.2024): ``` git clone https://github.com/lucidrains/vit-pytorch ``` -- [PyPi](https://pypi.org/project/vit-pytorch) (πŸ“₯ 23K / month Β· πŸ“¦ 11 Β· ⏱️ 11.05.2024): +- [PyPi](https://pypi.org/project/vit-pytorch) (πŸ“₯ 18K / month Β· πŸ“¦ 13 Β· ⏱️ 28.08.2024): ``` pip install vit-pytorch ```
-
sahi (πŸ₯ˆ30 Β· ⭐ 3.7K) - Framework agnostic sliced/tiled inference + interactive ui + error analysis.. MIT +
imageai (πŸ₯ˆ31 Β· ⭐ 8.5K Β· πŸ’€) - A python library built to empower developers to build applications.. MIT -- [GitHub](https://github.com/obss/sahi) (πŸ‘¨β€πŸ’» 47 Β· πŸ”€ 540 Β· πŸ“₯ 25K Β· πŸ“¦ 1.1K Β· ⏱️ 02.06.2024): +- [GitHub](https://github.com/OlafenwaMoses/ImageAI) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 2.2K Β· πŸ“₯ 940K Β· πŸ“¦ 1.7K Β· πŸ“‹ 760 - 41% open Β· ⏱️ 20.02.2024): ``` - git clone https://github.com/obss/sahi + git clone https://github.com/OlafenwaMoses/ImageAI ``` -- [PyPi](https://pypi.org/project/sahi) (πŸ“₯ 120K / month Β· πŸ“¦ 25 Β· ⏱️ 20.05.2024): +- [PyPi](https://pypi.org/project/imageai) (πŸ“₯ 5.9K / month Β· πŸ“¦ 19 Β· ⏱️ 02.01.2023): ``` - pip install sahi + pip install imageai ``` -- [Conda](https://anaconda.org/conda-forge/sahi) (πŸ“₯ 60K Β· ⏱️ 21.05.2024): +- [Conda](https://anaconda.org/conda-forge/imageai) (πŸ“₯ 7.8K Β· ⏱️ 16.06.2023): ``` - conda install -c conda-forge sahi + conda install -c conda-forge imageai ```
-
ImageHash (πŸ₯ˆ30 Β· ⭐ 3K) - A Python Perceptual Image Hashing Module. BSD-2 +
vidgear (πŸ₯ˆ30 Β· ⭐ 3.3K) - A High-performance cross-platform Video Processing Python framework.. Apache-2 -- [GitHub](https://github.com/JohannesBuchner/imagehash) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 320 Β· πŸ“¦ 13K Β· πŸ“‹ 140 - 10% open Β· ⏱️ 26.05.2024): +- [GitHub](https://github.com/abhiTronix/vidgear) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 250 Β· πŸ“₯ 1.6K Β· πŸ“¦ 600 Β· πŸ“‹ 290 - 2% open Β· ⏱️ 22.06.2024): ``` - git clone https://github.com/JohannesBuchner/imagehash - ``` -- [PyPi](https://pypi.org/project/ImageHash) (πŸ“₯ 1.7M / month Β· πŸ“¦ 220 Β· ⏱️ 28.09.2022): - ``` - pip install ImageHash + git clone https://github.com/abhiTronix/vidgear ``` -- [Conda](https://anaconda.org/conda-forge/imagehash) (πŸ“₯ 370K Β· ⏱️ 16.06.2023): +- [PyPi](https://pypi.org/project/vidgear) (πŸ“₯ 22K / month Β· πŸ“¦ 15 Β· ⏱️ 22.06.2024): ``` - conda install -c conda-forge imagehash + pip install vidgear ```
-
doctr (πŸ₯ˆ29 Β· ⭐ 3.2K) - docTR (Document Text Recognition) - a seamless, high-.. Apache-2 +
ImageHash (πŸ₯ˆ30 Β· ⭐ 3.1K) - A Python Perceptual Image Hashing Module. BSD-2 -- [GitHub](https://github.com/mindee/doctr) (πŸ‘¨β€πŸ’» 46 Β· πŸ”€ 380 Β· πŸ“₯ 3M Β· πŸ“‹ 350 - 9% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/JohannesBuchner/imagehash) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 330 Β· πŸ“¦ 14K Β· πŸ“‹ 140 - 10% open Β· ⏱️ 20.06.2024): ``` - git clone https://github.com/mindee/doctr + git clone https://github.com/JohannesBuchner/imagehash ``` -- [PyPi](https://pypi.org/project/python-doctr) (πŸ“₯ 30K / month Β· πŸ“¦ 7 Β· ⏱️ 04.03.2024): +- [PyPi](https://pypi.org/project/ImageHash) (πŸ“₯ 1.4M / month Β· πŸ“¦ 240 Β· ⏱️ 28.09.2022): ``` - pip install python-doctr + pip install ImageHash + ``` +- [Conda](https://anaconda.org/conda-forge/imagehash) (πŸ“₯ 390K Β· ⏱️ 16.06.2023): + ``` + conda install -c conda-forge imagehash ```
-
mahotas (πŸ₯ˆ29 Β· ⭐ 830) - Computer Vision in Python. MIT +
mahotas (πŸ₯ˆ30 Β· ⭐ 840) - Computer Vision in Python. MIT -- [GitHub](https://github.com/luispedro/mahotas) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 150 Β· πŸ“¦ 1.3K Β· πŸ“‹ 89 - 22% open Β· ⏱️ 22.05.2024): +- [GitHub](https://github.com/luispedro/mahotas) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 150 Β· πŸ“¦ 1.3K Β· πŸ“‹ 91 - 23% open Β· ⏱️ 17.07.2024): ``` git clone https://github.com/luispedro/mahotas ``` -- [PyPi](https://pypi.org/project/mahotas) (πŸ“₯ 15K / month Β· πŸ“¦ 60 Β· ⏱️ 17.04.2024): +- [PyPi](https://pypi.org/project/mahotas) (πŸ“₯ 22K / month Β· πŸ“¦ 62 Β· ⏱️ 17.07.2024): ``` pip install mahotas ``` -- [Conda](https://anaconda.org/conda-forge/mahotas) (πŸ“₯ 420K Β· ⏱️ 18.05.2024): +- [Conda](https://anaconda.org/conda-forge/mahotas) (πŸ“₯ 480K Β· ⏱️ 18.07.2024): ``` conda install -c conda-forge mahotas ```
-
Face Alignment (πŸ₯‰28 Β· ⭐ 6.9K Β· πŸ’€) - 2D and 3D Face alignment library build using pytorch. BSD-3 +
sahi (πŸ₯‰29 Β· ⭐ 3.9K) - Framework agnostic sliced/tiled inference + interactive ui + error analysis.. MIT -- [GitHub](https://github.com/1adrianb/face-alignment) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 1.3K Β· πŸ“¦ 21 Β· πŸ“‹ 320 - 24% open Β· ⏱️ 16.08.2023): +- [GitHub](https://github.com/obss/sahi) (πŸ‘¨β€πŸ’» 48 Β· πŸ”€ 570 Β· πŸ“₯ 27K Β· πŸ“¦ 1.3K Β· ⏱️ 27.08.2024): ``` - git clone https://github.com/1adrianb/face-alignment + git clone https://github.com/obss/sahi ``` -- [PyPi](https://pypi.org/project/face-alignment) (πŸ“₯ 70K / month Β· πŸ“¦ 9 Β· ⏱️ 17.08.2023): +- [PyPi](https://pypi.org/project/sahi) (πŸ“₯ 190K / month Β· πŸ“¦ 26 Β· ⏱️ 10.07.2024): ``` - pip install face-alignment + pip install sahi + ``` +- [Conda](https://anaconda.org/conda-forge/sahi) (πŸ“₯ 70K Β· ⏱️ 24.07.2024): + ``` + conda install -c conda-forge sahi ```
-
facenet-pytorch (πŸ₯‰28 Β· ⭐ 4.2K) - Pretrained Pytorch face detection (MTCNN) and facial.. MIT +
doctr (πŸ₯‰29 Β· ⭐ 3.5K) - docTR (Document Text Recognition) - a seamless, high-.. Apache-2 -- [GitHub](https://github.com/timesler/facenet-pytorch) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 920 Β· πŸ“₯ 1M Β· πŸ“¦ 1.8K Β· πŸ“‹ 180 - 39% open Β· ⏱️ 05.04.2024): +- [GitHub](https://github.com/mindee/doctr) (πŸ‘¨β€πŸ’» 50 Β· πŸ”€ 410 Β· πŸ“₯ 3.6M Β· πŸ“‹ 360 - 10% open Β· ⏱️ 29.08.2024): ``` - git clone https://github.com/timesler/facenet-pytorch + git clone https://github.com/mindee/doctr ``` -- [PyPi](https://pypi.org/project/facenet-pytorch) (πŸ“₯ 63K / month Β· πŸ“¦ 30 Β· ⏱️ 29.04.2024): +- [PyPi](https://pypi.org/project/python-doctr) (πŸ“₯ 53K / month Β· πŸ“¦ 12 Β· ⏱️ 08.08.2024): ``` - pip install facenet-pytorch + pip install python-doctr ```
-
PaddleDetection (πŸ₯‰27 Β· ⭐ 12K) - Object Detection toolkit based on PaddlePaddle. It.. Apache-2 +
Face Alignment (πŸ₯‰28 Β· ⭐ 7K) - 2D and 3D Face alignment library build using pytorch. BSD-3 -- [GitHub](https://github.com/PaddlePaddle/PaddleDetection) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 2.8K Β· πŸ“‹ 5.3K - 22% open Β· ⏱️ 22.05.2024): +- [GitHub](https://github.com/1adrianb/face-alignment) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 1.3K Β· πŸ“¦ 21 Β· πŸ“‹ 320 - 24% open Β· ⏱️ 30.08.2024): ``` - git clone https://github.com/PaddlePaddle/PaddleDetection + git clone https://github.com/1adrianb/face-alignment ``` -- [PyPi](https://pypi.org/project/paddledet) (πŸ“₯ 670 / month Β· πŸ“¦ 2 Β· ⏱️ 19.09.2022): +- [PyPi](https://pypi.org/project/face-alignment) (πŸ“₯ 84K / month Β· πŸ“¦ 10 Β· ⏱️ 17.08.2023): ``` - pip install paddledet + pip install face-alignment ```
-
vidgear (πŸ₯‰27 Β· ⭐ 3.2K Β· πŸ’€) - A High-performance cross-platform Video Processing Python.. Apache-2 +
facenet-pytorch (πŸ₯‰28 Β· ⭐ 4.4K) - Pretrained Pytorch face detection (MTCNN) and facial.. MIT -- [GitHub](https://github.com/abhiTronix/vidgear) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 240 Β· πŸ“₯ 1.4K Β· πŸ“¦ 560 Β· πŸ“‹ 280 - 3% open Β· ⏱️ 10.09.2023): +- [GitHub](https://github.com/timesler/facenet-pytorch) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 940 Β· πŸ“₯ 1.2M Β· πŸ“¦ 2.2K Β· πŸ“‹ 180 - 40% open Β· ⏱️ 02.08.2024): ``` - git clone https://github.com/abhiTronix/vidgear + git clone https://github.com/timesler/facenet-pytorch ``` -- [PyPi](https://pypi.org/project/vidgear) (πŸ“₯ 16K / month Β· πŸ“¦ 13 Β· ⏱️ 10.09.2023): +- [PyPi](https://pypi.org/project/facenet-pytorch) (πŸ“₯ 64K / month Β· πŸ“¦ 51 Β· ⏱️ 29.04.2024): ``` - pip install vidgear + pip install facenet-pytorch ```
-
CellProfiler (πŸ₯‰27 Β· ⭐ 870) - An open-source application for biological image analysis. BSD-3 +
CellProfiler (πŸ₯‰28 Β· ⭐ 890) - An open-source application for biological image analysis. BSD-3 -- [GitHub](https://github.com/CellProfiler/CellProfiler) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 370 Β· πŸ“₯ 7K Β· πŸ“¦ 20 Β· πŸ“‹ 3.3K - 9% open Β· ⏱️ 01.05.2024): +- [GitHub](https://github.com/CellProfiler/CellProfiler) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 370 Β· πŸ“₯ 7.6K Β· πŸ“¦ 22 Β· πŸ“‹ 3.3K - 9% open Β· ⏱️ 30.08.2024): ``` git clone https://github.com/CellProfiler/CellProfiler ``` -- [PyPi](https://pypi.org/project/cellprofiler) (πŸ“₯ 450 / month Β· πŸ“¦ 2 Β· ⏱️ 14.08.2023): +- [PyPi](https://pypi.org/project/cellprofiler) (πŸ“₯ 650 / month Β· πŸ“¦ 2 Β· ⏱️ 29.07.2024): ``` pip install cellprofiler ```
-
pytorchvideo (πŸ₯‰26 Β· ⭐ 3.2K) - A deep learning library for video understanding research. Apache-2 +
PaddleDetection (πŸ₯‰27 Β· ⭐ 13K) - Object Detection toolkit based on PaddlePaddle. It.. Apache-2 -- [GitHub](https://github.com/facebookresearch/pytorchvideo) (πŸ‘¨β€πŸ’» 55 Β· πŸ”€ 390 Β· πŸ“‹ 200 - 50% open Β· ⏱️ 03.03.2024): +- [GitHub](https://github.com/PaddlePaddle/PaddleDetection) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 2.8K Β· πŸ“‹ 5.4K - 22% open Β· ⏱️ 11.07.2024): ``` - git clone https://github.com/facebookresearch/pytorchvideo + git clone https://github.com/PaddlePaddle/PaddleDetection ``` -- [PyPi](https://pypi.org/project/pytorchvideo) (πŸ“₯ 67K / month Β· πŸ“¦ 23 Β· ⏱️ 20.01.2022): +- [PyPi](https://pypi.org/project/paddledet) (πŸ“₯ 470 / month Β· πŸ“¦ 2 Β· ⏱️ 19.09.2022): ``` - pip install pytorchvideo + pip install paddledet ```
-
Norfair (πŸ₯‰26 Β· ⭐ 2.3K) - Lightweight Python library for adding real-time multi-object tracking.. BSD-3 +
Norfair (πŸ₯‰26 Β· ⭐ 2.4K) - Lightweight Python library for adding real-time multi-object tracking.. BSD-3 -- [GitHub](https://github.com/tryolabs/norfair) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 230 Β· πŸ“₯ 310 Β· πŸ“¦ 190 Β· πŸ“‹ 160 - 10% open Β· ⏱️ 30.01.2024): +- [GitHub](https://github.com/tryolabs/norfair) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 240 Β· πŸ“₯ 320 Β· πŸ“¦ 220 Β· πŸ“‹ 170 - 14% open Β· ⏱️ 27.07.2024): ``` git clone https://github.com/tryolabs/norfair ``` -- [PyPi](https://pypi.org/project/norfair) (πŸ“₯ 18K / month Β· πŸ“¦ 4 Β· ⏱️ 30.05.2022): +- [PyPi](https://pypi.org/project/norfair) (πŸ“₯ 20K / month Β· πŸ“¦ 7 Β· ⏱️ 30.05.2022): ``` pip install norfair ```
-
ffcv (πŸ₯‰25 Β· ⭐ 2.8K) - FFCV: Fast Forward Computer Vision (and other ML workloads!). Apache-2 +
pytorchvideo (πŸ₯‰25 Β· ⭐ 3.3K) - A deep learning library for video understanding research. Apache-2 -- [GitHub](https://github.com/libffcv/ffcv) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 170 Β· πŸ“¦ 45 Β· πŸ“‹ 270 - 34% open Β· ⏱️ 06.05.2024): +- [GitHub](https://github.com/facebookresearch/pytorchvideo) (πŸ‘¨β€πŸ’» 56 Β· πŸ”€ 400 Β· πŸ“‹ 210 - 50% open Β· ⏱️ 13.08.2024): ``` - git clone https://github.com/libffcv/ffcv + git clone https://github.com/facebookresearch/pytorchvideo ``` -- [PyPi](https://pypi.org/project/ffcv) (πŸ“₯ 1.2K / month Β· πŸ“¦ 1 Β· ⏱️ 28.01.2022): +- [PyPi](https://pypi.org/project/pytorchvideo) (πŸ“₯ 16K / month Β· πŸ“¦ 24 Β· ⏱️ 20.01.2022): ``` - pip install ffcv + pip install pytorchvideo ```
-
pyvips (πŸ₯‰25 Β· ⭐ 600) - python binding for libvips using cffi. MIT +
pyvips (πŸ₯‰25 Β· ⭐ 630) - python binding for libvips using cffi. MIT -- [GitHub](https://github.com/libvips/pyvips) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 50 Β· πŸ“¦ 730 Β· πŸ“‹ 420 - 42% open Β· ⏱️ 28.04.2024): +- [GitHub](https://github.com/libvips/pyvips) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 49 Β· πŸ“¦ 790 Β· πŸ“‹ 440 - 42% open Β· ⏱️ 26.08.2024): ``` git clone https://github.com/libvips/pyvips ``` -- [PyPi](https://pypi.org/project/pyvips) (πŸ“₯ 46K / month Β· πŸ“¦ 73 Β· ⏱️ 28.04.2024): +- [PyPi](https://pypi.org/project/pyvips) (πŸ“₯ 53K / month Β· πŸ“¦ 77 Β· ⏱️ 28.04.2024): ``` pip install pyvips ``` -- [Conda](https://anaconda.org/conda-forge/pyvips) (πŸ“₯ 87K Β· ⏱️ 28.04.2024): +- [Conda](https://anaconda.org/conda-forge/pyvips) (πŸ“₯ 120K Β· ⏱️ 28.04.2024): ``` conda install -c conda-forge pyvips ```
-
MMF (πŸ₯‰24 Β· ⭐ 5.4K) - A modular framework for vision & language multimodal research from.. BSD-3 +
MMF (πŸ₯‰24 Β· ⭐ 5.5K) - A modular framework for vision & language multimodal research from.. BSD-3 -- [GitHub](https://github.com/facebookresearch/mmf) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 920 Β· πŸ“¦ 17 Β· πŸ“‹ 690 - 21% open Β· ⏱️ 25.05.2024): +- [GitHub](https://github.com/facebookresearch/mmf) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 920 Β· πŸ“¦ 20 Β· πŸ“‹ 690 - 21% open Β· ⏱️ 25.05.2024): ``` git clone https://github.com/facebookresearch/mmf ``` -- [PyPi](https://pypi.org/project/mmf) (πŸ“₯ 200 / month Β· πŸ“¦ 1 Β· ⏱️ 12.06.2020): +- [PyPi](https://pypi.org/project/mmf) (πŸ“₯ 410 / month Β· πŸ“¦ 1 Β· ⏱️ 12.06.2020): ``` pip install mmf ```
-
kubric (πŸ₯‰24 Β· ⭐ 2.2K) - A data generation pipeline for creating semi-realistic synthetic.. Apache-2 +
segmentation_models (πŸ₯‰24 Β· ⭐ 4.7K) - Segmentation models with pretrained backbones. Keras.. MIT -- [GitHub](https://github.com/google-research/kubric) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 210 Β· πŸ“¦ 4 Β· πŸ“‹ 190 - 32% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/qubvel/segmentation_models) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 1K Β· πŸ“‹ 530 - 48% open Β· ⏱️ 21.08.2024): ``` - git clone https://github.com/google-research/kubric + git clone https://github.com/qubvel/segmentation_models ``` -- [PyPi](https://pypi.org/project/kubric-nightly) (πŸ“₯ 2.3K / month Β· ⏱️ 27.12.2023): +- [PyPi](https://pypi.org/project/segmentation_models) (πŸ“₯ 31K / month Β· πŸ“¦ 28 Β· ⏱️ 10.01.2020): ``` - pip install kubric-nightly + pip install segmentation_models ```
-
tensorflow-graphics (πŸ₯‰23 Β· ⭐ 2.7K) - TensorFlow Graphics: Differentiable Graphics Layers.. Apache-2 +
ffcv (πŸ₯‰24 Β· ⭐ 2.8K) - FFCV: Fast Forward Computer Vision (and other ML workloads!). Apache-2 -- [GitHub](https://github.com/tensorflow/graphics) (πŸ‘¨β€πŸ’» 39 Β· πŸ”€ 360 Β· πŸ“‹ 240 - 61% open Β· ⏱️ 13.03.2024): +- [GitHub](https://github.com/libffcv/ffcv) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 170 Β· πŸ“¦ 53 Β· πŸ“‹ 280 - 36% open Β· ⏱️ 06.05.2024): ``` - git clone https://github.com/tensorflow/graphics + git clone https://github.com/libffcv/ffcv ``` -- [PyPi](https://pypi.org/project/tensorflow-graphics) (πŸ“₯ 37K / month Β· πŸ“¦ 11 Β· ⏱️ 03.12.2021): +- [PyPi](https://pypi.org/project/ffcv) (πŸ“₯ 1.2K / month Β· πŸ“¦ 1 Β· ⏱️ 28.01.2022): ``` - pip install tensorflow-graphics + pip install ffcv ```
-
PySlowFast (πŸ₯‰21 Β· ⭐ 6.3K Β· πŸ’€) - PySlowFast: video understanding codebase from FAIR for.. Apache-2 +
tensorflow-graphics (πŸ₯‰24 Β· ⭐ 2.7K) - TensorFlow Graphics: Differentiable Graphics Layers.. Apache-2 -- [GitHub](https://github.com/facebookresearch/SlowFast) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 1.2K Β· πŸ“¦ 16 Β· πŸ“‹ 680 - 57% open Β· ⏱️ 19.10.2023): +- [GitHub](https://github.com/tensorflow/graphics) (πŸ‘¨β€πŸ’» 39 Β· πŸ”€ 360 Β· πŸ“‹ 240 - 60% open Β· ⏱️ 01.08.2024): ``` - git clone https://github.com/facebookresearch/SlowFast + git clone https://github.com/tensorflow/graphics ``` -- [PyPi](https://pypi.org/project/pyslowfast) (πŸ“₯ 24 / month Β· ⏱️ 15.01.2020): +- [PyPi](https://pypi.org/project/tensorflow-graphics) (πŸ“₯ 13K / month Β· πŸ“¦ 11 Β· ⏱️ 03.12.2021): ``` - pip install pyslowfast + pip install tensorflow-graphics ```
-
vissl (πŸ₯‰21 Β· ⭐ 3.2K) - VISSL is FAIRs library of extensible, modular and scalable components.. MIT +
vissl (πŸ₯‰22 Β· ⭐ 3.2K) - VISSL is FAIRs library of extensible, modular and scalable components.. MIT -- [GitHub](https://github.com/facebookresearch/vissl) (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 330 Β· πŸ“¦ 40 Β· πŸ“‹ 190 - 43% open Β· ⏱️ 03.03.2024): +- [GitHub](https://github.com/facebookresearch/vissl) (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 330 Β· πŸ“¦ 48 Β· πŸ“‹ 190 - 43% open Β· ⏱️ 03.03.2024): ``` git clone https://github.com/facebookresearch/vissl ``` -- [PyPi](https://pypi.org/project/vissl) (πŸ“₯ 140 / month Β· πŸ“¦ 1 Β· ⏱️ 02.11.2021): +- [PyPi](https://pypi.org/project/vissl) (πŸ“₯ 150 / month Β· πŸ“¦ 1 Β· ⏱️ 02.11.2021): ``` pip install vissl ```
-
DEβ«ΆTR (πŸ₯‰20 Β· ⭐ 13K) - End-to-End Object Detection with Transformers. Apache-2 +
PySlowFast (πŸ₯‰21 Β· ⭐ 6.5K) - PySlowFast: video understanding codebase from FAIR for.. Apache-2 -- [GitHub](https://github.com/facebookresearch/detr) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 2.3K Β· πŸ“¦ 21 Β· πŸ“‹ 540 - 47% open Β· ⏱️ 12.03.2024): +- [GitHub](https://github.com/facebookresearch/SlowFast) (πŸ‘¨β€πŸ’» 33 Β· πŸ”€ 1.2K Β· πŸ“¦ 17 Β· πŸ“‹ 680 - 58% open Β· ⏱️ 13.08.2024): ``` - git clone https://github.com/facebookresearch/detr + git clone https://github.com/facebookresearch/SlowFast + ``` +- [PyPi](https://pypi.org/project/pyslowfast) (πŸ“₯ 49 / month Β· ⏱️ 15.01.2020): + ``` + pip install pyslowfast ```
-
pycls (πŸ₯‰20 Β· ⭐ 2.1K Β· πŸ’€) - Codebase for Image Classification Research, written in PyTorch. MIT +
kubric (πŸ₯‰21 Β· ⭐ 2.3K) - A data generation pipeline for creating semi-realistic synthetic.. Apache-2 -- [GitHub](https://github.com/facebookresearch/pycls) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 240 Β· πŸ“¦ 18 Β· πŸ“‹ 83 - 32% open Β· ⏱️ 26.08.2023): +- [GitHub](https://github.com/google-research/kubric) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 220 Β· πŸ“¦ 6 Β· πŸ“‹ 190 - 33% open Β· ⏱️ 27.06.2024): ``` - git clone https://github.com/facebookresearch/pycls + git clone https://github.com/google-research/kubric + ``` +- [PyPi](https://pypi.org/project/kubric-nightly) (πŸ“₯ 4.5K / month Β· ⏱️ 27.12.2023): + ``` + pip install kubric-nightly ``` -- [PyPi](https://pypi.org/project/pycls) (πŸ“₯ 1.3K / month Β· ⏱️ 05.09.2020): +
+
DEβ«ΆTR (πŸ₯‰20 Β· ⭐ 13K) - End-to-End Object Detection with Transformers. Apache-2 + +- [GitHub](https://github.com/facebookresearch/detr) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 2.4K Β· πŸ“¦ 21 Β· πŸ“‹ 540 - 47% open Β· ⏱️ 12.03.2024): + ``` - pip install pycls + git clone https://github.com/facebookresearch/detr ```
-
scenic (πŸ₯‰18 Β· ⭐ 3.1K) - Scenic: A Jax Library for Computer Vision Research and Beyond. Apache-2 +
scenic (πŸ₯‰18 Β· ⭐ 3.2K) - Scenic: A Jax Library for Computer Vision Research and Beyond. Apache-2 -- [GitHub](https://github.com/google-research/scenic) (πŸ‘¨β€πŸ’» 81 Β· πŸ”€ 410 Β· πŸ“‹ 260 - 56% open Β· ⏱️ 22.05.2024): +- [GitHub](https://github.com/google-research/scenic) (πŸ‘¨β€πŸ’» 84 Β· πŸ”€ 420 Β· πŸ“‹ 270 - 55% open Β· ⏱️ 28.08.2024): ``` git clone https://github.com/google-research/scenic @@ -2707,31 +2701,31 @@ _Libraries for image & video processing, manipulation, and augmentation as well
Show 26 hidden projects... -- scikit-image (πŸ₯‡42 Β· ⭐ 5.9K) - Image processing in Python. ❗Unlicensed +- scikit-image (πŸ₯‡42 Β· ⭐ 6K) - Image processing in Python. ❗Unlicensed - imgaug (πŸ₯ˆ37 Β· ⭐ 14K Β· πŸ’€) - Image augmentation for machine learning experiments. MIT -- glfw (πŸ₯ˆ37 Β· ⭐ 12K) - A multi-platform library for OpenGL, OpenGL ES, Vulkan, window and input. ❗️Zlib -- Face Recognition (πŸ₯ˆ33 Β· ⭐ 52K Β· πŸ’€) - The worlds simplest facial recognition api for Python.. MIT -- PyTorch3D (πŸ₯ˆ33 Β· ⭐ 8.4K) - PyTorch3D is FAIRs library of reusable components for.. ❗Unlicensed +- Face Recognition (πŸ₯ˆ35 Β· ⭐ 53K Β· πŸ’€) - The worlds simplest facial recognition api for Python.. MIT +- glfw (πŸ₯ˆ35 Β· ⭐ 13K) - A multi-platform library for OpenGL, OpenGL ES, Vulkan, window and input. ❗️Zlib +- PyTorch3D (πŸ₯ˆ33 Β· ⭐ 8.6K) - PyTorch3D is FAIRs library of reusable components for.. ❗Unlicensed - imutils (πŸ₯ˆ31 Β· ⭐ 4.5K Β· πŸ’€) - A series of convenience functions to make basic image processing.. MIT -- GluonCV (πŸ₯ˆ29 Β· ⭐ 5.8K Β· πŸ’€) - Gluon CV Toolkit. Apache-2 -- mtcnn (πŸ₯‰28 Β· ⭐ 2.1K Β· πŸ’€) - MTCNN face detection implementation for TensorFlow, as a PIP.. MIT -- layout-parser (πŸ₯‰27 Β· ⭐ 4.6K Β· πŸ’€) - A Unified Toolkit for Deep Learning Based Document Image.. Apache-2 +- GluonCV (πŸ₯‰29 Β· ⭐ 5.8K Β· πŸ’€) - Gluon CV Toolkit. Apache-2 +- layout-parser (πŸ₯‰28 Β· ⭐ 4.8K Β· πŸ’€) - A Unified Toolkit for Deep Learning Based Document Image.. Apache-2 +- mtcnn (πŸ₯‰27 Β· ⭐ 2.2K Β· πŸ’€) - MTCNN face detection implementation for TensorFlow, as a PIP.. MIT +- Pillow-SIMD (πŸ₯‰27 Β· ⭐ 2.1K) - The friendly PIL fork. ❗️PIL - chainercv (πŸ₯‰27 Β· ⭐ 1.5K Β· πŸ’€) - ChainerCV: a Library for Deep Learning in Computer Vision. MIT -- Augmentor (πŸ₯‰26 Β· ⭐ 5K Β· πŸ’€) - Image augmentation library in Python for machine learning. MIT -- Image Deduplicator (πŸ₯‰25 Β· ⭐ 5K Β· πŸ’€) - Finding duplicate images made easy!. Apache-2 -- Pillow-SIMD (πŸ₯‰25 Β· ⭐ 2.1K Β· πŸ’€) - The friendly PIL fork. ❗️PIL -- segmentation_models (πŸ₯‰24 Β· ⭐ 4.6K Β· πŸ’€) - Segmentation models with pretrained backbones. Keras.. MIT -- Image Super-Resolution (πŸ₯‰23 Β· ⭐ 4.5K Β· πŸ’€) - Super-scale your images and run experiments with.. Apache-2 +- Image Deduplicator (πŸ₯‰25 Β· ⭐ 5.1K Β· πŸ’€) - Finding duplicate images made easy!. Apache-2 +- Augmentor (πŸ₯‰25 Β· ⭐ 5.1K Β· πŸ’€) - Image augmentation library in Python for machine learning. MIT - Luminoth (πŸ₯‰23 Β· ⭐ 2.4K Β· πŸ’€) - Deep Learning toolkit for Computer Vision. BSD-3 - deep-daze (πŸ₯‰22 Β· ⭐ 4.4K Β· πŸ’€) - Simple command line tool for text to image generation using.. MIT +- Classy Vision (πŸ₯‰22 Β· ⭐ 1.6K Β· πŸ’€) - An end-to-end PyTorch framework for image and video.. MIT - icevision (πŸ₯‰22 Β· ⭐ 840 Β· πŸ’€) - An Agnostic Computer Vision Framework - Pluggable to any.. Apache-2 -- Classy Vision (πŸ₯‰21 Β· ⭐ 1.6K Β· πŸ’€) - An end-to-end PyTorch framework for image and video.. MIT +- Image Super-Resolution (πŸ₯‰21 Β· ⭐ 4.6K Β· πŸ’€) - Super-scale your images and run experiments with.. Apache-2 +- detecto (πŸ₯‰21 Β· ⭐ 610 Β· πŸ’€) - Build fully-functioning computer vision models with PyTorch. MIT +- image-match (πŸ₯‰20 Β· ⭐ 2.9K Β· πŸ’€) - Quickly search over billions of images. Apache-2 +- pycls (πŸ₯‰20 Β· ⭐ 2.1K Β· πŸ’€) - Codebase for Image Classification Research, written in PyTorch. MIT - nude.py (πŸ₯‰20 Β· ⭐ 920 Β· πŸ’€) - Nudity detection with Python. MIT -- detecto (πŸ₯‰20 Β· ⭐ 610 Β· πŸ’€) - Build fully-functioning computer vision models with PyTorch. MIT -- image-match (πŸ₯‰19 Β· ⭐ 2.9K Β· πŸ’€) - Quickly search over billions of images. Apache-2 -- solt (πŸ₯‰18 Β· ⭐ 260 Β· πŸ’€) - Streaming over lightweight data transformations. MIT -- Caer (πŸ₯‰17 Β· ⭐ 750 Β· πŸ’€) - A lightweight Computer Vision library. Scale your models, not boilerplate. MIT -- Torch Points 3D (πŸ₯‰16 Β· ⭐ 200 Β· πŸ’€) - Pytorch framework for doing deep learning on point.. BSD-3 +- solt (πŸ₯‰20 Β· ⭐ 260) - Streaming over lightweight data transformations. MIT +- Caer (πŸ₯‰17 Β· ⭐ 760 Β· πŸ’€) - A lightweight Computer Vision library. Scale your models, not boilerplate. MIT +- Torch Points 3D (πŸ₯‰16 Β· ⭐ 210 Β· πŸ’€) - Pytorch framework for doing deep learning on point.. BSD-3 - HugsVision (πŸ₯‰15 Β· ⭐ 190 Β· πŸ’€) - HugsVision is a easy to use huggingface wrapper for state-of-.. MIT huggingface

@@ -2742,231 +2736,219 @@ _Libraries for image & video processing, manipulation, and augmentation as well _Libraries for graph processing, clustering, embedding, and machine learning tasks._ -
networkx (πŸ₯‡44 Β· ⭐ 14K) - Network Analysis in Python. BSD-3 +
networkx (πŸ₯‡44 Β· ⭐ 15K) - Network Analysis in Python. BSD-3 -- [GitHub](https://github.com/networkx/networkx) (πŸ‘¨β€πŸ’» 720 Β· πŸ”€ 3.2K Β· πŸ“₯ 71 Β· πŸ“¦ 260K Β· πŸ“‹ 3.3K - 10% open Β· ⏱️ 04.06.2024): +- [GitHub](https://github.com/networkx/networkx) (πŸ‘¨β€πŸ’» 740 Β· πŸ”€ 3.2K Β· πŸ“₯ 73 Β· πŸ“¦ 290K Β· πŸ“‹ 3.4K - 10% open Β· ⏱️ 02.09.2024): ``` git clone https://github.com/networkx/networkx ``` -- [PyPi](https://pypi.org/project/networkx) (πŸ“₯ 55M / month Β· πŸ“¦ 8.5K Β· ⏱️ 06.04.2024): +- [PyPi](https://pypi.org/project/networkx) (πŸ“₯ 64M / month Β· πŸ“¦ 9.3K Β· ⏱️ 06.04.2024): ``` pip install networkx ``` -- [Conda](https://anaconda.org/conda-forge/networkx) (πŸ“₯ 16M Β· ⏱️ 08.04.2024): +- [Conda](https://anaconda.org/conda-forge/networkx) (πŸ“₯ 17M Β· ⏱️ 08.04.2024): ``` conda install -c conda-forge networkx ```
-
PyTorch Geometric (πŸ₯‡38 Β· ⭐ 20K) - Graph Neural Network Library for PyTorch. MIT +
PyTorch Geometric (πŸ₯‡40 Β· ⭐ 21K) - Graph Neural Network Library for PyTorch. MIT -- [GitHub](https://github.com/pyg-team/pytorch_geometric) (πŸ‘¨β€πŸ’» 500 Β· πŸ”€ 3.6K Β· πŸ“‹ 3.6K - 27% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/pyg-team/pytorch_geometric) (πŸ‘¨β€πŸ’» 520 Β· πŸ”€ 3.6K Β· πŸ“¦ 6.4K Β· πŸ“‹ 3.7K - 27% open Β· ⏱️ 03.09.2024): ``` git clone https://github.com/pyg-team/pytorch_geometric ``` -- [PyPi](https://pypi.org/project/torch-geometric) (πŸ“₯ 330K / month Β· πŸ“¦ 250 Β· ⏱️ 19.04.2024): +- [PyPi](https://pypi.org/project/torch-geometric) (πŸ“₯ 390K / month Β· πŸ“¦ 320 Β· ⏱️ 19.04.2024): ``` pip install torch-geometric ``` -- [Conda](https://anaconda.org/conda-forge/pytorch_geometric) (πŸ“₯ 43K Β· ⏱️ 04.05.2024): +- [Conda](https://anaconda.org/conda-forge/pytorch_geometric) (πŸ“₯ 79K Β· ⏱️ 16.08.2024): ``` conda install -c conda-forge pytorch_geometric ```
-
dgl (πŸ₯‡38 Β· ⭐ 13K) - Python package built to ease deep learning on graph, on top of existing DL.. Apache-2 +
dgl (πŸ₯‡39 Β· ⭐ 13K) - Python package built to ease deep learning on graph, on top of existing DL.. Apache-2 -- [GitHub](https://github.com/dmlc/dgl) (πŸ‘¨β€πŸ’» 290 Β· πŸ”€ 3K Β· πŸ“¦ 250 Β· πŸ“‹ 2.8K - 18% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/dmlc/dgl) (πŸ‘¨β€πŸ’» 300 Β· πŸ”€ 3K Β· πŸ“¦ 280 Β· πŸ“‹ 2.9K - 18% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/dmlc/dgl ``` -- [PyPi](https://pypi.org/project/dgl) (πŸ“₯ 110K / month Β· πŸ“¦ 130 Β· ⏱️ 13.05.2024): +- [PyPi](https://pypi.org/project/dgl) (πŸ“₯ 110K / month Β· πŸ“¦ 150 Β· ⏱️ 13.05.2024): ``` pip install dgl ```
-
Spektral (πŸ₯ˆ29 Β· ⭐ 2.3K) - Graph Neural Networks with Keras and Tensorflow 2. MIT - -- [GitHub](https://github.com/danielegrattarola/spektral) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 340 Β· πŸ“¦ 300 Β· πŸ“‹ 280 - 24% open Β· ⏱️ 21.01.2024): - - ``` - git clone https://github.com/danielegrattarola/spektral - ``` -- [PyPi](https://pypi.org/project/spektral) (πŸ“₯ 9.8K / month Β· πŸ“¦ 7 Β· ⏱️ 21.01.2024): - ``` - pip install spektral - ``` -
-
pygraphistry (πŸ₯ˆ29 Β· ⭐ 2.1K Β· πŸ“ˆ) - PyGraphistry is a Python library to quickly load,.. BSD-3 +
pygraphistry (πŸ₯ˆ30 Β· ⭐ 2.1K) - PyGraphistry is a Python library to quickly load, shape,.. BSD-3 -- [GitHub](https://github.com/graphistry/pygraphistry) (πŸ‘¨β€πŸ’» 42 Β· πŸ”€ 200 Β· πŸ“¦ 110 Β· πŸ“‹ 320 - 51% open Β· ⏱️ 30.04.2024): +- [GitHub](https://github.com/graphistry/pygraphistry) (πŸ‘¨β€πŸ’» 44 Β· πŸ”€ 210 Β· πŸ“¦ 120 Β· πŸ“‹ 330 - 51% open Β· ⏱️ 03.08.2024): ``` git clone https://github.com/graphistry/pygraphistry ``` -- [PyPi](https://pypi.org/project/graphistry) (πŸ“₯ 3.8K / month Β· πŸ“¦ 6 Β· ⏱️ 30.04.2024): +- [PyPi](https://pypi.org/project/graphistry) (πŸ“₯ 3.9K / month Β· πŸ“¦ 6 Β· ⏱️ 03.08.2024): ``` pip install graphistry ```
-
AmpliGraph (πŸ₯ˆ28 Β· ⭐ 2.1K) - Python library for Representation Learning on Knowledge.. Apache-2 - -- [GitHub](https://github.com/Accenture/AmpliGraph) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 250 Β· πŸ“¦ 50 Β· πŸ“‹ 220 - 15% open Β· ⏱️ 28.02.2024): - - ``` - git clone https://github.com/Accenture/AmpliGraph - ``` -- [PyPi](https://pypi.org/project/ampligraph) (πŸ“₯ 1.4K / month Β· πŸ“¦ 1 Β· ⏱️ 26.02.2024): - ``` - pip install ampligraph - ``` -
-
ogb (πŸ₯ˆ28 Β· ⭐ 1.9K) - Benchmark datasets, data loaders, and evaluators for graph machine learning. MIT +
ogb (πŸ₯ˆ29 Β· ⭐ 1.9K Β· πŸ’€) - Benchmark datasets, data loaders, and evaluators for graph machine learning. MIT -- [GitHub](https://github.com/snap-stanford/ogb) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 400 Β· πŸ“¦ 1.7K Β· πŸ“‹ 290 - 6% open Β· ⏱️ 01.02.2024): +- [GitHub](https://github.com/snap-stanford/ogb) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 400 Β· πŸ“¦ 1.9K Β· πŸ“‹ 290 - 7% open Β· ⏱️ 01.02.2024): ``` git clone https://github.com/snap-stanford/ogb ``` -- [PyPi](https://pypi.org/project/ogb) (πŸ“₯ 36K / month Β· πŸ“¦ 22 Β· ⏱️ 02.11.2022): +- [PyPi](https://pypi.org/project/ogb) (πŸ“₯ 100K / month Β· πŸ“¦ 22 Β· ⏱️ 02.11.2022): ``` pip install ogb ``` -- [Conda](https://anaconda.org/conda-forge/ogb) (πŸ“₯ 32K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/ogb) (πŸ“₯ 36K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge ogb ```
-
PyKEEN (πŸ₯ˆ26 Β· ⭐ 1.6K) - A Python library for learning and evaluating knowledge graph embeddings. MIT +
PyKEEN (πŸ₯ˆ29 Β· ⭐ 1.6K) - A Python library for learning and evaluating knowledge graph embeddings. MIT -- [GitHub](https://github.com/pykeen/pykeen) (πŸ‘¨β€πŸ’» 39 Β· πŸ”€ 180 Β· πŸ“₯ 180 Β· πŸ“‹ 570 - 20% open Β· ⏱️ 31.05.2024): +- [GitHub](https://github.com/pykeen/pykeen) (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 180 Β· πŸ“₯ 200 Β· πŸ“¦ 240 Β· πŸ“‹ 580 - 20% open Β· ⏱️ 04.09.2024): ``` git clone https://github.com/pykeen/pykeen ``` -- [PyPi](https://pypi.org/project/pykeen) (πŸ“₯ 6.6K / month Β· πŸ“¦ 6 Β· ⏱️ 19.02.2024): +- [PyPi](https://pypi.org/project/pykeen) (πŸ“₯ 6.5K / month Β· πŸ“¦ 6 Β· ⏱️ 19.02.2024): ``` pip install pykeen ```
-
pytorch_geometric_temporal (πŸ₯ˆ25 Β· ⭐ 2.5K Β· πŸ’€) - PyTorch Geometric Temporal: Spatiotemporal Signal.. MIT +
Spektral (πŸ₯ˆ28 Β· ⭐ 2.4K Β· πŸ’€) - Graph Neural Networks with Keras and Tensorflow 2. MIT -- [GitHub](https://github.com/benedekrozemberczki/pytorch_geometric_temporal) (πŸ‘¨β€πŸ’» 28 Β· πŸ”€ 360 Β· πŸ“‹ 190 - 15% open Β· ⏱️ 01.07.2023): +- [GitHub](https://github.com/danielegrattarola/spektral) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 340 Β· πŸ“¦ 320 Β· πŸ“‹ 280 - 24% open Β· ⏱️ 21.01.2024): ``` - git clone https://github.com/benedekrozemberczki/pytorch_geometric_temporal + git clone https://github.com/danielegrattarola/spektral ``` -- [PyPi](https://pypi.org/project/torch-geometric-temporal) (πŸ“₯ 1.8K / month Β· πŸ“¦ 3 Β· ⏱️ 04.09.2022): +- [PyPi](https://pypi.org/project/spektral) (πŸ“₯ 11K / month Β· πŸ“¦ 7 Β· ⏱️ 21.01.2024): ``` - pip install torch-geometric-temporal + pip install spektral ```
-
Paddle Graph Learning (πŸ₯ˆ25 Β· ⭐ 1.6K Β· πŸ’€) - Paddle Graph Learning (PGL) is an efficient and.. Apache-2 +
Paddle Graph Learning (πŸ₯ˆ26 Β· ⭐ 1.6K Β· πŸ’€) - Paddle Graph Learning (PGL) is an efficient and.. Apache-2 -- [GitHub](https://github.com/PaddlePaddle/PGL) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 310 Β· πŸ“¦ 56 Β· πŸ“‹ 210 - 26% open Β· ⏱️ 26.09.2023): +- [GitHub](https://github.com/PaddlePaddle/PGL) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 310 Β· πŸ“¦ 60 Β· πŸ“‹ 210 - 26% open Β· ⏱️ 26.09.2023): ``` git clone https://github.com/PaddlePaddle/PGL ``` -- [PyPi](https://pypi.org/project/pgl) (πŸ“₯ 930 / month Β· πŸ“¦ 1 Β· ⏱️ 26.09.2023): +- [PyPi](https://pypi.org/project/pgl) (πŸ“₯ 1.2K / month Β· πŸ“¦ 1 Β· ⏱️ 26.09.2023): ``` pip install pgl ```
-
PyTorch-BigGraph (πŸ₯ˆ24 Β· ⭐ 3.4K) - Generate embeddings from large-scale graph-structured.. BSD-3 +
AmpliGraph (πŸ₯ˆ25 Β· ⭐ 2.1K Β· πŸ’€) - Python library for Representation Learning on Knowledge.. Apache-2 -- [GitHub](https://github.com/facebookresearch/PyTorch-BigGraph) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 440 Β· πŸ“₯ 180 Β· πŸ“‹ 200 - 32% open Β· ⏱️ 03.03.2024): +- [GitHub](https://github.com/Accenture/AmpliGraph) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 250 Β· πŸ“¦ 55 Β· πŸ“‹ 230 - 17% open Β· ⏱️ 28.02.2024): ``` - git clone https://github.com/facebookresearch/PyTorch-BigGraph + git clone https://github.com/Accenture/AmpliGraph ``` -- [PyPi](https://pypi.org/project/torchbiggraph) (πŸ“₯ 560K / month Β· πŸ“¦ 2 Β· ⏱️ 14.10.2019): +- [PyPi](https://pypi.org/project/ampligraph) (πŸ“₯ 900 / month Β· πŸ“¦ 2 Β· ⏱️ 26.02.2024): ``` - pip install torchbiggraph + pip install ampligraph ```
-
Node2Vec (πŸ₯ˆ24 Β· ⭐ 1.2K) - Implementation of the node2vec algorithm. MIT +
Node2Vec (πŸ₯ˆ25 Β· ⭐ 1.2K) - Implementation of the node2vec algorithm. MIT -- [GitHub](https://github.com/eliorc/node2vec) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 230 Β· πŸ“¦ 620 Β· πŸ“‹ 92 - 5% open Β· ⏱️ 05.05.2024): +- [GitHub](https://github.com/eliorc/node2vec) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 240 Β· πŸ“¦ 670 Β· πŸ“‹ 93 - 5% open Β· ⏱️ 02.08.2024): ``` git clone https://github.com/eliorc/node2vec ``` -- [PyPi](https://pypi.org/project/node2vec) (πŸ“₯ 25K / month Β· πŸ“¦ 27 Β· ⏱️ 01.08.2022): +- [PyPi](https://pypi.org/project/node2vec) (πŸ“₯ 17K / month Β· πŸ“¦ 31 Β· ⏱️ 02.08.2024): ``` pip install node2vec ``` -- [Conda](https://anaconda.org/conda-forge/node2vec) (πŸ“₯ 28K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/node2vec) (πŸ“₯ 30K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge node2vec ```
-
torch-cluster (πŸ₯‰22 Β· ⭐ 770) - PyTorch Extension Library of Optimized Graph Cluster.. MIT +
PyTorch-BigGraph (πŸ₯ˆ24 Β· ⭐ 3.4K) - Generate embeddings from large-scale graph-structured.. BSD-3 + +- [GitHub](https://github.com/facebookresearch/PyTorch-BigGraph) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 450 Β· πŸ“₯ 200 Β· πŸ“‹ 200 - 32% open Β· ⏱️ 03.03.2024): + + ``` + git clone https://github.com/facebookresearch/PyTorch-BigGraph + ``` +- [PyPi](https://pypi.org/project/torchbiggraph) (πŸ“₯ 450K / month Β· πŸ“¦ 2 Β· ⏱️ 14.10.2019): + ``` + pip install torchbiggraph + ``` +
+
torch-cluster (πŸ₯‰22 Β· ⭐ 800) - PyTorch Extension Library of Optimized Graph Cluster.. MIT -- [GitHub](https://github.com/rusty1s/pytorch_cluster) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 140 Β· πŸ“‹ 160 - 17% open Β· ⏱️ 29.04.2024): +- [GitHub](https://github.com/rusty1s/pytorch_cluster) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 140 Β· πŸ“‹ 170 - 21% open Β· ⏱️ 15.08.2024): ``` git clone https://github.com/rusty1s/pytorch_cluster ``` -- [PyPi](https://pypi.org/project/torch-cluster) (πŸ“₯ 14K / month Β· πŸ“¦ 51 Β· ⏱️ 12.10.2023): +- [PyPi](https://pypi.org/project/torch-cluster) (πŸ“₯ 13K / month Β· πŸ“¦ 62 Β· ⏱️ 12.10.2023): ``` pip install torch-cluster ``` -- [Conda](https://anaconda.org/conda-forge/pytorch_cluster) (πŸ“₯ 120K Β· ⏱️ 17.05.2024): +- [Conda](https://anaconda.org/conda-forge/pytorch_cluster) (πŸ“₯ 180K Β· ⏱️ 28.08.2024): ``` conda install -c conda-forge pytorch_cluster ```
-
deepsnap (πŸ₯‰20 Β· ⭐ 530 Β· πŸ’€) - Python library assists deep learning on graphs. MIT +
deepsnap (πŸ₯‰20 Β· ⭐ 540 Β· πŸ’€) - Python library assists deep learning on graphs. MIT -- [GitHub](https://github.com/snap-stanford/deepsnap) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 57 Β· πŸ“₯ 10 Β· πŸ“¦ 100 Β· πŸ“‹ 50 - 50% open Β· ⏱️ 11.11.2023): +- [GitHub](https://github.com/snap-stanford/deepsnap) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 57 Β· πŸ“₯ 12 Β· πŸ“¦ 110 Β· πŸ“‹ 50 - 50% open Β· ⏱️ 11.11.2023): ``` git clone https://github.com/snap-stanford/deepsnap ``` -- [PyPi](https://pypi.org/project/deepsnap) (πŸ“₯ 380 / month Β· πŸ“¦ 2 Β· ⏱️ 05.09.2021): +- [PyPi](https://pypi.org/project/deepsnap) (πŸ“₯ 530 / month Β· πŸ“¦ 2 Β· ⏱️ 05.09.2021): ``` pip install deepsnap ```
-
Sematch (πŸ₯‰18 Β· ⭐ 420 Β· πŸ’€) - semantic similarity framework for knowledge graph. Apache-2 +
Sematch (πŸ₯‰18 Β· ⭐ 430 Β· πŸ’€) - semantic similarity framework for knowledge graph. Apache-2 -- [GitHub](https://github.com/gsi-upm/sematch) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 100 Β· πŸ“¦ 46 Β· πŸ“‹ 34 - 44% open Β· ⏱️ 07.11.2023): +- [GitHub](https://github.com/gsi-upm/sematch) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 100 Β· πŸ“¦ 47 Β· πŸ“‹ 34 - 44% open Β· ⏱️ 07.11.2023): ``` git clone https://github.com/gsi-upm/sematch ``` -- [PyPi](https://pypi.org/project/sematch) (πŸ“₯ 220 / month Β· ⏱️ 17.04.2017): +- [PyPi](https://pypi.org/project/sematch) (πŸ“₯ 230 / month Β· ⏱️ 17.04.2017): ``` pip install sematch ```
-
kglib (πŸ₯‰16 Β· ⭐ 550 Β· πŸ’€) - TypeDB-ML is the Machine Learning integrations library for TypeDB. Apache-2 +
AutoGL (πŸ₯‰16 Β· ⭐ 1.1K Β· πŸ’€) - An autoML framework & toolkit for machine learning on graphs. Apache-2 -- [GitHub](https://github.com/vaticle/typedb-ml) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 98 Β· πŸ“₯ 220 Β· πŸ“‹ 63 - 19% open Β· ⏱️ 18.11.2023): +- [GitHub](https://github.com/THUMNLab/AutoGL) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 120 Β· πŸ“‹ 39 - 35% open Β· ⏱️ 05.02.2024): ``` - git clone https://github.com/vaticle/kglib + git clone https://github.com/THUMNLab/AutoGL ``` -- [PyPi](https://pypi.org/project/grakn-kglib) (πŸ“₯ 77 / month Β· ⏱️ 19.08.2020): +- [PyPi](https://pypi.org/project/auto-graph-learning) (⏱️ 23.12.2020): ``` - pip install grakn-kglib + pip install auto-graph-learning ```
-
AutoGL (πŸ₯‰15 Β· ⭐ 1.1K) - An autoML framework & toolkit for machine learning on graphs. Apache-2 +
kglib (πŸ₯‰16 Β· ⭐ 550 Β· πŸ’€) - TypeDB-ML is the Machine Learning integrations library for TypeDB. Apache-2 -- [GitHub](https://github.com/THUMNLab/AutoGL) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 120 Β· πŸ“‹ 39 - 35% open Β· ⏱️ 05.02.2024): +- [GitHub](https://github.com/typedb/typedb-ml) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 98 Β· πŸ“₯ 240 Β· πŸ“‹ 63 - 19% open Β· ⏱️ 18.11.2023): ``` - git clone https://github.com/THUMNLab/AutoGL + git clone https://github.com/vaticle/kglib ``` -- [PyPi](https://pypi.org/project/auto-graph-learning) (⏱️ 23.12.2020): +- [PyPi](https://pypi.org/project/grakn-kglib) (πŸ“₯ 130 / month Β· ⏱️ 19.08.2020): ``` - pip install auto-graph-learning + pip install grakn-kglib ```
-
OpenNE (πŸ₯‰14 Β· ⭐ 1.7K) - An Open-Source Package for Network Embedding (NE). MIT +
OpenNE (πŸ₯‰14 Β· ⭐ 1.7K Β· πŸ’€) - An Open-Source Package for Network Embedding (NE). MIT - [GitHub](https://github.com/thunlp/OpenNE) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 490 Β· πŸ“‹ 110 - 9% open Β· ⏱️ 10.01.2024): @@ -2974,26 +2956,38 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas git clone https://github.com/thunlp/OpenNE ```
+
GraphVite (πŸ₯‰13 Β· ⭐ 1.2K) - GraphVite: A General and High-performance Graph Embedding System. Apache-2 + +- [GitHub](https://github.com/DeepGraphLearning/graphvite) (πŸ‘¨β€πŸ’» 1 Β· πŸ”€ 150 Β· πŸ“‹ 110 - 46% open Β· ⏱️ 14.06.2024): + + ``` + git clone https://github.com/DeepGraphLearning/graphvite + ``` +- [Conda](https://anaconda.org/milagraph/graphvite) (πŸ“₯ 4.8K Β· ⏱️ 16.06.2023): + ``` + conda install -c milagraph graphvite + ``` +
Show 18 hidden projects... -- igraph (πŸ₯‡33 Β· ⭐ 1.3K) - Python interface for igraph. ❗️GPL-2.0 -- StellarGraph (πŸ₯ˆ29 Β· ⭐ 2.9K Β· πŸ’€) - StellarGraph - Machine Learning on Graphs. Apache-2 -- pygal (πŸ₯ˆ26 Β· ⭐ 2.6K) - PYthon svg GrAph plotting Library. ❗️LGPL-3.0 -- Karate Club (πŸ₯‰23 Β· ⭐ 2.1K) - Karate Club: An API Oriented Open-source Python Framework for.. ❗️GPL-3.0 -- jraph (πŸ₯‰22 Β· ⭐ 1.3K Β· πŸ’€) - A Graph Neural Network Library in Jax. Apache-2 -- graph-nets (πŸ₯‰21 Β· ⭐ 5.3K Β· πŸ’€) - Build Graph Nets in Tensorflow. Apache-2 -- DIG (πŸ₯‰21 Β· ⭐ 1.8K) - A library for graph deep learning research. ❗️GPL-3.0 +- igraph (πŸ₯‡34 Β· ⭐ 1.3K) - Python interface for igraph. ❗️GPL-2.0 +- StellarGraph (πŸ₯ˆ28 Β· ⭐ 2.9K Β· πŸ’€) - StellarGraph - Machine Learning on Graphs. Apache-2 +- pygal (πŸ₯ˆ28 Β· ⭐ 2.6K) - PYthon svg GrAph plotting Library. ❗️LGPL-3.0 +- pytorch_geometric_temporal (πŸ₯ˆ24 Β· ⭐ 2.6K Β· πŸ’€) - PyTorch Geometric Temporal: Spatiotemporal Signal.. MIT +- Karate Club (πŸ₯ˆ24 Β· ⭐ 2.1K) - Karate Club: An API Oriented Open-source Python Framework for.. ❗️GPL-3.0 +- graph-nets (πŸ₯‰22 Β· ⭐ 5.3K Β· πŸ’€) - Build Graph Nets in Tensorflow. Apache-2 +- jraph (πŸ₯‰22 Β· ⭐ 1.4K Β· πŸ’€) - A Graph Neural Network Library in Jax. Apache-2 +- DIG (πŸ₯‰21 Β· ⭐ 1.8K Β· πŸ’€) - A library for graph deep learning research. ❗️GPL-3.0 - graph4nlp (πŸ₯‰21 Β· ⭐ 1.7K Β· πŸ’€) - Graph4nlp is the library for the easy use of Graph.. Apache-2 -- pyRDF2Vec (πŸ₯‰21 Β· ⭐ 240 Β· πŸ’€) - Python Implementation and Extension of RDF2Vec. MIT +- pyRDF2Vec (πŸ₯‰21 Β· ⭐ 240 Β· πŸ’€) - Python Implementation and Extension of RDF2Vec. MIT - DeepWalk (πŸ₯‰20 Β· ⭐ 2.7K Β· πŸ’€) - DeepWalk - Deep Learning for Graphs. ❗️GPL-3.0 - DeepGraph (πŸ₯‰19 Β· ⭐ 280) - Analyze Data with Pandas-based Networks. Documentation:. BSD-3 -- GraphGym (πŸ₯‰18 Β· ⭐ 1.6K Β· πŸ’€) - Platform for designing and evaluating Graph Neural Networks (GNN). MIT -- GraphEmbedding (πŸ₯‰16 Β· ⭐ 3.6K Β· πŸ’€) - Implementation and experiments of graph embedding.. MIT -- Euler (πŸ₯‰15 Β· ⭐ 2.9K Β· πŸ’€) - A distributed graph deep learning framework. Apache-2 -- GraphSAGE (πŸ₯‰14 Β· ⭐ 3.3K Β· πŸ’€) - Representation learning on large graphs using stochastic.. MIT -- GraphVite (πŸ₯‰14 Β· ⭐ 1.2K Β· πŸ’€) - GraphVite: A General and High-performance Graph Embedding.. Apache-2 -- ptgnn (πŸ₯‰14 Β· ⭐ 370 Β· πŸ’€) - A PyTorch Graph Neural Network Library. MIT -- OpenKE (πŸ₯‰13 Β· ⭐ 3.7K) - An Open-Source Package for Knowledge Embedding (KE). ❗Unlicensed +- GraphGym (πŸ₯‰18 Β· ⭐ 1.7K Β· πŸ’€) - Platform for designing and evaluating Graph Neural Networks (GNN). MIT +- Euler (πŸ₯‰16 Β· ⭐ 2.9K Β· πŸ’€) - A distributed graph deep learning framework. Apache-2 +- GraphSAGE (πŸ₯‰15 Β· ⭐ 3.4K Β· πŸ’€) - Representation learning on large graphs using stochastic.. MIT +- ptgnn (πŸ₯‰15 Β· ⭐ 370 Β· πŸ’€) - A PyTorch Graph Neural Network Library. MIT +- GraphEmbedding (πŸ₯‰14 Β· ⭐ 3.7K Β· πŸ’€) - Implementation and experiments of graph embedding.. MIT +- OpenKE (πŸ₯‰13 Β· ⭐ 3.8K Β· πŸ’€) - An Open-Source Package for Knowledge Embedding (KE). ❗Unlicensed

@@ -3003,259 +2997,237 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas _Libraries for audio analysis, manipulation, transformation, and extraction, as well as speech recognition and music generation tasks._ -
speechbrain (πŸ₯‡38 Β· ⭐ 8.1K) - A PyTorch-based Speech Toolkit. Apache-2 +
speechbrain (πŸ₯‡40 Β· ⭐ 8.5K) - A PyTorch-based Speech Toolkit. Apache-2 -- [GitHub](https://github.com/speechbrain/speechbrain) (πŸ‘¨β€πŸ’» 240 Β· πŸ”€ 1.3K Β· πŸ“¦ 1.9K Β· πŸ“‹ 1.1K - 12% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/speechbrain/speechbrain) (πŸ‘¨β€πŸ’» 240 Β· πŸ”€ 1.4K Β· πŸ“¦ 2.2K Β· πŸ“‹ 1.1K - 13% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/speechbrain/speechbrain ``` -- [PyPi](https://pypi.org/project/speechbrain) (πŸ“₯ 2.3M / month Β· πŸ“¦ 31 Β· ⏱️ 26.02.2024): +- [PyPi](https://pypi.org/project/speechbrain) (πŸ“₯ 4M / month Β· πŸ“¦ 62 Β· ⏱️ 02.09.2024): ``` pip install speechbrain ```
-
espnet (πŸ₯‡37 Β· ⭐ 8K) - End-to-End Speech Processing Toolkit. Apache-2 +
espnet (πŸ₯‡37 Β· ⭐ 8.3K) - End-to-End Speech Processing Toolkit. Apache-2 -- [GitHub](https://github.com/espnet/espnet) (πŸ‘¨β€πŸ’» 430 Β· πŸ”€ 2.1K Β· πŸ“₯ 79 Β· πŸ“¦ 340 Β· πŸ“‹ 2.4K - 13% open Β· ⏱️ 04.06.2024): +- [GitHub](https://github.com/espnet/espnet) (πŸ‘¨β€πŸ’» 450 Β· πŸ”€ 2.1K Β· πŸ“₯ 81 Β· πŸ“¦ 370 Β· πŸ“‹ 2.4K - 14% open Β· ⏱️ 04.09.2024): ``` git clone https://github.com/espnet/espnet ``` -- [PyPi](https://pypi.org/project/espnet) (πŸ“₯ 34K / month Β· πŸ“¦ 12 Β· ⏱️ 06.02.2024): +- [PyPi](https://pypi.org/project/espnet) (πŸ“₯ 50K / month Β· πŸ“¦ 12 Β· ⏱️ 06.02.2024): ``` pip install espnet ```
-
SpeechRecognition (πŸ₯‡36 Β· ⭐ 8.1K) - Speech recognition module for Python, supporting several.. BSD-3 +
Coqui TTS (πŸ₯‡35 Β· ⭐ 33K Β· πŸ’€) - - a deep learning toolkit for Text-to-Speech, battle-.. MPL-2.0 -- [GitHub](https://github.com/Uberi/speech_recognition) (πŸ‘¨β€πŸ’» 50 Β· πŸ”€ 2.4K Β· πŸ“¦ 21 Β· πŸ“‹ 640 - 50% open Β· ⏱️ 05.05.2024): +- [GitHub](https://github.com/coqui-ai/TTS) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 4K Β· πŸ“₯ 2.9M Β· πŸ“¦ 1.6K Β· πŸ“‹ 1.1K - 6% open Β· ⏱️ 10.02.2024): ``` - git clone https://github.com/Uberi/speech_recognition + git clone https://github.com/coqui-ai/TTS ``` -- [PyPi](https://pypi.org/project/SpeechRecognition) (πŸ“₯ 930K / month Β· πŸ“¦ 500 Β· ⏱️ 05.05.2024): +- [PyPi](https://pypi.org/project/tts) (πŸ“₯ 99K / month Β· πŸ“¦ 51 Β· ⏱️ 12.12.2023): ``` - pip install SpeechRecognition + pip install tts ``` -- [Conda](https://anaconda.org/conda-forge/speechrecognition) (πŸ“₯ 190K Β· ⏱️ 06.05.2024): +- [Conda](https://anaconda.org/conda-forge/tts) (πŸ“₯ 16K Β· ⏱️ 16.06.2023): ``` - conda install -c conda-forge speechrecognition + conda install -c conda-forge tts ```
-
Coqui TTS (πŸ₯ˆ35 Β· ⭐ 31K) - - a deep learning toolkit for Text-to-Speech, battle-.. MPL-2.0 +
torchaudio (πŸ₯‡35 Β· ⭐ 2.5K) - Data manipulation and transformation for audio signal.. BSD-2 -- [GitHub](https://github.com/coqui-ai/TTS) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 3.6K Β· πŸ“₯ 2.2M Β· πŸ“¦ 1.3K Β· πŸ“‹ 1K - 8% open Β· ⏱️ 10.02.2024): +- [GitHub](https://github.com/pytorch/audio) (πŸ‘¨β€πŸ’» 230 Β· πŸ”€ 640 Β· πŸ“‹ 980 - 25% open Β· ⏱️ 27.08.2024): ``` - git clone https://github.com/coqui-ai/TTS - ``` -- [PyPi](https://pypi.org/project/tts) (πŸ“₯ 120K / month Β· πŸ“¦ 46 Β· ⏱️ 12.12.2023): - ``` - pip install tts + git clone https://github.com/pytorch/audio ``` -- [Conda](https://anaconda.org/conda-forge/tts) (πŸ“₯ 12K Β· ⏱️ 16.06.2023): +- [PyPi](https://pypi.org/project/torchaudio) (πŸ“₯ 6.2M / month Β· πŸ“¦ 1.3K Β· ⏱️ 04.09.2024): ``` - conda install -c conda-forge tts + pip install torchaudio ```
-
torchaudio (πŸ₯ˆ35 Β· ⭐ 2.4K) - Data manipulation and transformation for audio signal.. BSD-2 +
SpeechRecognition (πŸ₯ˆ33 Β· ⭐ 8.3K Β· πŸ“‰) - Speech recognition module for Python, supporting.. BSD-3 -- [GitHub](https://github.com/pytorch/audio) (πŸ‘¨β€πŸ’» 220 Β· πŸ”€ 630 Β· πŸ“‹ 950 - 24% open Β· ⏱️ 14.05.2024): +- [GitHub](https://github.com/Uberi/speech_recognition) (πŸ‘¨β€πŸ’» 51 Β· πŸ”€ 2.4K Β· πŸ“¦ 21 Β· πŸ“‹ 640 - 50% open Β· ⏱️ 13.08.2024): ``` - git clone https://github.com/pytorch/audio + git clone https://github.com/Uberi/speech_recognition ``` -- [PyPi](https://pypi.org/project/torchaudio) (πŸ“₯ 4.9M / month Β· πŸ“¦ 1.1K Β· ⏱️ 05.06.2024): +- [PyPi](https://pypi.org/project/SpeechRecognition) (πŸ“₯ 1.1M / month Β· πŸ“¦ 550 Β· ⏱️ 05.05.2024): ``` - pip install torchaudio + pip install SpeechRecognition + ``` +- [Conda](https://anaconda.org/conda-forge/speechrecognition) (πŸ“₯ 200K Β· ⏱️ 06.05.2024): + ``` + conda install -c conda-forge speechrecognition ```
-
librosa (πŸ₯ˆ34 Β· ⭐ 6.8K) - Python library for audio and music analysis. ISC +
librosa (πŸ₯ˆ33 Β· ⭐ 7K) - Python library for audio and music analysis. ISC -- [GitHub](https://github.com/librosa/librosa) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 930 Β· πŸ“‹ 1.2K - 4% open Β· ⏱️ 03.06.2024): +- [GitHub](https://github.com/librosa/librosa) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 950 Β· πŸ“‹ 1.2K - 4% open Β· ⏱️ 19.08.2024): ``` git clone https://github.com/librosa/librosa ``` -- [PyPi](https://pypi.org/project/librosa) (πŸ“₯ 2.8M / month Β· πŸ“¦ 1.2K Β· ⏱️ 14.05.2024): +- [PyPi](https://pypi.org/project/librosa) (πŸ“₯ 2.7M / month Β· πŸ“¦ 1.3K Β· ⏱️ 14.05.2024): ``` pip install librosa ``` -- [Conda](https://anaconda.org/conda-forge/librosa) (πŸ“₯ 750K Β· ⏱️ 15.05.2024): +- [Conda](https://anaconda.org/conda-forge/librosa) (πŸ“₯ 800K Β· ⏱️ 15.05.2024): ``` conda install -c conda-forge librosa ```
-
Magenta (πŸ₯ˆ32 Β· ⭐ 19K Β· πŸ’€) - Magenta: Music and Art Generation with Machine Intelligence. Apache-2 +
Magenta (πŸ₯ˆ31 Β· ⭐ 19K) - Magenta: Music and Art Generation with Machine Intelligence. Apache-2 -- [GitHub](https://github.com/magenta/magenta) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 3.7K Β· πŸ“¦ 510 Β· πŸ“‹ 1K - 41% open Β· ⏱️ 11.07.2023): +- [GitHub](https://github.com/magenta/magenta) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 3.7K Β· πŸ“¦ 530 Β· πŸ“‹ 1K - 41% open Β· ⏱️ 01.08.2024): ``` git clone https://github.com/magenta/magenta ``` -- [PyPi](https://pypi.org/project/magenta) (πŸ“₯ 4.4K / month Β· πŸ“¦ 5 Β· ⏱️ 01.08.2022): +- [PyPi](https://pypi.org/project/magenta) (πŸ“₯ 4.2K / month Β· πŸ“¦ 5 Β· ⏱️ 01.08.2022): ``` pip install magenta ```
-
spleeter (πŸ₯ˆ30 Β· ⭐ 25K Β· πŸ’€) - Deezer source separation library including pretrained models. MIT +
Porcupine (πŸ₯ˆ30 Β· ⭐ 3.7K) - On-device wake word detection powered by deep learning. Apache-2 -- [GitHub](https://github.com/deezer/spleeter) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 2.7K Β· πŸ“₯ 3.2M Β· πŸ“¦ 720 Β· πŸ“‹ 790 - 29% open Β· ⏱️ 13.07.2023): +- [GitHub](https://github.com/Picovoice/porcupine) (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 500 Β· πŸ“¦ 33 Β· ⏱️ 30.08.2024): ``` - git clone https://github.com/deezer/spleeter - ``` -- [PyPi](https://pypi.org/project/spleeter) (πŸ“₯ 15K / month Β· πŸ“¦ 6 Β· ⏱️ 10.06.2022): - ``` - pip install spleeter + git clone https://github.com/Picovoice/Porcupine ``` -- [Conda](https://anaconda.org/conda-forge/spleeter) (πŸ“₯ 83K Β· ⏱️ 16.06.2023): +- [PyPi](https://pypi.org/project/pvporcupine) (πŸ“₯ 10K / month Β· πŸ“¦ 33 Β· ⏱️ 27.08.2024): ``` - conda install -c conda-forge spleeter + pip install pvporcupine ```
-
Porcupine (πŸ₯ˆ29 Β· ⭐ 3.5K) - On-device wake word detection powered by deep learning. Apache-2 +
audioread (πŸ₯ˆ30 Β· ⭐ 480 Β· πŸ’€) - cross-library (GStreamer + Core Audio + MAD + FFmpeg) audio.. MIT -- [GitHub](https://github.com/Picovoice/porcupine) (πŸ‘¨β€πŸ’» 37 Β· πŸ”€ 470 Β· πŸ“¦ 28 Β· πŸ“‹ 540 - 1% open Β· ⏱️ 18.04.2024): +- [GitHub](https://github.com/beetbox/audioread) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 110 Β· πŸ“¦ 23K Β· πŸ“‹ 94 - 39% open Β· ⏱️ 15.12.2023): ``` - git clone https://github.com/Picovoice/Porcupine + git clone https://github.com/beetbox/audioread ``` -- [PyPi](https://pypi.org/project/pvporcupine) (πŸ“₯ 8K / month Β· πŸ“¦ 15 Β· ⏱️ 30.01.2024): +- [PyPi](https://pypi.org/project/audioread) (πŸ“₯ 2M / month Β· πŸ“¦ 130 Β· ⏱️ 27.09.2023): ``` - pip install pvporcupine + pip install audioread + ``` +- [Conda](https://anaconda.org/conda-forge/audioread) (πŸ“₯ 850K Β· ⏱️ 03.09.2024): + ``` + conda install -c conda-forge audioread ```
-
audiomentations (πŸ₯ˆ29 Β· ⭐ 1.7K) - A Python library for audio data augmentation. Inspired by.. MIT +
audiomentations (πŸ₯‰29 Β· ⭐ 1.8K) - A Python library for audio data augmentation. Inspired by.. MIT -- [GitHub](https://github.com/iver56/audiomentations) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 180 Β· πŸ“¦ 490 Β· πŸ“‹ 180 - 26% open Β· ⏱️ 29.04.2024): +- [GitHub](https://github.com/iver56/audiomentations) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 190 Β· πŸ“¦ 560 Β· πŸ“‹ 180 - 25% open Β· ⏱️ 04.09.2024): ``` git clone https://github.com/iver56/audiomentations ``` -- [PyPi](https://pypi.org/project/audiomentations) (πŸ“₯ 21K / month Β· πŸ“¦ 13 Β· ⏱️ 15.03.2024): +- [PyPi](https://pypi.org/project/audiomentations) (πŸ“₯ 46K / month Β· πŸ“¦ 18 Β· ⏱️ 03.09.2024): ``` pip install audiomentations ```
-
audioread (πŸ₯ˆ29 Β· ⭐ 480) - cross-library (GStreamer + Core Audio + MAD + FFmpeg) audio decoding.. MIT +
python-soundfile (πŸ₯‰29 Β· ⭐ 700 Β· πŸ“ˆ) - SoundFile is an audio library based on libsndfile, CFFI,.. BSD-3 -- [GitHub](https://github.com/beetbox/audioread) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 110 Β· πŸ“¦ 21K Β· πŸ“‹ 94 - 39% open Β· ⏱️ 15.12.2023): +- [GitHub](https://github.com/bastibe/python-soundfile) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 110 Β· πŸ“₯ 20K Β· πŸ“¦ 41K Β· πŸ“‹ 260 - 46% open Β· ⏱️ 27.07.2024): ``` - git clone https://github.com/beetbox/audioread + git clone https://github.com/bastibe/python-soundfile ``` -- [PyPi](https://pypi.org/project/audioread) (πŸ“₯ 1.9M / month Β· πŸ“¦ 120 Β· ⏱️ 27.09.2023): +- [PyPi](https://pypi.org/project/soundfile) (πŸ“₯ 4.6M / month Β· πŸ“¦ 780 Β· ⏱️ 15.02.2023): ``` - pip install audioread + pip install soundfile ``` -- [Conda](https://anaconda.org/conda-forge/audioread) (πŸ“₯ 780K Β· ⏱️ 30.09.2023): +- [Conda](https://anaconda.org/anaconda/pysoundfile): ``` - conda install -c conda-forge audioread + conda install -c anaconda pysoundfile ```
-
pyAudioAnalysis (πŸ₯‰28 Β· ⭐ 5.7K Β· πŸ’€) - Python Audio Analysis Library: Feature Extraction,.. Apache-2 +
pyAudioAnalysis (πŸ₯‰28 Β· ⭐ 5.8K Β· πŸ’€) - Python Audio Analysis Library: Feature Extraction,.. Apache-2 -- [GitHub](https://github.com/tyiannak/pyAudioAnalysis) (πŸ‘¨β€πŸ’» 28 Β· πŸ”€ 1.2K Β· πŸ“¦ 460 Β· πŸ“‹ 320 - 61% open Β· ⏱️ 22.10.2023): +- [GitHub](https://github.com/tyiannak/pyAudioAnalysis) (πŸ‘¨β€πŸ’» 28 Β· πŸ”€ 1.2K Β· πŸ“¦ 500 Β· πŸ“‹ 320 - 62% open Β· ⏱️ 22.10.2023): ``` git clone https://github.com/tyiannak/pyAudioAnalysis ``` -- [PyPi](https://pypi.org/project/pyAudioAnalysis) (πŸ“₯ 21K / month Β· πŸ“¦ 12 Β· ⏱️ 07.02.2022): +- [PyPi](https://pypi.org/project/pyAudioAnalysis) (πŸ“₯ 10K / month Β· πŸ“¦ 12 Β· ⏱️ 07.02.2022): ``` pip install pyAudioAnalysis ```
-
Madmom (πŸ₯‰26 Β· ⭐ 1.3K Β· πŸ’€) - Python audio and music signal processing library. BSD-3 +
Madmom (πŸ₯‰27 Β· ⭐ 1.3K) - Python audio and music signal processing library. BSD-3 -- [GitHub](https://github.com/CPJKU/madmom) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 200 Β· πŸ“¦ 420 Β· πŸ“‹ 280 - 23% open Β· ⏱️ 10.09.2023): +- [GitHub](https://github.com/CPJKU/madmom) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 200 Β· πŸ“¦ 430 Β· πŸ“‹ 280 - 24% open Β· ⏱️ 25.08.2024): ``` git clone https://github.com/CPJKU/madmom ``` -- [PyPi](https://pypi.org/project/madmom) (πŸ“₯ 1.9K / month Β· πŸ“¦ 27 Β· ⏱️ 14.11.2018): +- [PyPi](https://pypi.org/project/madmom) (πŸ“₯ 2K / month Β· πŸ“¦ 27 Β· ⏱️ 14.11.2018): ``` pip install madmom ```
-
DDSP (πŸ₯‰25 Β· ⭐ 2.8K Β· πŸ’€) - DDSP: Differentiable Digital Signal Processing. Apache-2 - -- [GitHub](https://github.com/magenta/ddsp) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 320 Β· πŸ“¦ 54 Β· πŸ“‹ 170 - 28% open Β· ⏱️ 30.06.2023): - - ``` - git clone https://github.com/magenta/ddsp - ``` -- [PyPi](https://pypi.org/project/ddsp) (πŸ“₯ 1.5K / month Β· πŸ“¦ 1 Β· ⏱️ 25.05.2022): - ``` - pip install ddsp - ``` -- [Conda](https://anaconda.org/conda-forge/ddsp) (πŸ“₯ 16K Β· ⏱️ 16.06.2023): - ``` - conda install -c conda-forge ddsp - ``` -
-
tinytag (πŸ₯‰25 Β· ⭐ 670) - Python library for reading audio file metadata, duration of MP3, OGG,.. MIT +
tinytag (πŸ₯‰25 Β· ⭐ 690) - Python library for reading audio file metadata. MIT -- [GitHub](https://github.com/devsnd/tinytag) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 100 Β· πŸ“‹ 120 - 12% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/tinytag/tinytag) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 100 Β· πŸ“‹ 120 - 12% open Β· ⏱️ 29.08.2024): ``` git clone https://github.com/devsnd/tinytag ``` -- [PyPi](https://pypi.org/project/tinytag) (πŸ“₯ 25K / month Β· πŸ“¦ 100 Β· ⏱️ 26.10.2023): +- [PyPi](https://pypi.org/project/tinytag) (πŸ“₯ 25K / month Β· πŸ“¦ 110 Β· ⏱️ 26.10.2023): ``` pip install tinytag ```
-
python-soundfile (πŸ₯‰25 Β· ⭐ 670) - SoundFile is an audio library based on libsndfile, CFFI, and.. BSD-3 +
DDSP (πŸ₯‰23 Β· ⭐ 2.9K) - DDSP: Differentiable Digital Signal Processing. Apache-2 -- [GitHub](https://github.com/bastibe/python-soundfile) (πŸ‘¨β€πŸ’» 33 Β· πŸ”€ 100 Β· πŸ“₯ 19K Β· πŸ“‹ 250 - 46% open Β· ⏱️ 05.01.2024): +- [GitHub](https://github.com/magenta/ddsp) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 320 Β· πŸ“¦ 58 Β· πŸ“‹ 170 - 28% open Β· ⏱️ 17.06.2024): ``` - git clone https://github.com/bastibe/python-soundfile + git clone https://github.com/magenta/ddsp ``` -- [PyPi](https://pypi.org/project/soundfile) (πŸ“₯ 3.2M / month Β· πŸ“¦ 620 Β· ⏱️ 15.02.2023): +- [PyPi](https://pypi.org/project/ddsp) (πŸ“₯ 1.4K / month Β· πŸ“¦ 1 Β· ⏱️ 25.05.2022): ``` - pip install soundfile + pip install ddsp ``` -- [Conda](https://anaconda.org/anaconda/pysoundfile): +- [Conda](https://anaconda.org/conda-forge/ddsp) (πŸ“₯ 18K Β· ⏱️ 16.06.2023): ``` - conda install -c anaconda pysoundfile + conda install -c conda-forge ddsp ```
-
nnAudio (πŸ₯‰22 Β· ⭐ 970) - Audio processing by using pytorch 1D convolution network. MIT +
nnAudio (πŸ₯‰22 Β· ⭐ 1K Β· πŸ’€) - Audio processing by using pytorch 1D convolution network. MIT -- [GitHub](https://github.com/KinWaiCheuk/nnAudio) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 90 Β· πŸ“¦ 180 Β· πŸ“‹ 62 - 29% open Β· ⏱️ 13.02.2024): +- [GitHub](https://github.com/KinWaiCheuk/nnAudio) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 89 Β· πŸ“¦ 200 Β· πŸ“‹ 63 - 28% open Β· ⏱️ 13.02.2024): ``` git clone https://github.com/KinWaiCheuk/nnAudio ``` -- [PyPi](https://pypi.org/project/nnAudio) (πŸ“₯ 11K / month Β· πŸ“¦ 4 Β· ⏱️ 13.02.2024): +- [PyPi](https://pypi.org/project/nnAudio) (πŸ“₯ 13K / month Β· πŸ“¦ 4 Β· ⏱️ 13.02.2024): ``` pip install nnAudio ```
-
textlesslib (πŸ₯‰10 Β· ⭐ 510 Β· πŸ’€) - Library for Textless Spoken Language Processing. MIT - -- [GitHub](https://github.com/facebookresearch/textlesslib) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 51 Β· πŸ“‹ 25 - 56% open Β· ⏱️ 29.08.2023): - - ``` - git clone https://github.com/facebookresearch/textlesslib - ``` -
-
Show 11 hidden projects... +
Show 13 hidden projects... -- Pydub (πŸ₯ˆ35 Β· ⭐ 8.5K Β· πŸ’€) - Manipulate audio with a simple and easy high level interface. MIT -- DeepSpeech (πŸ₯ˆ33 Β· ⭐ 25K Β· πŸ’€) - DeepSpeech is an open source embedded (offline, on-.. MPL-2.0 -- aubio (πŸ₯‰28 Β· ⭐ 3.2K) - a library for audio and music analysis. ❗️GPL-3.0 -- Essentia (πŸ₯‰28 Β· ⭐ 2.7K) - C++ library for audio and music analysis, description and.. ❗️AGPL-3.0 -- TTS (πŸ₯‰26 Β· ⭐ 8.9K Β· πŸ’€) - Deep learning for Text to Speech (Discussion forum:.. MPL-2.0 -- python_speech_features (πŸ₯‰24 Β· ⭐ 2.3K Β· πŸ’€) - This library provides common speech features for ASR.. MIT -- Dejavu (πŸ₯‰23 Β· ⭐ 6.3K Β· πŸ’€) - Audio fingerprinting and recognition in Python. MIT -- kapre (πŸ₯‰23 Β· ⭐ 920 Β· πŸ’€) - kapre: Keras Audio Preprocessors. MIT -- Julius (πŸ₯‰21 Β· ⭐ 410 Β· πŸ’€) - Fast PyTorch based DSP for audio and 1D signals. MIT -- TimeSide (πŸ₯‰20 Β· ⭐ 370 Β· πŸ’€) - scalable audio processing framework and server written in.. ❗️AGPL-3.0 +- Pydub (πŸ₯‡35 Β· ⭐ 8.7K Β· πŸ’€) - Manipulate audio with a simple and easy high level interface. MIT +- DeepSpeech (πŸ₯ˆ34 Β· ⭐ 25K Β· πŸ’€) - DeepSpeech is an open source embedded (offline, on-.. MPL-2.0 +- spleeter (πŸ₯ˆ31 Β· ⭐ 26K Β· πŸ’€) - Deezer source separation library including pretrained models. MIT +- aubio (πŸ₯‰28 Β· ⭐ 3.3K Β· πŸ’€) - a library for audio and music analysis. ❗️GPL-3.0 +- Essentia (πŸ₯‰28 Β· ⭐ 2.8K) - C++ library for audio and music analysis, description and.. ❗️AGPL-3.0 +- TTS (πŸ₯‰26 Β· ⭐ 9.2K Β· πŸ’€) - Deep learning for Text to Speech (Discussion forum:.. MPL-2.0 +- python_speech_features (πŸ₯‰24 Β· ⭐ 2.4K Β· πŸ’€) - This library provides common speech features for ASR.. MIT +- Dejavu (πŸ₯‰23 Β· ⭐ 6.4K Β· πŸ’€) - Audio fingerprinting and recognition in Python. MIT +- kapre (πŸ₯‰22 Β· ⭐ 920 Β· πŸ’€) - kapre: Keras Audio Preprocessors. MIT +- TimeSide (πŸ₯‰22 Β· ⭐ 370 Β· πŸ’€) - scalable audio processing framework and server written in.. ❗️AGPL-3.0 +- Julius (πŸ₯‰21 Β· ⭐ 420 Β· πŸ’€) - Fast PyTorch based DSP for audio and 1D signals. MIT - Muda (πŸ₯‰17 Β· ⭐ 230 Β· πŸ’€) - A library for augmenting annotated audio data. ISC +- textlesslib (πŸ₯‰10 Β· ⭐ 520 Β· πŸ’€) - Library for Textless Spoken Language Processing. MIT

@@ -3267,261 +3239,246 @@ _Libraries to load, process, analyze, and write geographic data as well as libra
pydeck (πŸ₯‡43 Β· ⭐ 12K) - WebGL2 powered visualization framework. MIT -- [GitHub](https://github.com/visgl/deck.gl) (πŸ‘¨β€πŸ’» 260 Β· πŸ”€ 2K Β· πŸ“¦ 7.7K Β· πŸ“‹ 3K - 10% open Β· ⏱️ 04.06.2024): +- [GitHub](https://github.com/visgl/deck.gl) (πŸ‘¨β€πŸ’» 270 Β· πŸ”€ 2.1K Β· πŸ“¦ 8K Β· πŸ“‹ 3.1K - 11% open Β· ⏱️ 04.09.2024): ``` git clone https://github.com/visgl/deck.gl ``` -- [PyPi](https://pypi.org/project/pydeck) (πŸ“₯ 3.7M / month Β· πŸ“¦ 88 Β· ⏱️ 10.05.2024): +- [PyPi](https://pypi.org/project/pydeck) (πŸ“₯ 4.6M / month Β· πŸ“¦ 100 Β· ⏱️ 10.05.2024): ``` pip install pydeck ``` -- [Conda](https://anaconda.org/conda-forge/pydeck) (πŸ“₯ 530K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/pydeck) (πŸ“₯ 600K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge pydeck ``` -- [npm](https://www.npmjs.com/package/deck.gl) (πŸ“₯ 460K / month Β· πŸ“¦ 290 Β· ⏱️ 29.05.2024): +- [npm](https://www.npmjs.com/package/deck.gl) (πŸ“₯ 640K / month Β· πŸ“¦ 300 Β· ⏱️ 04.09.2024): ``` npm install deck.gl ```
-
folium (πŸ₯‡40 Β· ⭐ 6.7K) - Python Data. Leaflet.js Maps. MIT +
Shapely (πŸ₯‡40 Β· ⭐ 3.8K) - Manipulation and analysis of geometric objects. BSD-3 -- [GitHub](https://github.com/python-visualization/folium) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 2.2K Β· πŸ“¦ 38K Β· πŸ“‹ 1.1K - 7% open Β· ⏱️ 03.06.2024): +- [GitHub](https://github.com/shapely/shapely) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 560 Β· πŸ“₯ 3.6K Β· πŸ“¦ 78K Β· πŸ“‹ 1.2K - 23% open Β· ⏱️ 03.09.2024): ``` - git clone https://github.com/python-visualization/folium + git clone https://github.com/shapely/shapely ``` -- [PyPi](https://pypi.org/project/folium) (πŸ“₯ 1.2M / month Β· πŸ“¦ 660 Β· ⏱️ 29.02.2024): +- [PyPi](https://pypi.org/project/shapely) (πŸ“₯ 32M / month Β· πŸ“¦ 2.9K Β· ⏱️ 19.08.2024): ``` - pip install folium + pip install shapely ``` -- [Conda](https://anaconda.org/conda-forge/folium) (πŸ“₯ 2.8M Β· ⏱️ 29.02.2024): +- [Conda](https://anaconda.org/conda-forge/shapely) (πŸ“₯ 10M Β· ⏱️ 03.09.2024): ``` - conda install -c conda-forge folium + conda install -c conda-forge shapely ```
-
GeoPandas (πŸ₯‡40 Β· ⭐ 4.3K) - Python tools for geographic data. BSD-3 +
folium (πŸ₯‡39 Β· ⭐ 6.8K) - Python Data. Leaflet.js Maps. MIT -- [GitHub](https://github.com/geopandas/geopandas) (πŸ‘¨β€πŸ’» 220 Β· πŸ”€ 900 Β· πŸ“₯ 2.5K Β· πŸ“¦ 36K Β· πŸ“‹ 1.7K - 26% open Β· ⏱️ 04.06.2024): +- [GitHub](https://github.com/python-visualization/folium) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 2.2K Β· πŸ“¦ 42K Β· πŸ“‹ 1.1K - 7% open Β· ⏱️ 04.09.2024): ``` - git clone https://github.com/geopandas/geopandas + git clone https://github.com/python-visualization/folium ``` -- [PyPi](https://pypi.org/project/geopandas) (πŸ“₯ 6.1M / month Β· πŸ“¦ 2.5K Β· ⏱️ 28.04.2024): +- [PyPi](https://pypi.org/project/folium) (πŸ“₯ 1.4M / month Β· πŸ“¦ 710 Β· ⏱️ 16.06.2024): ``` - pip install geopandas + pip install folium ``` -- [Conda](https://anaconda.org/conda-forge/geopandas) (πŸ“₯ 3.7M Β· ⏱️ 28.04.2024): +- [Conda](https://anaconda.org/conda-forge/folium) (πŸ“₯ 3M Β· ⏱️ 17.06.2024): ``` - conda install -c conda-forge geopandas + conda install -c conda-forge folium ```
-
Shapely (πŸ₯ˆ39 Β· ⭐ 3.7K) - Manipulation and analysis of geometric objects. BSD-3 +
GeoPandas (πŸ₯‡39 Β· ⭐ 4.4K) - Python tools for geographic data. BSD-3 -- [GitHub](https://github.com/shapely/shapely) (πŸ‘¨β€πŸ’» 150 Β· πŸ”€ 560 Β· πŸ“₯ 3.3K Β· πŸ“¦ 71K Β· πŸ“‹ 1.2K - 22% open Β· ⏱️ 14.05.2024): +- [GitHub](https://github.com/geopandas/geopandas) (πŸ‘¨β€πŸ’» 230 Β· πŸ”€ 920 Β· πŸ“₯ 2.7K Β· πŸ“¦ 40K Β· πŸ“‹ 1.7K - 25% open Β· ⏱️ 01.09.2024): ``` - git clone https://github.com/shapely/shapely + git clone https://github.com/geopandas/geopandas ``` -- [PyPi](https://pypi.org/project/shapely) (πŸ“₯ 27M / month Β· πŸ“¦ 2.5K Β· ⏱️ 16.04.2024): +- [PyPi](https://pypi.org/project/geopandas) (πŸ“₯ 6.6M / month Β· πŸ“¦ 2.7K Β· ⏱️ 02.07.2024): ``` - pip install shapely + pip install geopandas ``` -- [Conda](https://anaconda.org/conda-forge/shapely) (πŸ“₯ 9.4M Β· ⏱️ 16.05.2024): +- [Conda](https://anaconda.org/conda-forge/geopandas) (πŸ“₯ 3.9M Β· ⏱️ 02.07.2024): ``` - conda install -c conda-forge shapely + conda install -c conda-forge geopandas ```
Rasterio (πŸ₯ˆ37 Β· ⭐ 2.2K) - Rasterio reads and writes geospatial raster datasets. BSD-3 -- [GitHub](https://github.com/rasterio/rasterio) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 520 Β· πŸ“₯ 860 Β· πŸ“¦ 12K Β· πŸ“‹ 1.8K - 8% open Β· ⏱️ 10.05.2024): +- [GitHub](https://github.com/rasterio/rasterio) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 520 Β· πŸ“₯ 920 Β· πŸ“¦ 13K Β· πŸ“‹ 1.8K - 7% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/rasterio/rasterio ``` -- [PyPi](https://pypi.org/project/rasterio) (πŸ“₯ 2.8M / month Β· πŸ“¦ 1.3K Β· ⏱️ 16.04.2024): +- [PyPi](https://pypi.org/project/rasterio) (πŸ“₯ 3.2M / month Β· πŸ“¦ 1.4K Β· ⏱️ 04.09.2024): ``` pip install rasterio ``` -- [Conda](https://anaconda.org/conda-forge/rasterio) (πŸ“₯ 3M Β· ⏱️ 06.06.2024): +- [Conda](https://anaconda.org/conda-forge/rasterio) (πŸ“₯ 3.5M Β· ⏱️ 04.09.2024): ``` conda install -c conda-forge rasterio ```
Fiona (πŸ₯ˆ37 Β· ⭐ 1.1K) - Fiona reads and writes geographic data files. BSD-3 -- [GitHub](https://github.com/Toblerity/Fiona) (πŸ‘¨β€πŸ’» 74 Β· πŸ”€ 200 Β· πŸ“¦ 20K Β· πŸ“‹ 790 - 4% open Β· ⏱️ 20.05.2024): +- [GitHub](https://github.com/Toblerity/Fiona) (πŸ‘¨β€πŸ’» 74 Β· πŸ”€ 200 Β· πŸ“¦ 22K Β· πŸ“‹ 800 - 3% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/Toblerity/Fiona ``` -- [PyPi](https://pypi.org/project/fiona) (πŸ“₯ 6.1M / month Β· πŸ“¦ 190 Β· ⏱️ 16.04.2024): +- [PyPi](https://pypi.org/project/fiona) (πŸ“₯ 5M / month Β· πŸ“¦ 260 Β· ⏱️ 04.09.2024): ``` pip install fiona ``` -- [Conda](https://anaconda.org/conda-forge/fiona) (πŸ“₯ 5.6M Β· ⏱️ 21.05.2024): +- [Conda](https://anaconda.org/conda-forge/fiona) (πŸ“₯ 5.9M Β· ⏱️ 04.09.2024): ``` conda install -c conda-forge fiona ```
+
ArcGIS API (πŸ₯ˆ35 Β· ⭐ 1.9K) - Documentation and samples for ArcGIS API for Python. Apache-2 + +- [GitHub](https://github.com/Esri/arcgis-python-api) (πŸ‘¨β€πŸ’» 91 Β· πŸ”€ 1.1K Β· πŸ“₯ 12K Β· πŸ“¦ 820 Β· πŸ“‹ 750 - 9% open Β· ⏱️ 04.09.2024): + + ``` + git clone https://github.com/Esri/arcgis-python-api + ``` +- [PyPi](https://pypi.org/project/arcgis) (πŸ“₯ 72K / month Β· πŸ“¦ 40 Β· ⏱️ 09.07.2024): + ``` + pip install arcgis + ``` +- [Docker Hub](https://hub.docker.com/r/esridocker/arcgis-api-python-notebook): + ``` + docker pull esridocker/arcgis-api-python-notebook + ``` +
pyproj (πŸ₯ˆ35 Β· ⭐ 1K) - Python interface to PROJ (cartographic projections and coordinate.. MIT -- [GitHub](https://github.com/pyproj4/pyproj) (πŸ‘¨β€πŸ’» 65 Β· πŸ”€ 210 Β· πŸ“¦ 31K Β· πŸ“‹ 610 - 5% open Β· ⏱️ 02.06.2024): +- [GitHub](https://github.com/pyproj4/pyproj) (πŸ‘¨β€πŸ’» 65 Β· πŸ”€ 210 Β· πŸ“¦ 33K Β· πŸ“‹ 620 - 5% open Β· ⏱️ 30.08.2024): ``` git clone https://github.com/pyproj4/pyproj ``` -- [PyPi](https://pypi.org/project/pyproj) (πŸ“₯ 8.5M / month Β· πŸ“¦ 1.5K Β· ⏱️ 21.09.2023): +- [PyPi](https://pypi.org/project/pyproj) (πŸ“₯ 8.8M / month Β· πŸ“¦ 1.7K Β· ⏱️ 21.09.2023): ``` pip install pyproj ``` -- [Conda](https://anaconda.org/conda-forge/pyproj) (πŸ“₯ 7.7M Β· ⏱️ 01.05.2024): +- [Conda](https://anaconda.org/conda-forge/pyproj) (πŸ“₯ 8.4M Β· ⏱️ 04.09.2024): ``` conda install -c conda-forge pyproj ```
-
ArcGIS API (πŸ₯ˆ34 Β· ⭐ 1.8K) - Documentation and samples for ArcGIS API for Python. Apache-2 +
geopy (πŸ₯ˆ33 Β· ⭐ 4.4K Β· πŸ’€) - Geocoding library for Python. MIT -- [GitHub](https://github.com/Esri/arcgis-python-api) (πŸ‘¨β€πŸ’» 91 Β· πŸ”€ 1.1K Β· πŸ“₯ 11K Β· πŸ“¦ 760 Β· πŸ“‹ 730 - 9% open Β· ⏱️ 22.05.2024): +- [GitHub](https://github.com/geopy/geopy) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 640 Β· πŸ“₯ 75 Β· πŸ“‹ 290 - 13% open Β· ⏱️ 23.11.2023): ``` - git clone https://github.com/Esri/arcgis-python-api + git clone https://github.com/geopy/geopy ``` -- [PyPi](https://pypi.org/project/arcgis) (πŸ“₯ 68K / month Β· πŸ“¦ 36 Β· ⏱️ 28.05.2024): +- [PyPi](https://pypi.org/project/geopy) (πŸ“₯ 5.8M / month Β· πŸ“¦ 870 Β· ⏱️ 23.11.2023): ``` - pip install arcgis + pip install geopy ``` -- [Docker Hub](https://hub.docker.com/r/esridocker/arcgis-api-python-notebook): +- [Conda](https://anaconda.org/conda-forge/geopy) (πŸ“₯ 1.4M Β· ⏱️ 28.02.2024): ``` - docker pull esridocker/arcgis-api-python-notebook + conda install -c conda-forge geopy ```
-
ipyleaflet (πŸ₯ˆ34 Β· ⭐ 1.5K) - A Jupyter - Leaflet.js bridge. MIT +
ipyleaflet (πŸ₯ˆ33 Β· ⭐ 1.5K) - A Jupyter - Leaflet.js bridge. MIT -- [GitHub](https://github.com/jupyter-widgets/ipyleaflet) (πŸ‘¨β€πŸ’» 88 Β· πŸ”€ 360 Β· πŸ“¦ 9.2K Β· πŸ“‹ 630 - 43% open Β· ⏱️ 29.05.2024): +- [GitHub](https://github.com/jupyter-widgets/ipyleaflet) (πŸ‘¨β€πŸ’» 90 Β· πŸ”€ 360 Β· πŸ“¦ 11K Β· πŸ“‹ 650 - 44% open Β· ⏱️ 22.07.2024): ``` git clone https://github.com/jupyter-widgets/ipyleaflet ``` -- [PyPi](https://pypi.org/project/ipyleaflet) (πŸ“₯ 140K / month Β· πŸ“¦ 250 Β· ⏱️ 14.05.2024): +- [PyPi](https://pypi.org/project/ipyleaflet) (πŸ“₯ 260K / month Β· πŸ“¦ 270 Β· ⏱️ 22.07.2024): ``` pip install ipyleaflet ``` -- [Conda](https://anaconda.org/conda-forge/ipyleaflet) (πŸ“₯ 1.2M Β· ⏱️ 14.05.2024): +- [Conda](https://anaconda.org/conda-forge/ipyleaflet) (πŸ“₯ 1.2M Β· ⏱️ 22.07.2024): ``` conda install -c conda-forge ipyleaflet ``` -- [npm](https://www.npmjs.com/package/jupyter-leaflet) (πŸ“₯ 11K / month Β· πŸ“¦ 9 Β· ⏱️ 13.05.2024): +- [npm](https://www.npmjs.com/package/jupyter-leaflet) (πŸ“₯ 6.5K / month Β· πŸ“¦ 9 Β· ⏱️ 22.07.2024): ``` npm install jupyter-leaflet ```
-
geopy (πŸ₯‰32 Β· ⭐ 4.3K Β· πŸ’€) - Geocoding library for Python. MIT - -- [GitHub](https://github.com/geopy/geopy) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 630 Β· πŸ“₯ 48 Β· πŸ“‹ 290 - 13% open Β· ⏱️ 23.11.2023): - - ``` - git clone https://github.com/geopy/geopy - ``` -- [PyPi](https://pypi.org/project/geopy) (πŸ“₯ 5.2M / month Β· πŸ“¦ 790 Β· ⏱️ 23.11.2023): - ``` - pip install geopy - ``` -- [Conda](https://anaconda.org/conda-forge/geopy) (πŸ“₯ 1.3M Β· ⏱️ 28.02.2024): - ``` - conda install -c conda-forge geopy - ``` -
-
PySAL (πŸ₯‰30 Β· ⭐ 1.3K) - PySAL: Python Spatial Analysis Library Meta-Package. BSD-3 +
PySAL (πŸ₯‰32 Β· ⭐ 1.3K) - PySAL: Python Spatial Analysis Library Meta-Package. BSD-3 -- [GitHub](https://github.com/pysal/pysal) (πŸ‘¨β€πŸ’» 78 Β· πŸ”€ 280 Β· πŸ“¦ 1.5K Β· πŸ“‹ 630 - 3% open Β· ⏱️ 15.03.2024): +- [GitHub](https://github.com/pysal/pysal) (πŸ‘¨β€πŸ’» 79 Β· πŸ”€ 300 Β· πŸ“¦ 1.6K Β· πŸ“‹ 650 - 2% open Β· ⏱️ 31.07.2024): ``` git clone https://github.com/pysal/pysal ``` -- [PyPi](https://pypi.org/project/pysal) (πŸ“₯ 29K / month Β· πŸ“¦ 39 Β· ⏱️ 31.01.2024): +- [PyPi](https://pypi.org/project/pysal) (πŸ“₯ 39K / month Β· πŸ“¦ 49 Β· ⏱️ 30.07.2024): ``` pip install pysal ``` -- [Conda](https://anaconda.org/conda-forge/pysal) (πŸ“₯ 550K Β· ⏱️ 04.10.2023): +- [Conda](https://anaconda.org/conda-forge/pysal) (πŸ“₯ 570K Β· ⏱️ 30.07.2024): ``` conda install -c conda-forge pysal ```
-
geojson (πŸ₯‰29 Β· ⭐ 890) - Python bindings and utilities for GeoJSON. BSD-3 +
geojson (πŸ₯‰29 Β· ⭐ 910) - Python bindings and utilities for GeoJSON. BSD-3 -- [GitHub](https://github.com/jazzband/geojson) (πŸ‘¨β€πŸ’» 56 Β· πŸ”€ 120 Β· πŸ“¦ 17K Β· πŸ“‹ 100 - 26% open Β· ⏱️ 25.03.2024): +- [GitHub](https://github.com/jazzband/geojson) (πŸ‘¨β€πŸ’» 56 Β· πŸ”€ 120 Β· πŸ“¦ 18K Β· πŸ“‹ 100 - 25% open Β· ⏱️ 08.08.2024): ``` git clone https://github.com/jazzband/geojson ``` -- [PyPi](https://pypi.org/project/geojson) (πŸ“₯ 1.7M / month Β· πŸ“¦ 660 Β· ⏱️ 05.11.2023): +- [PyPi](https://pypi.org/project/geojson) (πŸ“₯ 2.2M / month Β· πŸ“¦ 690 Β· ⏱️ 05.11.2023): ``` pip install geojson ``` -- [Conda](https://anaconda.org/conda-forge/geojson) (πŸ“₯ 810K Β· ⏱️ 06.11.2023): +- [Conda](https://anaconda.org/conda-forge/geojson) (πŸ“₯ 840K Β· ⏱️ 06.11.2023): ``` conda install -c conda-forge geojson ```
-
GeoViews (πŸ₯‰29 Β· ⭐ 570) - Simple, concise geographical visualization in Python. BSD-3 +
GeoViews (πŸ₯‰29 Β· ⭐ 590) - Simple, concise geographical visualization in Python. BSD-3 -- [GitHub](https://github.com/holoviz/geoviews) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 75 Β· πŸ“¦ 1K Β· πŸ“‹ 340 - 31% open Β· ⏱️ 03.06.2024): +- [GitHub](https://github.com/holoviz/geoviews) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 75 Β· πŸ“¦ 1.1K Β· πŸ“‹ 340 - 30% open Β· ⏱️ 01.08.2024): ``` git clone https://github.com/holoviz/geoviews ``` -- [PyPi](https://pypi.org/project/geoviews) (πŸ“₯ 13K / month Β· πŸ“¦ 56 Β· ⏱️ 05.04.2024): +- [PyPi](https://pypi.org/project/geoviews) (πŸ“₯ 14K / month Β· πŸ“¦ 57 Β· ⏱️ 02.08.2024): ``` pip install geoviews ``` -- [Conda](https://anaconda.org/conda-forge/geoviews) (πŸ“₯ 220K Β· ⏱️ 05.04.2024): +- [Conda](https://anaconda.org/conda-forge/geoviews) (πŸ“₯ 240K Β· ⏱️ 05.04.2024): ``` conda install -c conda-forge geoviews ```
-
EarthPy (πŸ₯‰27 Β· ⭐ 480 Β· πŸ’€) - A package built to support working with spatial data using open.. BSD-3 - -- [GitHub](https://github.com/earthlab/earthpy) (πŸ‘¨β€πŸ’» 44 Β· πŸ”€ 150 Β· πŸ“¦ 330 Β· πŸ“‹ 230 - 11% open Β· ⏱️ 23.08.2023): - - ``` - git clone https://github.com/earthlab/earthpy - ``` -- [PyPi](https://pypi.org/project/earthpy) (πŸ“₯ 9.7K / month Β· πŸ“¦ 17 Β· ⏱️ 01.10.2021): - ``` - pip install earthpy - ``` -- [Conda](https://anaconda.org/conda-forge/earthpy) (πŸ“₯ 77K Β· ⏱️ 16.06.2023): - ``` - conda install -c conda-forge earthpy - ``` -
-
pymap3d (πŸ₯‰25 Β· ⭐ 370) - pure-Python (Numpy optional) 3D coordinate conversions for geospace ecef.. BSD-2 +
pymap3d (πŸ₯‰23 Β· ⭐ 380 Β· πŸ’€) - pure-Python (Numpy optional) 3D coordinate conversions for geospace.. BSD-2 -- [GitHub](https://github.com/geospace-code/pymap3d) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 85 Β· πŸ“¦ 410 Β· πŸ“‹ 56 - 12% open Β· ⏱️ 11.02.2024): +- [GitHub](https://github.com/geospace-code/pymap3d) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 87 Β· πŸ“¦ 430 Β· πŸ“‹ 58 - 15% open Β· ⏱️ 11.02.2024): ``` git clone https://github.com/geospace-code/pymap3d ``` -- [PyPi](https://pypi.org/project/pymap3d) (πŸ“₯ 140K / month Β· πŸ“¦ 43 Β· ⏱️ 11.02.2024): +- [PyPi](https://pypi.org/project/pymap3d) (πŸ“₯ 190K / month Β· πŸ“¦ 44 Β· ⏱️ 11.02.2024): ``` pip install pymap3d ``` -- [Conda](https://anaconda.org/conda-forge/pymap3d) (πŸ“₯ 72K Β· ⏱️ 11.02.2024): +- [Conda](https://anaconda.org/conda-forge/pymap3d) (πŸ“₯ 80K Β· ⏱️ 11.02.2024): ``` conda install -c conda-forge pymap3d ```
-
Show 7 hidden projects... +
Show 8 hidden projects... -- Geocoder (πŸ₯‰33 Β· ⭐ 1.6K Β· πŸ’€) - Python Geocoder. MIT +- Geocoder (πŸ₯‰32 Β· ⭐ 1.6K Β· πŸ’€) - Python Geocoder. MIT - Satpy (πŸ₯‰32 Β· ⭐ 1K) - Python package for earth-observing satellite data processing. ❗️GPL-3.0 -- Sentinelsat (πŸ₯‰26 Β· ⭐ 960) - Search and download Copernicus Sentinel satellite images. ❗️GPL-3.0 +- Sentinelsat (πŸ₯‰26 Β· ⭐ 970 Β· πŸ’€) - Search and download Copernicus Sentinel satellite images. ❗️GPL-3.0 +- EarthPy (πŸ₯‰26 Β· ⭐ 490 Β· πŸ’€) - A package built to support working with spatial data using open.. BSD-3 +- prettymaps (πŸ₯‰24 Β· ⭐ 11K) - A small set of Python functions to draw pretty maps from.. ❗️AGPL-3.0 - Mapbox GL (πŸ₯‰24 Β· ⭐ 660 Β· πŸ’€) - Use Mapbox GL JS to visualize data in a Python Jupyter notebook. MIT -- prettymaps (πŸ₯‰23 Β· ⭐ 11K Β· πŸ’€) - A small set of Python functions to draw pretty maps from.. ❗️AGPL-3.0 -- gmaps (πŸ₯‰23 Β· ⭐ 760 Β· πŸ’€) - Google maps for Jupyter notebooks. BSD-3 -- geoplotlib (πŸ₯‰21 Β· ⭐ 1K Β· πŸ’€) - python toolbox for visualizing geographical data and making maps. MIT +- gmaps (πŸ₯‰22 Β· ⭐ 760 Β· πŸ’€) - Google maps for Jupyter notebooks. BSD-3 +- geoplotlib (πŸ₯‰20 Β· ⭐ 1K Β· πŸ’€) - python toolbox for visualizing geographical data and making maps. MIT

@@ -3531,193 +3488,182 @@ _Libraries to load, process, analyze, and write geographic data as well as libra _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, technical analysis, and other tasks on financial data._ -
yfinance (πŸ₯‡40 Β· ⭐ 12K) - Download market data from Yahoo! Finances API. Apache-2 +
yfinance (πŸ₯‡41 Β· ⭐ 13K) - Download market data from Yahoo! Finances API. Apache-2 -- [GitHub](https://github.com/ranaroussi/yfinance) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 2.2K Β· πŸ“¦ 39K Β· πŸ“‹ 1.3K - 12% open Β· ⏱️ 04.06.2024): +- [GitHub](https://github.com/ranaroussi/yfinance) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 2.3K Β· πŸ“¦ 46K Β· πŸ“‹ 1.3K - 13% open Β· ⏱️ 26.08.2024): ``` git clone https://github.com/ranaroussi/yfinance ``` -- [PyPi](https://pypi.org/project/yfinance) (πŸ“₯ 1.7M / month Β· πŸ“¦ 560 Β· ⏱️ 19.05.2024): +- [PyPi](https://pypi.org/project/yfinance) (πŸ“₯ 2M / month Β· πŸ“¦ 630 Β· ⏱️ 24.08.2024): ``` pip install yfinance ``` -- [Conda](https://anaconda.org/ranaroussi/yfinance) (πŸ“₯ 91K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/ranaroussi/yfinance) (πŸ“₯ 94K Β· ⏱️ 16.06.2023): ``` conda install -c ranaroussi yfinance ```
-
Qlib (πŸ₯‡31 Β· ⭐ 14K) - Qlib is an AI-oriented quantitative investment platform that aims to.. MIT +
Qlib (πŸ₯‡31 Β· ⭐ 15K) - Qlib is an AI-oriented quantitative investment platform that aims to.. MIT -- [GitHub](https://github.com/microsoft/qlib) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 2.5K Β· πŸ“₯ 580 Β· πŸ“¦ 21 Β· πŸ“‹ 910 - 24% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/microsoft/qlib) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 2.6K Β· πŸ“₯ 680 Β· πŸ“¦ 21 Β· πŸ“‹ 930 - 25% open Β· ⏱️ 30.08.2024): ``` git clone https://github.com/microsoft/qlib ``` -- [PyPi](https://pypi.org/project/pyqlib) (πŸ“₯ 3.9K / month Β· πŸ“¦ 1 Β· ⏱️ 24.05.2024): +- [PyPi](https://pypi.org/project/pyqlib) (πŸ“₯ 1.9K / month Β· πŸ“¦ 1 Β· ⏱️ 24.05.2024): ``` pip install pyqlib ```
-
ta (πŸ₯ˆ30 Β· ⭐ 4.1K Β· πŸ’€) - Technical Analysis Library using Pandas and Numpy. MIT +
ta (πŸ₯‡31 Β· ⭐ 4.2K Β· πŸ’€) - Technical Analysis Library using Pandas and Numpy. MIT -- [GitHub](https://github.com/bukosabino/ta) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 840 Β· πŸ“¦ 3.5K Β· πŸ“‹ 240 - 56% open Β· ⏱️ 02.11.2023): +- [GitHub](https://github.com/bukosabino/ta) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 860 Β· πŸ“¦ 4K Β· πŸ“‹ 240 - 56% open Β· ⏱️ 02.11.2023): ``` git clone https://github.com/bukosabino/ta ``` -- [PyPi](https://pypi.org/project/ta) (πŸ“₯ 130K / month Β· πŸ“¦ 89 Β· ⏱️ 02.11.2023): +- [PyPi](https://pypi.org/project/ta) (πŸ“₯ 160K / month Β· πŸ“¦ 100 Β· ⏱️ 02.11.2023): ``` pip install ta ``` -- [Conda](https://anaconda.org/conda-forge/ta) (πŸ“₯ 26K Β· ⏱️ 02.11.2023): +- [Conda](https://anaconda.org/conda-forge/ta) (πŸ“₯ 29K Β· ⏱️ 02.11.2023): ``` conda install -c conda-forge ta ```
-
ffn (πŸ₯ˆ29 Β· ⭐ 1.8K) - ffn - a financial function library for Python. MIT +
bt (πŸ₯‡31 Β· ⭐ 2.2K Β· πŸ“ˆ) - bt - flexible backtesting for Python. MIT -- [GitHub](https://github.com/pmorissette/ffn) (πŸ‘¨β€πŸ’» 33 Β· πŸ”€ 280 Β· πŸ“¦ 460 Β· πŸ“‹ 120 - 17% open Β· ⏱️ 09.05.2024): +- [GitHub](https://github.com/pmorissette/bt) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 410 Β· πŸ“¦ 1.6K Β· πŸ“‹ 340 - 22% open Β· ⏱️ 06.08.2024): ``` - git clone https://github.com/pmorissette/ffn + git clone https://github.com/pmorissette/bt ``` -- [PyPi](https://pypi.org/project/ffn) (πŸ“₯ 150K / month Β· πŸ“¦ 16 Β· ⏱️ 31.12.2023): +- [PyPi](https://pypi.org/project/bt) (πŸ“₯ 7.2K / month Β· πŸ“¦ 10 Β· ⏱️ 06.08.2024): ``` - pip install ffn + pip install bt ``` -- [Conda](https://anaconda.org/conda-forge/ffn) (πŸ“₯ 7.6K Β· ⏱️ 31.12.2023): +- [Conda](https://anaconda.org/conda-forge/bt) (πŸ“₯ 41K Β· ⏱️ 06.08.2024): ``` - conda install -c conda-forge ffn + conda install -c conda-forge bt ```
-
Alpha Vantage (πŸ₯ˆ28 Β· ⭐ 4.2K) - A python wrapper for Alpha Vantage API for financial data. MIT +
Alpha Vantage (πŸ₯ˆ29 Β· ⭐ 4.2K) - A python wrapper for Alpha Vantage API for financial data. MIT -- [GitHub](https://github.com/RomelTorres/alpha_vantage) (πŸ‘¨β€πŸ’» 43 Β· πŸ”€ 720 Β· πŸ“¦ 580 Β· πŸ“‹ 290 - 2% open Β· ⏱️ 19.03.2024): +- [GitHub](https://github.com/RomelTorres/alpha_vantage) (πŸ‘¨β€πŸ’» 44 Β· πŸ”€ 740 Β· πŸ“‹ 290 - 0% open Β· ⏱️ 18.07.2024): ``` git clone https://github.com/RomelTorres/alpha_vantage ``` -- [PyPi](https://pypi.org/project/alpha_vantage) (πŸ“₯ 47K / month Β· πŸ“¦ 33 Β· ⏱️ 21.12.2020): +- [PyPi](https://pypi.org/project/alpha_vantage) (πŸ“₯ 33K / month Β· πŸ“¦ 35 Β· ⏱️ 18.07.2024): ``` pip install alpha_vantage ``` -- [Conda](https://anaconda.org/conda-forge/alpha_vantage) (πŸ“₯ 6.8K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/alpha_vantage) (πŸ“₯ 7.3K Β· ⏱️ 09.08.2024): ``` conda install -c conda-forge alpha_vantage ```
-
TensorTrade (πŸ₯ˆ27 Β· ⭐ 4.4K) - An open source reinforcement learning framework for training,.. Apache-2 +
ffn (πŸ₯ˆ29 Β· ⭐ 1.9K) - ffn - a financial function library for Python. MIT -- [GitHub](https://github.com/tensortrade-org/tensortrade) (πŸ‘¨β€πŸ’» 61 Β· πŸ”€ 980 Β· πŸ“¦ 56 Β· πŸ“‹ 250 - 20% open Β· ⏱️ 27.05.2024): +- [GitHub](https://github.com/pmorissette/ffn) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 280 Β· πŸ“¦ 490 Β· πŸ“‹ 130 - 18% open Β· ⏱️ 06.08.2024): ``` - git clone https://github.com/tensortrade-org/tensortrade + git clone https://github.com/pmorissette/ffn ``` -- [PyPi](https://pypi.org/project/tensortrade) (πŸ“₯ 790 / month Β· πŸ“¦ 1 Β· ⏱️ 10.05.2021): +- [PyPi](https://pypi.org/project/ffn) (πŸ“₯ 48K / month Β· πŸ“¦ 16 Β· ⏱️ 05.08.2024): ``` - pip install tensortrade + pip install ffn ``` -- [Conda](https://anaconda.org/conda-forge/tensortrade) (πŸ“₯ 3.5K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/ffn) (πŸ“₯ 11K Β· ⏱️ 06.08.2024): ``` - conda install -c conda-forge tensortrade + conda install -c conda-forge ffn ```
-
bt (πŸ₯ˆ27 Β· ⭐ 2.1K) - bt - flexible backtesting for Python. MIT +
IB-insync (πŸ₯‰27 Β· ⭐ 2.8K) - Python sync/async framework for Interactive Brokers API. BSD-2 -- [GitHub](https://github.com/pmorissette/bt) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 400 Β· πŸ“¦ 1.6K Β· πŸ“‹ 340 - 23% open Β· ⏱️ 04.04.2024): +- [GitHub](https://github.com/erdewit/ib_insync) (πŸ‘¨β€πŸ’» 36 Β· πŸ”€ 740 Β· πŸ“‹ 590 - 3% open Β· ⏱️ 14.03.2024): ``` - git clone https://github.com/pmorissette/bt + git clone https://github.com/erdewit/ib_insync ``` -- [PyPi](https://pypi.org/project/bt) (πŸ“₯ 7.1K / month Β· πŸ“¦ 10 Β· ⏱️ 20.11.2023): +- [PyPi](https://pypi.org/project/ib_insync) (πŸ“₯ 32K / month Β· πŸ“¦ 44 Β· ⏱️ 21.11.2022): ``` - pip install bt + pip install ib_insync ``` -- [Conda](https://anaconda.org/conda-forge/bt) (πŸ“₯ 25K Β· ⏱️ 20.11.2023): +- [Conda](https://anaconda.org/conda-forge/ib-insync) (πŸ“₯ 46K Β· ⏱️ 16.06.2023): ``` - conda install -c conda-forge bt + conda install -c conda-forge ib-insync ```
-
IB-insync (πŸ₯‰25 Β· ⭐ 2.7K) - Python sync/async framework for Interactive Brokers API. BSD-2 +
TensorTrade (πŸ₯‰24 Β· ⭐ 4.5K) - An open source reinforcement learning framework for training,.. Apache-2 -- [GitHub](https://github.com/erdewit/ib_insync) (πŸ‘¨β€πŸ’» 36 Β· πŸ”€ 700 Β· πŸ“‹ 590 - 3% open Β· ⏱️ 14.03.2024): +- [GitHub](https://github.com/tensortrade-org/tensortrade) (πŸ‘¨β€πŸ’» 61 Β· πŸ”€ 980 Β· πŸ“¦ 60 Β· πŸ“‹ 250 - 20% open Β· ⏱️ 09.06.2024): ``` - git clone https://github.com/erdewit/ib_insync + git clone https://github.com/tensortrade-org/tensortrade ``` -- [PyPi](https://pypi.org/project/ib_insync) (πŸ“₯ 33K / month Β· πŸ“¦ 40 Β· ⏱️ 21.11.2022): +- [PyPi](https://pypi.org/project/tensortrade) (πŸ“₯ 700 / month Β· πŸ“¦ 1 Β· ⏱️ 10.05.2021): ``` - pip install ib_insync + pip install tensortrade ``` -- [Conda](https://anaconda.org/conda-forge/ib-insync) (πŸ“₯ 41K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/tensortrade) (πŸ“₯ 3.9K Β· ⏱️ 16.06.2023): ``` - conda install -c conda-forge ib-insync + conda install -c conda-forge tensortrade ```
-
stockstats (πŸ₯‰25 Β· ⭐ 1.2K) - Supply a wrapper ``StockDataFrame`` based on the.. BSD-3 +
stockstats (πŸ₯‰24 Β· ⭐ 1.3K Β· πŸ’€) - Supply a wrapper ``StockDataFrame`` based on the.. BSD-3 -- [GitHub](https://github.com/jealous/stockstats) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 300 Β· πŸ“¦ 1.1K Β· πŸ“‹ 120 - 12% open Β· ⏱️ 05.01.2024): +- [GitHub](https://github.com/jealous/stockstats) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 300 Β· πŸ“¦ 1.1K Β· πŸ“‹ 130 - 12% open Β· ⏱️ 05.01.2024): ``` git clone https://github.com/jealous/stockstats ``` -- [PyPi](https://pypi.org/project/stockstats) (πŸ“₯ 10K / month Β· πŸ“¦ 11 Β· ⏱️ 30.07.2023): +- [PyPi](https://pypi.org/project/stockstats) (πŸ“₯ 8K / month Β· πŸ“¦ 11 Β· ⏱️ 30.07.2023): ``` pip install stockstats ```
-
finmarketpy (πŸ₯‰23 Β· ⭐ 3.4K) - Python library for backtesting trading strategies & analyzing.. Apache-2 +
finmarketpy (πŸ₯‰22 Β· ⭐ 3.4K) - Python library for backtesting trading strategies & analyzing.. Apache-2 -- [GitHub](https://github.com/cuemacro/finmarketpy) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 490 Β· πŸ“₯ 51 Β· πŸ“¦ 13 Β· πŸ“‹ 28 - 85% open Β· ⏱️ 19.05.2024): +- [GitHub](https://github.com/cuemacro/finmarketpy) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 490 Β· πŸ“₯ 54 Β· πŸ“¦ 14 Β· πŸ“‹ 28 - 85% open Β· ⏱️ 19.05.2024): ``` git clone https://github.com/cuemacro/finmarketpy ``` -- [PyPi](https://pypi.org/project/finmarketpy) (πŸ“₯ 360 / month Β· ⏱️ 19.05.2024): +- [PyPi](https://pypi.org/project/finmarketpy) (πŸ“₯ 290 / month Β· ⏱️ 19.05.2024): ``` pip install finmarketpy ```
-
FinQuant (πŸ₯‰22 Β· ⭐ 1.3K Β· πŸ’€) - A program for financial portfolio management, analysis and.. MIT +
FinQuant (πŸ₯‰22 Β· ⭐ 1.4K Β· πŸ’€) - A program for financial portfolio management, analysis and.. MIT -- [GitHub](https://github.com/fmilthaler/FinQuant) (πŸ‘¨β€πŸ’» 11 Β· πŸ”€ 180 Β· πŸ“¦ 92 Β· πŸ“‹ 48 - 33% open Β· ⏱️ 03.09.2023): +- [GitHub](https://github.com/fmilthaler/FinQuant) (πŸ‘¨β€πŸ’» 11 Β· πŸ”€ 180 Β· πŸ“¦ 93 Β· πŸ“‹ 49 - 32% open Β· ⏱️ 03.09.2023): ``` git clone https://github.com/fmilthaler/FinQuant ``` -- [PyPi](https://pypi.org/project/FinQuant) (πŸ“₯ 590 / month Β· πŸ“¦ 1 Β· ⏱️ 04.09.2023): +- [PyPi](https://pypi.org/project/FinQuant) (πŸ“₯ 380 / month Β· πŸ“¦ 1 Β· ⏱️ 04.09.2023): ``` pip install FinQuant ```
-
tf-quant-finance (πŸ₯‰21 Β· ⭐ 4.3K Β· πŸ’€) - High-performance TensorFlow library for quantitative.. Apache-2 - -- [GitHub](https://github.com/google/tf-quant-finance) (πŸ‘¨β€πŸ’» 47 Β· πŸ”€ 540 Β· πŸ“‹ 65 - 56% open Β· ⏱️ 15.08.2023): - - ``` - git clone https://github.com/google/tf-quant-finance - ``` -- [PyPi](https://pypi.org/project/tf-quant-finance) (πŸ“₯ 530 / month Β· πŸ“¦ 2 Β· ⏱️ 19.08.2022): - ``` - pip install tf-quant-finance - ``` -
-
Show 13 hidden projects... +
Show 14 hidden projects... - zipline (πŸ₯‡32 Β· ⭐ 17K Β· πŸ’€) - Zipline, a Pythonic Algorithmic Trading Library. Apache-2 -- pyfolio (πŸ₯‡31 Β· ⭐ 5.5K Β· πŸ’€) - Portfolio and risk analytics in Python. Apache-2 - arch (πŸ₯‡31 Β· ⭐ 1.3K) - ARCH models in Python. ❗Unlicensed -- backtrader (πŸ₯ˆ29 Β· ⭐ 13K Β· πŸ’€) - Python Backtesting library for trading strategies. ❗️GPL-3.0 -- empyrical (πŸ₯ˆ27 Β· ⭐ 1.2K Β· πŸ’€) - Common financial risk and performance metrics. Used by.. Apache-2 -- Alphalens (πŸ₯‰26 Β· ⭐ 3.1K Β· πŸ’€) - Performance analysis of predictive (alpha) stock factors. Apache-2 -- Enigma Catalyst (πŸ₯‰25 Β· ⭐ 2.5K Β· πŸ’€) - An Algorithmic Trading Library for Crypto-Assets in.. Apache-2 +- pyfolio (πŸ₯ˆ30 Β· ⭐ 5.6K Β· πŸ’€) - Portfolio and risk analytics in Python. Apache-2 +- backtrader (πŸ₯ˆ29 Β· ⭐ 14K Β· πŸ’€) - Python Backtesting library for trading strategies. ❗️GPL-3.0 +- empyrical (πŸ₯‰28 Β· ⭐ 1.3K Β· πŸ’€) - Common financial risk and performance metrics. Used by.. Apache-2 +- Alphalens (πŸ₯‰27 Β· ⭐ 3.3K Β· πŸ’€) - Performance analysis of predictive (alpha) stock factors. Apache-2 +- Enigma Catalyst (πŸ₯‰26 Β· ⭐ 2.5K Β· πŸ’€) - An Algorithmic Trading Library for Crypto-Assets in.. Apache-2 +- PyAlgoTrade (πŸ₯‰25 Β· ⭐ 4.4K Β· πŸ’€) - Python Algorithmic Trading Library. Apache-2 - FinTA (πŸ₯‰24 Β· ⭐ 2.1K Β· πŸ’€) - Common financial technical indicators implemented in Pandas. ❗️LGPL-3.0 -- PyAlgoTrade (πŸ₯‰23 Β· ⭐ 4.3K Β· πŸ’€) - Python Algorithmic Trading Library. Apache-2 -- Backtesting.py (πŸ₯‰22 Β· ⭐ 4.9K Β· πŸ’€) - Backtest trading strategies in Python. ❗️AGPL-3.0 -- Crypto Signals (πŸ₯‰22 Β· ⭐ 4.8K Β· πŸ’€) - Github.com/CryptoSignal - Trading & Technical Analysis Bot -.. MIT -- surpriver (πŸ₯‰12 Β· ⭐ 1.7K Β· πŸ’€) - Find big moving stocks before they move using machine.. ❗️GPL-3.0 -- pyrtfolio (πŸ₯‰8 Β· ⭐ 140 Β· πŸ’€) - Python package to generate stock portfolios. ❗️GPL-3.0 +- Backtesting.py (πŸ₯‰23 Β· ⭐ 5.3K Β· πŸ’€) - Backtest trading strategies in Python. ❗️AGPL-3.0 +- Crypto Signals (πŸ₯‰23 Β· ⭐ 4.8K Β· πŸ’€) - Github.com/CryptoSignal - Trading & Technical Analysis Bot -.. MIT +- tf-quant-finance (πŸ₯‰21 Β· ⭐ 4.4K Β· πŸ’€) - High-performance TensorFlow library for quantitative.. Apache-2 +- surpriver (πŸ₯‰12 Β· ⭐ 1.8K Β· πŸ’€) - Find big moving stocks before they move using machine.. ❗️GPL-3.0 +- pyrtfolio (πŸ₯‰8 Β· ⭐ 150 Β· πŸ’€) - Python package to generate stock portfolios. ❗️GPL-3.0

@@ -3727,317 +3673,302 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te _Libraries for forecasting, anomaly detection, feature extraction, and machine learning on time-series and sequential data._ -
sktime (πŸ₯‡39 Β· ⭐ 7.5K) - A unified framework for machine learning with time series. BSD-3 +
sktime (πŸ₯‡39 Β· ⭐ 7.7K) - A unified framework for machine learning with time series. BSD-3 -- [GitHub](https://github.com/sktime/sktime) (πŸ‘¨β€πŸ’» 360 Β· πŸ”€ 1.3K Β· πŸ“₯ 91 Β· πŸ“¦ 2.8K Β· πŸ“‹ 2.3K - 35% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/sktime/sktime) (πŸ‘¨β€πŸ’» 390 Β· πŸ”€ 1.3K Β· πŸ“₯ 96 Β· πŸ“¦ 3.2K Β· πŸ“‹ 2.5K - 37% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/alan-turing-institute/sktime ``` -- [PyPi](https://pypi.org/project/sktime) (πŸ“₯ 800K / month Β· πŸ“¦ 120 Β· ⏱️ 04.06.2024): +- [PyPi](https://pypi.org/project/sktime) (πŸ“₯ 700K / month Β· πŸ“¦ 120 Β· ⏱️ 27.08.2024): ``` pip install sktime ``` -- [Conda](https://anaconda.org/conda-forge/sktime-all-extras) (πŸ“₯ 960K Β· ⏱️ 05.06.2024): +- [Conda](https://anaconda.org/conda-forge/sktime-all-extras) (πŸ“₯ 1M Β· ⏱️ 27.08.2024): ``` conda install -c conda-forge sktime-all-extras ```
-
Prophet (πŸ₯‡34 Β· ⭐ 18K) - Tool for producing high quality forecasts for time series data that has.. MIT +
StatsForecast (πŸ₯‡34 Β· ⭐ 3.8K) - Lightning fast forecasting with statistical and econometric.. Apache-2 -- [GitHub](https://github.com/facebook/prophet) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 4.5K Β· πŸ“₯ 2.5K Β· πŸ“¦ 21 Β· πŸ“‹ 2.1K - 18% open Β· ⏱️ 18.05.2024): +- [GitHub](https://github.com/Nixtla/statsforecast) (πŸ‘¨β€πŸ’» 43 Β· πŸ”€ 270 Β· πŸ“¦ 1.1K Β· πŸ“‹ 330 - 29% open Β· ⏱️ 03.09.2024): ``` - git clone https://github.com/facebook/prophet + git clone https://github.com/Nixtla/statsforecast ``` -- [PyPi](https://pypi.org/project/fbprophet) (πŸ“₯ 830K / month Β· πŸ“¦ 89 Β· ⏱️ 05.09.2020): +- [PyPi](https://pypi.org/project/statsforecast) (πŸ“₯ 770K / month Β· πŸ“¦ 57 Β· ⏱️ 17.07.2024): ``` - pip install fbprophet + pip install statsforecast ``` -- [Conda](https://anaconda.org/conda-forge/prophet) (πŸ“₯ 1.2M Β· ⏱️ 20.10.2023): +- [Conda](https://anaconda.org/conda-forge/statsforecast) (πŸ“₯ 89K Β· ⏱️ 18.07.2024): ``` - conda install -c conda-forge prophet + conda install -c conda-forge statsforecast ```
-
StatsForecast (πŸ₯‡34 Β· ⭐ 3.6K) - Lightning fast forecasting with statistical and econometric.. Apache-2 +
STUMPY (πŸ₯‡34 Β· ⭐ 3.6K) - STUMPY is a powerful and scalable Python library for modern time series.. BSD-3 -- [GitHub](https://github.com/Nixtla/statsforecast) (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 250 Β· πŸ“¦ 920 Β· πŸ“‹ 320 - 30% open Β· ⏱️ 30.05.2024): +- [GitHub](https://github.com/TDAmeritrade/stumpy) (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 320 Β· πŸ“¦ 860 Β· πŸ“‹ 510 - 12% open Β· ⏱️ 16.08.2024): ``` - git clone https://github.com/Nixtla/statsforecast + git clone https://github.com/TDAmeritrade/stumpy ``` -- [PyPi](https://pypi.org/project/statsforecast) (πŸ“₯ 590K / month Β· πŸ“¦ 55 Β· ⏱️ 24.05.2024): +- [PyPi](https://pypi.org/project/stumpy) (πŸ“₯ 330K / month Β· πŸ“¦ 30 Β· ⏱️ 09.07.2024): ``` - pip install statsforecast + pip install stumpy ``` -- [Conda](https://anaconda.org/conda-forge/statsforecast) (πŸ“₯ 71K Β· ⏱️ 24.05.2024): +- [Conda](https://anaconda.org/conda-forge/stumpy) (πŸ“₯ 1M Β· ⏱️ 09.07.2024): ``` - conda install -c conda-forge statsforecast + conda install -c conda-forge stumpy ```
-
Darts (πŸ₯ˆ33 Β· ⭐ 7.4K) - A python library for user-friendly forecasting and anomaly detection.. Apache-2 +
Prophet (πŸ₯ˆ33 Β· ⭐ 18K) - Tool for producing high quality forecasts for time series data that has.. MIT -- [GitHub](https://github.com/unit8co/darts) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 800 Β· πŸ“¦ 630 Β· πŸ“‹ 1.4K - 18% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/facebook/prophet) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 4.5K Β· πŸ“₯ 2.7K Β· πŸ“¦ 21 Β· πŸ“‹ 2.1K - 19% open Β· ⏱️ 18.05.2024): ``` - git clone https://github.com/unit8co/darts - ``` -- [PyPi](https://pypi.org/project/u8darts) (πŸ“₯ 24K / month Β· πŸ“¦ 6 Β· ⏱️ 17.04.2024): - ``` - pip install u8darts + git clone https://github.com/facebook/prophet ``` -- [Conda](https://anaconda.org/conda-forge/u8darts-all) (πŸ“₯ 46K Β· ⏱️ 18.04.2024): +- [PyPi](https://pypi.org/project/fbprophet) (πŸ“₯ 310K / month Β· πŸ“¦ 91 Β· ⏱️ 05.09.2020): ``` - conda install -c conda-forge u8darts-all + pip install fbprophet ``` -- [Docker Hub](https://hub.docker.com/r/unit8/darts) (πŸ“₯ 590 Β· ⏱️ 17.04.2024): +- [Conda](https://anaconda.org/conda-forge/prophet) (πŸ“₯ 1.2M Β· ⏱️ 20.10.2023): ``` - docker pull unit8/darts + conda install -c conda-forge prophet ```
-
tsfresh (πŸ₯ˆ32 Β· ⭐ 8.2K) - Automatic extraction of relevant features from time series:. MIT +
tsfresh (πŸ₯ˆ32 Β· ⭐ 8.3K) - Automatic extraction of relevant features from time series:. MIT -- [GitHub](https://github.com/blue-yonder/tsfresh) (πŸ‘¨β€πŸ’» 94 Β· πŸ”€ 1.2K Β· πŸ“¦ 21 Β· πŸ“‹ 540 - 12% open Β· ⏱️ 26.05.2024): +- [GitHub](https://github.com/blue-yonder/tsfresh) (πŸ‘¨β€πŸ’» 96 Β· πŸ”€ 1.2K Β· πŸ“¦ 21 Β· πŸ“‹ 540 - 12% open Β· ⏱️ 03.08.2024): ``` git clone https://github.com/blue-yonder/tsfresh ``` -- [PyPi](https://pypi.org/project/tsfresh) (πŸ“₯ 250K / month Β· πŸ“¦ 75 Β· ⏱️ 28.01.2024): +- [PyPi](https://pypi.org/project/tsfresh) (πŸ“₯ 280K / month Β· πŸ“¦ 92 Β· ⏱️ 03.08.2024): ``` pip install tsfresh ``` -- [Conda](https://anaconda.org/conda-forge/tsfresh) (πŸ“₯ 1.4M Β· ⏱️ 28.01.2024): +- [Conda](https://anaconda.org/conda-forge/tsfresh) (πŸ“₯ 1.4M Β· ⏱️ 04.08.2024): ``` conda install -c conda-forge tsfresh ```
-
pmdarima (πŸ₯ˆ32 Β· ⭐ 1.5K) - A statistical library designed to fill the void in Pythons time series.. MIT +
pmdarima (πŸ₯ˆ32 Β· ⭐ 1.6K Β· πŸ’€) - A statistical library designed to fill the void in Pythons time.. MIT -- [GitHub](https://github.com/alkaline-ml/pmdarima) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 230 Β· πŸ“¦ 8.3K Β· πŸ“‹ 330 - 17% open Β· ⏱️ 23.02.2024): +- [GitHub](https://github.com/alkaline-ml/pmdarima) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 230 Β· πŸ“¦ 9.1K Β· πŸ“‹ 330 - 18% open Β· ⏱️ 23.02.2024): ``` git clone https://github.com/alkaline-ml/pmdarima ``` -- [PyPi](https://pypi.org/project/pmdarima) (πŸ“₯ 2.4M / month Β· πŸ“¦ 140 Β· ⏱️ 23.10.2023): +- [PyPi](https://pypi.org/project/pmdarima) (πŸ“₯ 2.2M / month Β· πŸ“¦ 150 Β· ⏱️ 23.10.2023): ``` pip install pmdarima ``` -- [Conda](https://anaconda.org/conda-forge/pmdarima) (πŸ“₯ 1.1M Β· ⏱️ 19.04.2024): +- [Conda](https://anaconda.org/conda-forge/pmdarima) (πŸ“₯ 1.2M Β· ⏱️ 14.07.2024): ``` conda install -c conda-forge pmdarima ```
-
STUMPY (πŸ₯ˆ31 Β· ⭐ 3K) - STUMPY is a powerful and scalable Python library for modern time series.. BSD-3 +
NeuralForecast (πŸ₯ˆ31 Β· ⭐ 2.9K) - Scalable and user friendly neural forecasting algorithms. Apache-2 -- [GitHub](https://github.com/TDAmeritrade/stumpy) (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 280 Β· πŸ“¦ 770 Β· πŸ“‹ 480 - 11% open Β· ⏱️ 01.06.2024): +- [GitHub](https://github.com/Nixtla/neuralforecast) (πŸ‘¨β€πŸ’» 48 Β· πŸ”€ 330 Β· πŸ“¦ 200 Β· πŸ“‹ 530 - 20% open Β· ⏱️ 02.09.2024): ``` - git clone https://github.com/TDAmeritrade/stumpy + git clone https://github.com/Nixtla/neuralforecast ``` -- [PyPi](https://pypi.org/project/stumpy) (πŸ“₯ 240K / month Β· πŸ“¦ 23 Β· ⏱️ 21.08.2023): +- [PyPi](https://pypi.org/project/neuralforecast) (πŸ“₯ 39K / month Β· πŸ“¦ 16 Β· ⏱️ 30.07.2024): ``` - pip install stumpy + pip install neuralforecast ``` -- [Conda](https://anaconda.org/conda-forge/stumpy) (πŸ“₯ 990K Β· ⏱️ 21.08.2023): +- [Conda](https://anaconda.org/conda-forge/neuralforecast) (πŸ“₯ 21K Β· ⏱️ 31.07.2024): ``` - conda install -c conda-forge stumpy + conda install -c conda-forge neuralforecast ```
-
GluonTS (πŸ₯ˆ30 Β· ⭐ 4.4K) - Probabilistic time series modeling in Python. Apache-2 +
Darts (πŸ₯ˆ30 Β· ⭐ 7.9K) - A python library for user-friendly forecasting and anomaly detection.. Apache-2 -- [GitHub](https://github.com/awslabs/gluonts) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 740 Β· πŸ“‹ 940 - 33% open Β· ⏱️ 31.05.2024): +- [GitHub](https://github.com/unit8co/darts) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 850 Β· πŸ“‹ 1.5K - 16% open Β· ⏱️ 02.09.2024): ``` - git clone https://github.com/awslabs/gluon-ts - ``` -- [PyPi](https://pypi.org/project/gluonts) (πŸ“₯ 240K / month Β· πŸ“¦ 27 Β· ⏱️ 03.06.2024): - ``` - pip install gluonts + git clone https://github.com/unit8co/darts ``` -- [Conda](https://anaconda.org/anaconda/gluonts) (πŸ“₯ 770 Β· ⏱️ 22.12.2023): +- [PyPi](https://pypi.org/project/u8darts) (πŸ“₯ 53K / month Β· πŸ“¦ 10 Β· ⏱️ 19.06.2024): ``` - conda install -c anaconda gluonts + pip install u8darts ``` -
-
NeuralProphet (πŸ₯ˆ30 Β· ⭐ 3.7K) - NeuralProphet: A simple forecasting package. MIT - -- [GitHub](https://github.com/ourownstory/neural_prophet) (πŸ‘¨β€πŸ’» 53 Β· πŸ”€ 460 Β· πŸ“¦ 450 Β· πŸ“‹ 520 - 8% open Β· ⏱️ 15.03.2024): - +- [Conda](https://anaconda.org/conda-forge/u8darts-all) (πŸ“₯ 56K Β· ⏱️ 21.06.2024): ``` - git clone https://github.com/ourownstory/neural_prophet + conda install -c conda-forge u8darts-all ``` -- [PyPi](https://pypi.org/project/neuralprophet) (πŸ“₯ 180K / month Β· πŸ“¦ 5 Β· ⏱️ 23.02.2024): +- [Docker Hub](https://hub.docker.com/r/unit8/darts) (πŸ“₯ 630 Β· ⏱️ 17.04.2024): ``` - pip install neuralprophet + docker pull unit8/darts ```
-
tslearn (πŸ₯ˆ30 Β· ⭐ 2.8K) - The machine learning toolkit for time series analysis in Python. BSD-2 +
pytorch-forecasting (πŸ₯ˆ30 Β· ⭐ 3.8K) - Time series forecasting with PyTorch. MIT -- [GitHub](https://github.com/tslearn-team/tslearn) (πŸ‘¨β€πŸ’» 43 Β· πŸ”€ 320 Β· πŸ“¦ 1.3K Β· πŸ“‹ 320 - 39% open Β· ⏱️ 20.03.2024): +- [GitHub](https://github.com/jdb78/pytorch-forecasting) (πŸ‘¨β€πŸ’» 50 Β· πŸ”€ 610 Β· πŸ“‹ 790 - 63% open Β· ⏱️ 05.09.2024): ``` - git clone https://github.com/tslearn-team/tslearn + git clone https://github.com/jdb78/pytorch-forecasting ``` -- [PyPi](https://pypi.org/project/tslearn) (πŸ“₯ 390K / month Β· πŸ“¦ 71 Β· ⏱️ 12.12.2023): +- [PyPi](https://pypi.org/project/pytorch-forecasting) (πŸ“₯ 62K / month Β· πŸ“¦ 20 Β· ⏱️ 10.04.2023): ``` - pip install tslearn + pip install pytorch-forecasting ``` -- [Conda](https://anaconda.org/conda-forge/tslearn) (πŸ“₯ 1.3M Β· ⏱️ 04.02.2024): +- [Conda](https://anaconda.org/conda-forge/pytorch-forecasting) (πŸ“₯ 63K Β· ⏱️ 16.06.2023): ``` - conda install -c conda-forge tslearn + conda install -c conda-forge pytorch-forecasting ```
-
NeuralForecast (πŸ₯ˆ30 Β· ⭐ 2.6K) - Scalable and user friendly neural forecasting algorithms. Apache-2 +
tslearn (πŸ₯ˆ30 Β· ⭐ 2.9K) - The machine learning toolkit for time series analysis in Python. BSD-2 -- [GitHub](https://github.com/Nixtla/neuralforecast) (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 300 Β· πŸ“¦ 160 Β· πŸ“‹ 470 - 20% open Β· ⏱️ 30.05.2024): +- [GitHub](https://github.com/tslearn-team/tslearn) (πŸ‘¨β€πŸ’» 43 Β· πŸ”€ 340 Β· πŸ“¦ 1.4K Β· πŸ“‹ 330 - 40% open Β· ⏱️ 01.07.2024): ``` - git clone https://github.com/Nixtla/neuralforecast + git clone https://github.com/tslearn-team/tslearn ``` -- [PyPi](https://pypi.org/project/neuralforecast) (πŸ“₯ 43K / month Β· πŸ“¦ 16 Β· ⏱️ 07.05.2024): +- [PyPi](https://pypi.org/project/tslearn) (πŸ“₯ 380K / month Β· πŸ“¦ 79 Β· ⏱️ 12.12.2023): ``` - pip install neuralforecast + pip install tslearn ``` -- [Conda](https://anaconda.org/conda-forge/neuralforecast) (πŸ“₯ 16K Β· ⏱️ 08.05.2024): +- [Conda](https://anaconda.org/conda-forge/tslearn) (πŸ“₯ 1.4M Β· ⏱️ 26.07.2024): ``` - conda install -c conda-forge neuralforecast + conda install -c conda-forge tslearn ```
-
skforecast (πŸ₯ˆ28 Β· ⭐ 980) - Time series forecasting with scikit-learn models. BSD-3 +
skforecast (πŸ₯ˆ30 Β· ⭐ 1.1K) - Time series forecasting with machine learning models. BSD-3 -- [GitHub](https://github.com/JoaquinAmatRodrigo/skforecast) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 110 Β· πŸ“¦ 270 Β· πŸ“‹ 140 - 17% open Β· ⏱️ 30.05.2024): +- [GitHub](https://github.com/JoaquinAmatRodrigo/skforecast) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 120 Β· πŸ“¦ 320 Β· πŸ“‹ 170 - 10% open Β· ⏱️ 13.08.2024): ``` git clone https://github.com/JoaquinAmatRodrigo/skforecast ``` -- [PyPi](https://pypi.org/project/skforecast) (πŸ“₯ 48K / month Β· πŸ“¦ 12 Β· ⏱️ 20.05.2024): +- [PyPi](https://pypi.org/project/skforecast) (πŸ“₯ 79K / month Β· πŸ“¦ 15 Β· ⏱️ 01.08.2024): ``` pip install skforecast ```
-
pytorch-forecasting (πŸ₯‰27 Β· ⭐ 3.7K) - Time series forecasting with PyTorch. MIT +
GluonTS (πŸ₯ˆ29 Β· ⭐ 4.5K) - Probabilistic time series modeling in Python. Apache-2 -- [GitHub](https://github.com/jdb78/pytorch-forecasting) (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 580 Β· πŸ“‹ 760 - 62% open Β· ⏱️ 15.03.2024): +- [GitHub](https://github.com/awslabs/gluonts) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 740 Β· πŸ“‹ 960 - 33% open Β· ⏱️ 25.07.2024): ``` - git clone https://github.com/jdb78/pytorch-forecasting + git clone https://github.com/awslabs/gluon-ts ``` -- [PyPi](https://pypi.org/project/pytorch-forecasting) (πŸ“₯ 53K / month Β· πŸ“¦ 16 Β· ⏱️ 26.07.2020): +- [PyPi](https://pypi.org/project/gluonts) (πŸ“₯ 250K / month Β· πŸ“¦ 31 Β· ⏱️ 03.06.2024): ``` - pip install pytorch-forecasting + pip install gluonts ``` -- [Conda](https://anaconda.org/conda-forge/pytorch-forecasting) (πŸ“₯ 58K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/anaconda/gluonts) (πŸ“₯ 900 Β· ⏱️ 22.12.2023): ``` - conda install -c conda-forge pytorch-forecasting + conda install -c anaconda gluonts ```
-
uber/orbit (πŸ₯‰26 Β· ⭐ 1.8K) - A Python package for Bayesian forecasting with object-oriented.. Apache-2 +
NeuralProphet (πŸ₯ˆ29 Β· ⭐ 3.8K) - NeuralProphet: A simple forecasting package. MIT -- [GitHub](https://github.com/uber/orbit) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 140 Β· πŸ“¦ 57 Β· πŸ“‹ 400 - 12% open Β· ⏱️ 31.03.2024): +- [GitHub](https://github.com/ourownstory/neural_prophet) (πŸ‘¨β€πŸ’» 56 Β· πŸ”€ 470 Β· πŸ“‹ 550 - 10% open Β· ⏱️ 04.09.2024): ``` - git clone https://github.com/uber/orbit - ``` -- [PyPi](https://pypi.org/project/orbit-ml) (πŸ“₯ 21K / month Β· πŸ“¦ 1 Β· ⏱️ 01.04.2024): - ``` - pip install orbit-ml + git clone https://github.com/ourownstory/neural_prophet ``` -- [Conda](https://anaconda.org/conda-forge/orbit-ml) (πŸ“₯ 7.8K Β· ⏱️ 01.04.2024): +- [PyPi](https://pypi.org/project/neuralprophet) (πŸ“₯ 160K / month Β· πŸ“¦ 8 Β· ⏱️ 26.06.2024): ``` - conda install -c conda-forge orbit-ml + pip install neuralprophet ```
-
pyts (πŸ₯‰26 Β· ⭐ 1.7K Β· πŸ’€) - A Python package for time series classification. BSD-3 +
uber/orbit (πŸ₯‰25 Β· ⭐ 1.9K) - A Python package for Bayesian forecasting with object-oriented.. Apache-2 -- [GitHub](https://github.com/johannfaouzi/pyts) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 160 Β· πŸ“¦ 610 Β· πŸ“‹ 78 - 55% open Β· ⏱️ 20.06.2023): +- [GitHub](https://github.com/uber/orbit) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 140 Β· πŸ“¦ 61 Β· πŸ“‹ 400 - 12% open Β· ⏱️ 10.07.2024): ``` - git clone https://github.com/johannfaouzi/pyts + git clone https://github.com/uber/orbit ``` -- [PyPi](https://pypi.org/project/pyts) (πŸ“₯ 170K / month Β· πŸ“¦ 19 Β· ⏱️ 31.10.2021): +- [PyPi](https://pypi.org/project/orbit-ml) (πŸ“₯ 19K / month Β· πŸ“¦ 1 Β· ⏱️ 01.04.2024): ``` - pip install pyts + pip install orbit-ml ``` -- [Conda](https://anaconda.org/conda-forge/pyts) (πŸ“₯ 24K Β· ⏱️ 18.06.2023): +- [Conda](https://anaconda.org/conda-forge/orbit-ml) (πŸ“₯ 13K Β· ⏱️ 01.04.2024): ``` - conda install -c conda-forge pyts + conda install -c conda-forge orbit-ml ```
-
TSFEL (πŸ₯‰24 Β· ⭐ 870) - An intuitive library to extract features from time series. BSD-3 +
TSFEL (πŸ₯‰24 Β· ⭐ 900) - An intuitive library to extract features from time series. BSD-3 -- [GitHub](https://github.com/fraunhoferportugal/tsfel) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 130 Β· πŸ“¦ 130 Β· πŸ“‹ 69 - 4% open Β· ⏱️ 14.05.2024): +- [GitHub](https://github.com/fraunhoferportugal/tsfel) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 140 Β· πŸ“¦ 140 Β· πŸ“‹ 72 - 8% open Β· ⏱️ 27.08.2024): ``` git clone https://github.com/fraunhoferportugal/tsfel ``` -- [PyPi](https://pypi.org/project/tsfel) (πŸ“₯ 23K / month Β· πŸ“¦ 3 Β· ⏱️ 27.03.2024): +- [PyPi](https://pypi.org/project/tsfel) (πŸ“₯ 25K / month Β· πŸ“¦ 7 Β· ⏱️ 27.08.2024): ``` pip install tsfel ```
-
greykite (πŸ₯‰22 Β· ⭐ 1.8K) - A flexible, intuitive and fast forecasting library. BSD-2 +
pydlm (πŸ₯‰22 Β· ⭐ 480) - A python library for Bayesian time series modeling. BSD-3 -- [GitHub](https://github.com/linkedin/greykite) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 100 Β· πŸ“₯ 26 Β· πŸ“¦ 30 Β· πŸ“‹ 110 - 26% open Β· ⏱️ 16.01.2024): +- [GitHub](https://github.com/wwrechard/pydlm) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 98 Β· πŸ“¦ 36 Β· πŸ“‹ 56 - 73% open Β· ⏱️ 30.08.2024): ``` - git clone https://github.com/linkedin/greykite + git clone https://github.com/wwrechard/pydlm ``` -- [PyPi](https://pypi.org/project/greykite) (πŸ“₯ 11K / month Β· ⏱️ 12.01.2024): +- [PyPi](https://pypi.org/project/pydlm) (πŸ“₯ 23K / month Β· πŸ“¦ 2 Β· ⏱️ 13.08.2024): ``` - pip install greykite + pip install pydlm ```
-
Auto TS (πŸ₯‰20 Β· ⭐ 690) - Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost.. Apache-2 +
tsflex (πŸ₯‰21 Β· ⭐ 400) - Flexible time series feature extraction & processing. MIT -- [GitHub](https://github.com/AutoViML/Auto_TS) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 110 Β· πŸ“‹ 88 - 1% open Β· ⏱️ 05.05.2024): +- [GitHub](https://github.com/predict-idlab/tsflex) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 25 Β· πŸ“¦ 15 Β· πŸ“‹ 52 - 57% open Β· ⏱️ 24.08.2024): ``` - git clone https://github.com/AutoViML/Auto_TS + git clone https://github.com/predict-idlab/tsflex ``` -- [PyPi](https://pypi.org/project/auto-ts) (πŸ“₯ 12K / month Β· ⏱️ 05.05.2024): +- [PyPi](https://pypi.org/project/tsflex) (πŸ“₯ 840 / month Β· πŸ“¦ 1 Β· ⏱️ 04.04.2024): ``` - pip install auto-ts + pip install tsflex + ``` +- [Conda](https://anaconda.org/conda-forge/tsflex) (πŸ“₯ 25K Β· ⏱️ 08.04.2024): + ``` + conda install -c conda-forge tsflex ```
-
tsflex (πŸ₯‰20 Β· ⭐ 380) - Flexible time series feature extraction & processing. MIT +
greykite (πŸ₯‰20 Β· ⭐ 1.8K Β· πŸ’€) - A flexible, intuitive and fast forecasting library. BSD-2 -- [GitHub](https://github.com/predict-idlab/tsflex) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 25 Β· πŸ“¦ 13 Β· πŸ“‹ 52 - 57% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/linkedin/greykite) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 100 Β· πŸ“₯ 32 Β· πŸ“¦ 33 Β· πŸ“‹ 110 - 27% open Β· ⏱️ 16.01.2024): ``` - git clone https://github.com/predict-idlab/tsflex - ``` -- [PyPi](https://pypi.org/project/tsflex) (πŸ“₯ 320 / month Β· πŸ“¦ 1 Β· ⏱️ 04.04.2024): - ``` - pip install tsflex + git clone https://github.com/linkedin/greykite ``` -- [Conda](https://anaconda.org/conda-forge/tsflex) (πŸ“₯ 22K Β· ⏱️ 08.04.2024): +- [PyPi](https://pypi.org/project/greykite) (πŸ“₯ 6.6K / month Β· ⏱️ 12.01.2024): ``` - conda install -c conda-forge tsflex + pip install greykite ```
-
pydlm (πŸ₯‰19 Β· ⭐ 470 Β· πŸ’€) - A python library for Bayesian time series modeling. BSD-3 +
Auto TS (πŸ₯‰20 Β· ⭐ 720) - Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost.. Apache-2 -- [GitHub](https://github.com/wwrechard/pydlm) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 97 Β· πŸ“¦ 33 Β· πŸ“‹ 49 - 75% open Β· ⏱️ 04.09.2023): +- [GitHub](https://github.com/AutoViML/Auto_TS) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 110 Β· πŸ“‹ 88 - 1% open Β· ⏱️ 05.05.2024): ``` - git clone https://github.com/wwrechard/pydlm + git clone https://github.com/AutoViML/Auto_TS ``` -- [PyPi](https://pypi.org/project/pydlm) (πŸ“₯ 22K / month Β· πŸ“¦ 2 Β· ⏱️ 19.12.2018): +- [PyPi](https://pypi.org/project/auto-ts) (πŸ“₯ 8.7K / month Β· ⏱️ 05.05.2024): ``` - pip install pydlm + pip install auto-ts ```
-
Show 10 hidden projects... +
Show 11 hidden projects... +- pyts (πŸ₯‰26 Β· ⭐ 1.8K Β· πŸ’€) - A Python package for time series classification. BSD-3 - Streamz (πŸ₯‰26 Β· ⭐ 1.2K Β· πŸ’€) - Real-time stream processing for python. BSD-3 - PyFlux (πŸ₯‰25 Β· ⭐ 2.1K Β· πŸ’€) - Open source time series library for Python. BSD-3 - luminol (πŸ₯‰22 Β· ⭐ 1.2K Β· πŸ’€) - Anomaly Detection and Correlation library. Apache-2 -- tick (πŸ₯‰22 Β· ⭐ 470 Β· πŸ’€) - Module for statistical learning, with a particular emphasis on time-.. BSD-3 -- seglearn (πŸ₯‰21 Β· ⭐ 570 Β· πŸ’€) - Python module for machine learning time series:. BSD-3 -- ADTK (πŸ₯‰20 Β· ⭐ 1K Β· πŸ’€) - A Python toolkit for rule-based/unsupervised anomaly detection in time.. MPL-2.0 -- matrixprofile-ts (πŸ₯‰19 Β· ⭐ 730 Β· πŸ’€) - A Python library for detecting patterns and anomalies.. Apache-2 -- atspy (πŸ₯‰14 Β· ⭐ 510 Β· πŸ’€) - AtsPy: Automated Time Series Models in Python (by @firmai). MIT -- tsaug (πŸ₯‰14 Β· ⭐ 340 Β· πŸ’€) - A Python package for time series augmentation. Apache-2 +- tick (πŸ₯‰22 Β· ⭐ 480 Β· πŸ’€) - Module for statistical learning, with a particular emphasis on time-.. BSD-3 +- ADTK (πŸ₯‰21 Β· ⭐ 1.1K Β· πŸ’€) - A Python toolkit for rule-based/unsupervised anomaly detection in.. MPL-2.0 +- matrixprofile-ts (πŸ₯‰20 Β· ⭐ 730 Β· πŸ’€) - A Python library for detecting patterns and anomalies.. Apache-2 +- seglearn (πŸ₯‰20 Β· ⭐ 570 Β· πŸ’€) - Python module for machine learning time series:. BSD-3 +- atspy (πŸ₯‰15 Β· ⭐ 510 Β· πŸ’€) - AtsPy: Automated Time Series Models in Python (by @firmai). MIT +- tsaug (πŸ₯‰14 Β· ⭐ 350 Β· πŸ’€) - A Python package for time series augmentation. Apache-2 - tslumen (πŸ₯‰8 Β· ⭐ 67 Β· πŸ’€) - A library for Time Series EDA (exploratory data analysis). Apache-2

@@ -4048,134 +3979,134 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic data, and other medical imaging formats._ -
MNE (πŸ₯‡39 Β· ⭐ 2.6K) - MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python. BSD-3 +
MNE (πŸ₯‡39 Β· ⭐ 2.7K) - MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python. BSD-3 -- [GitHub](https://github.com/mne-tools/mne-python) (πŸ‘¨β€πŸ’» 370 Β· πŸ”€ 1.3K Β· πŸ“¦ 3.9K Β· πŸ“‹ 4.8K - 10% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/mne-tools/mne-python) (πŸ‘¨β€πŸ’» 380 Β· πŸ”€ 1.3K Β· πŸ“¦ 4.3K Β· πŸ“‹ 4.9K - 10% open Β· ⏱️ 04.09.2024): ``` git clone https://github.com/mne-tools/mne-python ``` -- [PyPi](https://pypi.org/project/mne) (πŸ“₯ 120K / month Β· πŸ“¦ 350 Β· ⏱️ 19.04.2024): +- [PyPi](https://pypi.org/project/mne) (πŸ“₯ 150K / month Β· πŸ“¦ 380 Β· ⏱️ 19.08.2024): ``` pip install mne ``` -- [Conda](https://anaconda.org/conda-forge/mne) (πŸ“₯ 370K Β· ⏱️ 26.05.2024): +- [Conda](https://anaconda.org/conda-forge/mne) (πŸ“₯ 420K Β· ⏱️ 19.08.2024): ``` conda install -c conda-forge mne ```
-
Nilearn (πŸ₯‡37 Β· ⭐ 1.1K) - Machine learning for NeuroImaging in Python. BSD-3 +
MONAI (πŸ₯‡36 Β· ⭐ 5.7K) - AI Toolkit for Healthcare Imaging. Apache-2 -- [GitHub](https://github.com/nilearn/nilearn) (πŸ‘¨β€πŸ’» 240 Β· πŸ”€ 550 Β· πŸ“₯ 170 Β· πŸ“¦ 3.2K Β· πŸ“‹ 2.1K - 14% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/Project-MONAI/MONAI) (πŸ‘¨β€πŸ’» 200 Β· πŸ”€ 1K Β· πŸ“¦ 2.7K Β· πŸ“‹ 3.1K - 11% open Β· ⏱️ 04.09.2024): ``` - git clone https://github.com/nilearn/nilearn + git clone https://github.com/Project-MONAI/MONAI ``` -- [PyPi](https://pypi.org/project/nilearn) (πŸ“₯ 60K / month Β· πŸ“¦ 280 Β· ⏱️ 09.04.2024): +- [PyPi](https://pypi.org/project/monai) (πŸ“₯ 170K / month Β· πŸ“¦ 110 Β· ⏱️ 02.09.2024): ``` - pip install nilearn + pip install monai ``` -- [Conda](https://anaconda.org/conda-forge/nilearn) (πŸ“₯ 270K Β· ⏱️ 09.04.2024): +- [Conda](https://anaconda.org/conda-forge/monai) (πŸ“₯ 29K Β· ⏱️ 26.06.2024): ``` - conda install -c conda-forge nilearn + conda install -c conda-forge monai ```
-
MONAI (πŸ₯ˆ36 Β· ⭐ 5.4K) - AI Toolkit for Healthcare Imaging. Apache-2 +
Nilearn (πŸ₯‡36 Β· ⭐ 1.2K) - Machine learning for NeuroImaging in Python. BSD-3 -- [GitHub](https://github.com/Project-MONAI/MONAI) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 980 Β· πŸ“¦ 2.3K Β· πŸ“‹ 3K - 11% open Β· ⏱️ 31.05.2024): +- [GitHub](https://github.com/nilearn/nilearn) (πŸ‘¨β€πŸ’» 240 Β· πŸ”€ 580 Β· πŸ“₯ 210 Β· πŸ“¦ 3.4K Β· πŸ“‹ 2.1K - 13% open Β· ⏱️ 05.09.2024): ``` - git clone https://github.com/Project-MONAI/MONAI + git clone https://github.com/nilearn/nilearn ``` -- [PyPi](https://pypi.org/project/monai) (πŸ“₯ 150K / month Β· πŸ“¦ 97 Β· ⏱️ 21.05.2024): +- [PyPi](https://pypi.org/project/nilearn) (πŸ“₯ 52K / month Β· πŸ“¦ 290 Β· ⏱️ 09.04.2024): ``` - pip install monai + pip install nilearn ``` -- [Conda](https://anaconda.org/conda-forge/monai) (πŸ“₯ 24K Β· ⏱️ 21.05.2024): +- [Conda](https://anaconda.org/conda-forge/nilearn) (πŸ“₯ 290K Β· ⏱️ 09.04.2024): ``` - conda install -c conda-forge monai + conda install -c conda-forge nilearn ```
-
NiBabel (πŸ₯ˆ36 Β· ⭐ 630) - Python package to access a cacophony of neuro-imaging file formats. MIT +
NiBabel (πŸ₯ˆ34 Β· ⭐ 640) - Python package to access a cacophony of neuro-imaging file formats. MIT -- [GitHub](https://github.com/nipy/nibabel) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 260 Β· πŸ“¦ 19K Β· πŸ“‹ 530 - 24% open Β· ⏱️ 29.05.2024): +- [GitHub](https://github.com/nipy/nibabel) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 260 Β· πŸ“¦ 21K Β· πŸ“‹ 540 - 24% open Β· ⏱️ 26.07.2024): ``` git clone https://github.com/nipy/nibabel ``` -- [PyPi](https://pypi.org/project/nibabel) (πŸ“₯ 500K / month Β· πŸ“¦ 1K Β· ⏱️ 27.02.2024): +- [PyPi](https://pypi.org/project/nibabel) (πŸ“₯ 610K / month Β· πŸ“¦ 1.1K Β· ⏱️ 27.02.2024): ``` pip install nibabel ``` -- [Conda](https://anaconda.org/conda-forge/nibabel) (πŸ“₯ 710K Β· ⏱️ 27.02.2024): +- [Conda](https://anaconda.org/conda-forge/nibabel) (πŸ“₯ 760K Β· ⏱️ 27.02.2024): ``` conda install -c conda-forge nibabel ```
-
NIPYPE (πŸ₯ˆ35 Β· ⭐ 740) - Workflows and interfaces for neuroimaging packages. Apache-2 +
NIPYPE (πŸ₯ˆ33 Β· ⭐ 740) - Workflows and interfaces for neuroimaging packages. Apache-2 -- [GitHub](https://github.com/nipy/nipype) (πŸ‘¨β€πŸ’» 260 Β· πŸ”€ 510 Β· πŸ“¦ 4.4K Β· πŸ“‹ 1.4K - 29% open Β· ⏱️ 30.05.2024): +- [GitHub](https://github.com/nipy/nipype) (πŸ‘¨β€πŸ’» 260 Β· πŸ”€ 510 Β· πŸ“¦ 4.9K Β· πŸ“‹ 1.4K - 29% open Β· ⏱️ 30.05.2024): ``` git clone https://github.com/nipy/nipype ``` -- [PyPi](https://pypi.org/project/nipype) (πŸ“₯ 170K / month Β· πŸ“¦ 140 Β· ⏱️ 06.04.2023): +- [PyPi](https://pypi.org/project/nipype) (πŸ“₯ 170K / month Β· πŸ“¦ 150 Β· ⏱️ 06.04.2023): ``` pip install nipype ``` -- [Conda](https://anaconda.org/conda-forge/nipype) (πŸ“₯ 620K Β· ⏱️ 22.09.2023): +- [Conda](https://anaconda.org/conda-forge/nipype) (πŸ“₯ 670K Β· ⏱️ 22.09.2023): ``` conda install -c conda-forge nipype ```
Lifelines (πŸ₯ˆ32 Β· ⭐ 2.3K) - Survival analysis in Python. MIT -- [GitHub](https://github.com/CamDavidsonPilon/lifelines) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 580 Β· πŸ“¦ 2.5K Β· πŸ“‹ 950 - 26% open Β· ⏱️ 07.03.2024): +- [GitHub](https://github.com/CamDavidsonPilon/lifelines) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 550 Β· πŸ“¦ 2.9K Β· πŸ“‹ 970 - 26% open Β· ⏱️ 26.06.2024): ``` git clone https://github.com/CamDavidsonPilon/lifelines ``` -- [PyPi](https://pypi.org/project/lifelines) (πŸ“₯ 550K / month Β· πŸ“¦ 130 Β· ⏱️ 03.01.2024): +- [PyPi](https://pypi.org/project/lifelines) (πŸ“₯ 740K / month Β· πŸ“¦ 140 Β· ⏱️ 26.06.2024): ``` pip install lifelines ``` -- [Conda](https://anaconda.org/conda-forge/lifelines) (πŸ“₯ 340K Β· ⏱️ 13.09.2023): +- [Conda](https://anaconda.org/conda-forge/lifelines) (πŸ“₯ 360K Β· ⏱️ 27.06.2024): ``` conda install -c conda-forge lifelines ```
-
Hail (πŸ₯ˆ32 Β· ⭐ 950) - Cloud-native genomic dataframes and batch computing. MIT +
Hail (πŸ₯ˆ32 Β· ⭐ 960) - Cloud-native genomic dataframes and batch computing. MIT -- [GitHub](https://github.com/hail-is/hail) (πŸ‘¨β€πŸ’» 92 Β· πŸ”€ 240 Β· πŸ“¦ 130 Β· πŸ“‹ 2.4K - 9% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/hail-is/hail) (πŸ‘¨β€πŸ’» 95 Β· πŸ”€ 240 Β· πŸ“¦ 140 Β· πŸ“‹ 2.4K - 9% open Β· ⏱️ 29.08.2024): ``` git clone https://github.com/hail-is/hail ``` -- [PyPi](https://pypi.org/project/hail) (πŸ“₯ 19K / month Β· πŸ“¦ 30 Β· ⏱️ 05.06.2024): +- [PyPi](https://pypi.org/project/hail) (πŸ“₯ 200K / month Β· πŸ“¦ 34 Β· ⏱️ 08.08.2024): ``` pip install hail ```
-
DeepVariant (πŸ₯‰25 Β· ⭐ 3.1K) - DeepVariant is an analysis pipeline that uses a deep neural.. BSD-3 +
DeepVariant (πŸ₯‰24 Β· ⭐ 3.2K) - DeepVariant is an analysis pipeline that uses a deep neural.. BSD-3 -- [GitHub](https://github.com/google/deepvariant) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 690 Β· πŸ“₯ 4.7K Β· πŸ“‹ 760 - 0% open Β· ⏱️ 18.03.2024): +- [GitHub](https://github.com/google/deepvariant) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 710 Β· πŸ“₯ 4.8K Β· πŸ“‹ 810 - 0% open Β· ⏱️ 18.03.2024): ``` git clone https://github.com/google/deepvariant ``` -- [Conda](https://anaconda.org/bioconda/deepvariant) (πŸ“₯ 65K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/bioconda/deepvariant) (πŸ“₯ 68K Β· ⏱️ 16.06.2023): ``` conda install -c bioconda deepvariant ```
-
Brainiak (πŸ₯‰18 Β· ⭐ 320 Β· πŸ’€) - Brain Imaging Analysis Kit. Apache-2 +
Brainiak (πŸ₯‰18 Β· ⭐ 330) - Brain Imaging Analysis Kit. Apache-2 -- [GitHub](https://github.com/brainiak/brainiak) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 130 Β· πŸ“‹ 210 - 38% open Β· ⏱️ 27.11.2023): +- [GitHub](https://github.com/brainiak/brainiak) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 130 Β· πŸ“‹ 220 - 39% open Β· ⏱️ 08.07.2024): ``` git clone https://github.com/brainiak/brainiak ``` -- [PyPi](https://pypi.org/project/brainiak) (πŸ“₯ 100 / month Β· ⏱️ 15.10.2020): +- [PyPi](https://pypi.org/project/brainiak) (πŸ“₯ 200 / month Β· ⏱️ 15.10.2020): ``` pip install brainiak ``` @@ -4186,14 +4117,14 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic
Show 10 hidden projects... -- DIPY (πŸ₯ˆ33 Β· ⭐ 680) - DIPY is the paragon 3D/4D+ imaging library in Python. Contains.. ❗Unlicensed -- NiftyNet (πŸ₯‰24 Β· ⭐ 1.4K Β· πŸ’€) - [unmaintained] An open-source convolutional neural.. Apache-2 -- MedPy (πŸ₯‰24 Β· ⭐ 560) - Medical image processing in Python. ❗️GPL-3.0 -- NIPY (πŸ₯‰22 Β· ⭐ 370) - Neuroimaging in Python FMRI analysis package. ❗Unlicensed -- Glow (πŸ₯‰22 Β· ⭐ 260) - An open-source toolkit for large-scale genomic analysis. Apache-2 +- DIPY (πŸ₯ˆ32 Β· ⭐ 700) - DIPY is the paragon 3D/4D+ imaging library in Python. Contains.. ❗Unlicensed +- NiftyNet (πŸ₯‰25 Β· ⭐ 1.4K Β· πŸ’€) - [unmaintained] An open-source convolutional neural.. Apache-2 +- MedPy (πŸ₯‰25 Β· ⭐ 570) - Medical image processing in Python. ❗️GPL-3.0 +- NIPY (πŸ₯‰25 Β· ⭐ 380) - Neuroimaging in Python FMRI analysis package. ❗Unlicensed +- Glow (πŸ₯‰21 Β· ⭐ 260) - An open-source toolkit for large-scale genomic analysis. Apache-2 - DLTK (πŸ₯‰20 Β· ⭐ 1.4K Β· πŸ’€) - Deep Learning Toolkit for Medical Image Analysis. Apache-2 -- MedicalTorch (πŸ₯‰16 Β· ⭐ 840 Β· πŸ’€) - A medical imaging framework for Pytorch. Apache-2 -- Medical Detection Toolkit (πŸ₯‰15 Β· ⭐ 1.3K Β· πŸ’€) - The Medical Detection Toolkit contains 2D + 3D.. Apache-2 +- MedicalTorch (πŸ₯‰15 Β· ⭐ 840 Β· πŸ’€) - A medical imaging framework for Pytorch. Apache-2 +- Medical Detection Toolkit (πŸ₯‰14 Β· ⭐ 1.3K Β· πŸ’€) - The Medical Detection Toolkit contains 2D + 3D.. Apache-2 - DeepNeuro (πŸ₯‰13 Β· ⭐ 120 Β· πŸ’€) - A deep learning python package for neuroimaging data. Made by:. MIT - MedicalNet (πŸ₯‰12 Β· ⭐ 1.9K Β· πŸ’€) - Many studies have shown that the performance on deep learning is.. MIT
@@ -4205,49 +4136,60 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic _Libraries for processing tabular and structured data._ -
pytorch_tabular (πŸ₯‡23 Β· ⭐ 1.2K) - A standard framework for modelling Deep Learning Models.. MIT +
miceforest (πŸ₯‡26 Β· ⭐ 330 Β· πŸ“ˆ) - Multiple Imputation with LightGBM in Python. MIT -- [GitHub](https://github.com/manujosephv/pytorch_tabular) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 130 Β· πŸ“₯ 27 Β· πŸ“‹ 140 - 7% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/AnotherSamWilson/miceforest) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 30 Β· πŸ“¦ 150 Β· πŸ“‹ 84 - 8% open Β· ⏱️ 02.08.2024): ``` - git clone https://github.com/manujosephv/pytorch_tabular + git clone https://github.com/AnotherSamWilson/miceforest ``` -- [PyPi](https://pypi.org/project/pytorch_tabular) (πŸ“₯ 5.4K / month Β· πŸ“¦ 2 Β· ⏱️ 15.01.2024): +- [PyPi](https://pypi.org/project/miceforest) (πŸ“₯ 63K / month Β· πŸ“¦ 9 Β· ⏱️ 02.08.2024): ``` - pip install pytorch_tabular + pip install miceforest + ``` +- [Conda](https://anaconda.org/conda-forge/miceforest) (πŸ“₯ 15K Β· ⏱️ 16.06.2023): + ``` + conda install -c conda-forge miceforest ```
-
miceforest (πŸ₯ˆ22 Β· ⭐ 320) - Multiple Imputation with LightGBM in Python. MIT +
pytorch_tabular (πŸ₯ˆ22 Β· ⭐ 1.3K) - A standard framework for modelling Deep Learning Models.. MIT -- [GitHub](https://github.com/AnotherSamWilson/miceforest) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 27 Β· πŸ“¦ 140 Β· πŸ“‹ 82 - 26% open Β· ⏱️ 27.04.2024): +- [GitHub](https://github.com/manujosephv/pytorch_tabular) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 130 Β· πŸ“₯ 35 Β· πŸ“‹ 160 - 13% open Β· ⏱️ 07.06.2024): ``` - git clone https://github.com/AnotherSamWilson/miceforest + git clone https://github.com/manujosephv/pytorch_tabular ``` -- [PyPi](https://pypi.org/project/miceforest) (πŸ“₯ 46K / month Β· πŸ“¦ 5 Β· ⏱️ 16.11.2023): +- [PyPi](https://pypi.org/project/pytorch_tabular) (πŸ“₯ 3K / month Β· πŸ“¦ 3 Β· ⏱️ 15.01.2024): ``` - pip install miceforest + pip install pytorch_tabular ``` -- [Conda](https://anaconda.org/conda-forge/miceforest) (πŸ“₯ 13K Β· ⏱️ 16.06.2023): +
+
upgini (πŸ₯‰21 Β· ⭐ 310) - Data search & enrichment library for Machine Learning Easily find and add.. BSD-3 + +- [GitHub](https://github.com/upgini/upgini) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 25 Β· πŸ“¦ 7 Β· ⏱️ 05.09.2024): + ``` - conda install -c conda-forge miceforest + git clone https://github.com/upgini/upgini + ``` +- [PyPi](https://pypi.org/project/upgini) (πŸ“₯ 9.9K / month Β· ⏱️ 05.09.2024): + ``` + pip install upgini ```
carefree-learn (πŸ₯‰17 Β· ⭐ 400) - Deep Learning PyTorch. MIT -- [GitHub](https://github.com/carefree0910/carefree-learn) (πŸ‘¨β€πŸ’» 1 Β· πŸ”€ 38 Β· πŸ“¦ 5 Β· πŸ“‹ 82 - 2% open Β· ⏱️ 18.03.2024): +- [GitHub](https://github.com/carefree0910/carefree-learn) (πŸ‘¨β€πŸ’» 1 Β· πŸ”€ 38 Β· πŸ“¦ 7 Β· πŸ“‹ 82 - 2% open Β· ⏱️ 18.03.2024): ``` git clone https://github.com/carefree0910/carefree-learn ``` -- [PyPi](https://pypi.org/project/carefree-learn) (πŸ“₯ 400 / month Β· ⏱️ 09.01.2024): +- [PyPi](https://pypi.org/project/carefree-learn) (πŸ“₯ 850 / month Β· ⏱️ 09.01.2024): ``` pip install carefree-learn ```
-
Show 2 hidden projects... +
Show 1 hidden projects... -- upgini (πŸ₯‰21 Β· ⭐ 300) - Data search & enrichment library for Machine Learning Easily find and add.. BSD-3 - deltapy (πŸ₯‰12 Β· ⭐ 530 Β· πŸ’€) - DeltaPy - Tabular Data Augmentation (by @firmai). MIT

@@ -4258,135 +4200,135 @@ _Libraries for processing tabular and structured data._ _Libraries for optical character recognition (OCR) and text extraction from images or videos._ -
PaddleOCR (πŸ₯‡40 Β· ⭐ 39K) - Awesome multilingual OCR toolkits based on PaddlePaddle.. Apache-2 +
PaddleOCR (πŸ₯‡41 Β· ⭐ 42K) - Awesome multilingual OCR toolkits based on PaddlePaddle.. Apache-2 -- [GitHub](https://github.com/PaddlePaddle/PaddleOCR) (πŸ‘¨β€πŸ’» 200 Β· πŸ”€ 7.3K Β· πŸ“¦ 2.7K Β· πŸ“‹ 9.2K - 5% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/PaddlePaddle/PaddleOCR) (πŸ‘¨β€πŸ’» 250 Β· πŸ”€ 7.6K Β· πŸ“₯ 230K Β· πŸ“¦ 3.2K Β· πŸ“‹ 9.3K - 1% open Β· ⏱️ 02.09.2024): ``` git clone https://github.com/PaddlePaddle/PaddleOCR ``` -- [PyPi](https://pypi.org/project/paddleocr) (πŸ“₯ 190K / month Β· πŸ“¦ 65 Β· ⏱️ 29.03.2024): +- [PyPi](https://pypi.org/project/paddleocr) (πŸ“₯ 470K / month Β· πŸ“¦ 92 Β· ⏱️ 17.07.2024): ``` pip install paddleocr ```
-
EasyOCR (πŸ₯‡35 Β· ⭐ 22K Β· πŸ’€) - Ready-to-use OCR with 80+ supported languages and all popular.. Apache-2 +
OCRmyPDF (πŸ₯‡35 Β· ⭐ 14K) - OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them.. MPL-2.0 -- [GitHub](https://github.com/JaidedAI/EasyOCR) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 3K Β· πŸ“₯ 11M Β· πŸ“¦ 6.7K Β· πŸ“‹ 980 - 40% open Β· ⏱️ 04.09.2023): +- [GitHub](https://github.com/ocrmypdf/OCRmyPDF) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 990 Β· πŸ“₯ 4.9K Β· πŸ“¦ 970 Β· πŸ“‹ 1.2K - 9% open Β· ⏱️ 05.09.2024): ``` - git clone https://github.com/JaidedAI/EasyOCR + git clone https://github.com/ocrmypdf/OCRmyPDF ``` -- [PyPi](https://pypi.org/project/easyocr) (πŸ“₯ 270K / month Β· πŸ“¦ 180 Β· ⏱️ 04.09.2023): +- [PyPi](https://pypi.org/project/ocrmypdf) (πŸ“₯ 120K / month Β· πŸ“¦ 32 Β· ⏱️ 31.08.2024): ``` - pip install easyocr + pip install ocrmypdf + ``` +- [Conda](https://anaconda.org/conda-forge/ocrmypdf) (πŸ“₯ 76K Β· ⏱️ 16.06.2023): + ``` + conda install -c conda-forge ocrmypdf ```
-
OCRmyPDF (πŸ₯‡35 Β· ⭐ 12K) - OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them.. MPL-2.0 +
EasyOCR (πŸ₯ˆ34 Β· ⭐ 24K) - Ready-to-use OCR with 80+ supported languages and all popular writing.. Apache-2 -- [GitHub](https://github.com/ocrmypdf/OCRmyPDF) (πŸ‘¨β€πŸ’» 96 Β· πŸ”€ 910 Β· πŸ“₯ 3.6K Β· πŸ“¦ 840 Β· πŸ“‹ 1.1K - 9% open Β· ⏱️ 01.06.2024): +- [GitHub](https://github.com/JaidedAI/EasyOCR) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 3.1K Β· πŸ“₯ 14M Β· πŸ“¦ 8K Β· πŸ“‹ 1K - 41% open Β· ⏱️ 25.07.2024): ``` - git clone https://github.com/ocrmypdf/OCRmyPDF - ``` -- [PyPi](https://pypi.org/project/ocrmypdf) (πŸ“₯ 93K / month Β· πŸ“¦ 25 Β· ⏱️ 21.05.2024): - ``` - pip install ocrmypdf + git clone https://github.com/JaidedAI/EasyOCR ``` -- [Conda](https://anaconda.org/conda-forge/ocrmypdf) (πŸ“₯ 67K Β· ⏱️ 16.06.2023): +- [PyPi](https://pypi.org/project/easyocr) (πŸ“₯ 450K / month Β· πŸ“¦ 200 Β· ⏱️ 04.09.2023): ``` - conda install -c conda-forge ocrmypdf + pip install easyocr ```
-
tesserocr (πŸ₯ˆ32 Β· ⭐ 1.9K) - A Python wrapper for the tesseract-ocr API. MIT +
Tesseract (πŸ₯ˆ32 Β· ⭐ 5.8K) - Python-tesseract is an optical character recognition (OCR) tool.. Apache-2 -- [GitHub](https://github.com/sirfz/tesserocr) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 250 Β· πŸ“₯ 250 Β· πŸ“¦ 990 Β· πŸ“‹ 280 - 18% open Β· ⏱️ 27.04.2024): +- [GitHub](https://github.com/madmaze/pytesseract) (πŸ‘¨β€πŸ’» 49 Β· πŸ”€ 710 Β· πŸ“‹ 370 - 4% open Β· ⏱️ 08.05.2024): ``` - git clone https://github.com/sirfz/tesserocr + git clone https://github.com/madmaze/pytesseract ``` -- [PyPi](https://pypi.org/project/tesserocr) (πŸ“₯ 66K / month Β· πŸ“¦ 34 Β· ⏱️ 27.04.2024): +- [PyPi](https://pypi.org/project/pytesseract) (πŸ“₯ 3.1M / month Β· πŸ“¦ 940 Β· ⏱️ 16.08.2024): ``` - pip install tesserocr + pip install pytesseract ``` -- [Conda](https://anaconda.org/conda-forge/tesserocr) (πŸ“₯ 140K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/pytesseract) (πŸ“₯ 620K Β· ⏱️ 15.10.2023): ``` - conda install -c conda-forge tesserocr + conda install -c conda-forge pytesseract ```
-
Tesseract (πŸ₯ˆ30 Β· ⭐ 5.6K) - Python-tesseract is an optical character recognition (OCR) tool.. Apache-2 +
tesserocr (πŸ₯ˆ30 Β· ⭐ 2K) - A Python wrapper for the tesseract-ocr API. MIT -- [GitHub](https://github.com/madmaze/pytesseract) (πŸ‘¨β€πŸ’» 49 Β· πŸ”€ 700 Β· πŸ“‹ 360 - 3% open Β· ⏱️ 08.05.2024): +- [GitHub](https://github.com/sirfz/tesserocr) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 250 Β· πŸ“₯ 420 Β· πŸ“¦ 1.1K Β· πŸ“‹ 280 - 17% open Β· ⏱️ 26.08.2024): ``` - git clone https://github.com/madmaze/pytesseract + git clone https://github.com/sirfz/tesserocr ``` -- [PyPi](https://pypi.org/project/pytesseract) (πŸ“₯ 2.1M / month Β· πŸ“¦ 850 Β· ⏱️ 16.08.2022): +- [PyPi](https://pypi.org/project/tesserocr) (πŸ“₯ 82K / month Β· πŸ“¦ 36 Β· ⏱️ 26.08.2024): ``` - pip install pytesseract + pip install tesserocr ``` -- [Conda](https://anaconda.org/conda-forge/pytesseract) (πŸ“₯ 610K Β· ⏱️ 15.10.2023): +- [Conda](https://anaconda.org/conda-forge/tesserocr) (πŸ“₯ 170K Β· ⏱️ 30.07.2024): ``` - conda install -c conda-forge pytesseract + conda install -c conda-forge tesserocr ```
-
MMOCR (πŸ₯‰26 Β· ⭐ 4.1K) - OpenMMLab Text Detection, Recognition and Understanding Toolbox. Apache-2 +
MMOCR (πŸ₯‰28 Β· ⭐ 4.3K) - OpenMMLab Text Detection, Recognition and Understanding Toolbox. Apache-2 -- [GitHub](https://github.com/open-mmlab/mmocr) (πŸ‘¨β€πŸ’» 90 Β· πŸ”€ 720 Β· πŸ“¦ 130 Β· πŸ“‹ 910 - 18% open Β· ⏱️ 23.04.2024): +- [GitHub](https://github.com/open-mmlab/mmocr) (πŸ‘¨β€πŸ’» 90 Β· πŸ”€ 740 Β· πŸ“¦ 160 Β· πŸ“‹ 930 - 20% open Β· ⏱️ 23.04.2024): ``` git clone https://github.com/open-mmlab/mmocr ``` -- [PyPi](https://pypi.org/project/mmocr) (πŸ“₯ 6K / month Β· πŸ“¦ 3 Β· ⏱️ 05.05.2022): +- [PyPi](https://pypi.org/project/mmocr) (πŸ“₯ 14K / month Β· πŸ“¦ 4 Β· ⏱️ 05.05.2022): ``` pip install mmocr ```
-
keras-ocr (πŸ₯‰26 Β· ⭐ 1.3K Β· πŸ’€) - A packaged and flexible version of the CRAFT text detector.. MIT +
keras-ocr (πŸ₯‰27 Β· ⭐ 1.4K Β· πŸ’€) - A packaged and flexible version of the CRAFT text detector.. MIT -- [GitHub](https://github.com/faustomorales/keras-ocr) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 330 Β· πŸ“₯ 1.3M Β· πŸ“¦ 480 Β· πŸ“‹ 210 - 46% open Β· ⏱️ 06.11.2023): +- [GitHub](https://github.com/faustomorales/keras-ocr) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 330 Β· πŸ“₯ 1.6M Β· πŸ“¦ 550 Β· πŸ“‹ 210 - 46% open Β· ⏱️ 06.11.2023): ``` git clone https://github.com/faustomorales/keras-ocr ``` -- [PyPi](https://pypi.org/project/keras-ocr) (πŸ“₯ 48K / month Β· πŸ“¦ 8 Β· ⏱️ 06.11.2023): +- [PyPi](https://pypi.org/project/keras-ocr) (πŸ“₯ 35K / month Β· πŸ“¦ 8 Β· ⏱️ 06.11.2023): ``` pip install keras-ocr ``` -- [Conda](https://anaconda.org/anaconda/keras-ocr) (πŸ“₯ 310 Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/anaconda/keras-ocr) (πŸ“₯ 330 Β· ⏱️ 16.06.2023): ``` conda install -c anaconda keras-ocr ```
-
calamari (πŸ₯‰21 Β· ⭐ 1K Β· πŸ’€) - Line based ATR Engine based on OCRopy. Apache-2 +
calamari (πŸ₯‰23 Β· ⭐ 1K) - Line based ATR Engine based on OCRopy. Apache-2 -- [GitHub](https://github.com/Calamari-OCR/calamari) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 210 Β· πŸ“‹ 270 - 23% open Β· ⏱️ 18.08.2023): +- [GitHub](https://github.com/Calamari-OCR/calamari) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 210 Β· πŸ“‹ 280 - 24% open Β· ⏱️ 30.07.2024): ``` git clone https://github.com/Calamari-OCR/calamari ``` -- [PyPi](https://pypi.org/project/calamari_ocr) (πŸ“₯ 2.4K / month Β· πŸ“¦ 5 Β· ⏱️ 18.08.2023): +- [PyPi](https://pypi.org/project/calamari_ocr) (πŸ“₯ 3.8K / month Β· πŸ“¦ 8 Β· ⏱️ 31.07.2024): ``` pip install calamari_ocr ```
-
attention-ocr (πŸ₯‰20 Β· ⭐ 1.1K Β· πŸ’€) - A Tensorflow model for text recognition (CNN + seq2seq.. MIT +
attention-ocr (πŸ₯‰21 Β· ⭐ 1.1K Β· πŸ’€) - A Tensorflow model for text recognition (CNN + seq2seq.. MIT -- [GitHub](https://github.com/emedvedev/attention-ocr) (πŸ‘¨β€πŸ’» 28 Β· πŸ”€ 250 Β· πŸ“¦ 28 Β· πŸ“‹ 150 - 16% open Β· ⏱️ 20.10.2023): +- [GitHub](https://github.com/emedvedev/attention-ocr) (πŸ‘¨β€πŸ’» 28 Β· πŸ”€ 250 Β· πŸ“¦ 29 Β· πŸ“‹ 150 - 16% open Β· ⏱️ 20.10.2023): ``` git clone https://github.com/emedvedev/attention-ocr ``` -- [PyPi](https://pypi.org/project/aocr) (πŸ“₯ 130 / month Β· ⏱️ 19.04.2019): +- [PyPi](https://pypi.org/project/aocr) (πŸ“₯ 190 / month Β· ⏱️ 19.04.2019): ``` pip install aocr ```
Show 3 hidden projects... -- pdftabextract (πŸ₯‰22 Β· ⭐ 2.2K Β· πŸ’€) - A set of tools for extracting tables from PDF files.. Apache-2 +- pdftabextract (πŸ₯‰21 Β· ⭐ 2.2K Β· πŸ’€) - A set of tools for extracting tables from PDF files.. Apache-2 - doc2text (πŸ₯‰20 Β· ⭐ 1.3K Β· πŸ’€) - Detect text blocks and OCR poorly scanned PDFs in bulk. Python.. MIT -- Mozart (πŸ₯‰10 Β· ⭐ 580 Β· πŸ’€) - An optical music recognition (OMR) system. Converts sheet.. Apache-2 +- Mozart (πŸ₯‰10 Β· ⭐ 590 Β· πŸ’€) - An optical music recognition (OMR) system. Converts sheet.. Apache-2

@@ -4396,7 +4338,7 @@ _Libraries for optical character recognition (OCR) and text extraction from imag _General-purpose data containers & structures as well as utilities & extensions for pandas._ -πŸ”— best-of-python - Data Containers ( ⭐ 3.5K) - Collection of data-container, dataframe, and pandas-.. +πŸ”— best-of-python - Data Containers ( ⭐ 3.6K) - Collection of data-container, dataframe, and pandas-..
@@ -4406,7 +4348,7 @@ _General-purpose data containers & structures as well as utilities & extensions _Libraries for loading, collecting, and extracting data from a variety of data sources and formats._ -πŸ”— best-of-python - Data Extraction ( ⭐ 3.5K) - Collection of data-loading and -extraction libraries. +πŸ”— best-of-python - Data Extraction ( ⭐ 3.6K) - Collection of data-loading and -extraction libraries.
@@ -4416,7 +4358,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s _Libraries for web scraping, crawling, downloading, and mining as well as libraries._ -πŸ”— best-of-web-python - Web Scraping ( ⭐ 2.2K) - Collection of web-scraping and crawling libraries. +πŸ”— best-of-web-python - Web Scraping ( ⭐ 2.3K) - Collection of web-scraping and crawling libraries.
@@ -4426,7 +4368,7 @@ _Libraries for web scraping, crawling, downloading, and mining as well as librar _Libraries for data batch- and stream-processing, workflow automation, job scheduling, and other data pipeline tasks._ -πŸ”— best-of-python - Data Pipelines ( ⭐ 3.5K) - Libraries for data batch- and stream-processing,.. +πŸ”— best-of-python - Data Pipelines ( ⭐ 3.6K) - Libraries for data batch- and stream-processing,..
@@ -4436,46 +4378,46 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched _Libraries that provide capabilities to distribute and parallelize machine learning tasks across large-scale compute infrastructure._ -
Ray (πŸ₯‡44 Β· ⭐ 32K) - Ray is a unified framework for scaling AI and Python applications. Ray.. Apache-2 +
Ray (πŸ₯‡45 Β· ⭐ 33K) - Ray is a unified framework for scaling AI and Python applications. Ray.. Apache-2 -- [GitHub](https://github.com/ray-project/ray) (πŸ‘¨β€πŸ’» 1K Β· πŸ”€ 5.3K Β· πŸ“₯ 210 Β· πŸ“¦ 16K Β· πŸ“‹ 18K - 20% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/ray-project/ray) (πŸ‘¨β€πŸ’» 1.1K Β· πŸ”€ 5.6K Β· πŸ“₯ 240 Β· πŸ“¦ 18K Β· πŸ“‹ 19K - 21% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/ray-project/ray ``` -- [PyPi](https://pypi.org/project/ray) (πŸ“₯ 4M / month Β· πŸ“¦ 700 Β· ⏱️ 22.05.2024): +- [PyPi](https://pypi.org/project/ray) (πŸ“₯ 4.2M / month Β· πŸ“¦ 760 Β· ⏱️ 27.08.2024): ``` pip install ray ``` -- [Conda](https://anaconda.org/conda-forge/ray-tune) (πŸ“₯ 230K Β· ⏱️ 29.05.2024): +- [Conda](https://anaconda.org/conda-forge/ray-tune) (πŸ“₯ 380K Β· ⏱️ 29.08.2024): ``` conda install -c conda-forge ray-tune ```
dask (πŸ₯‡44 Β· ⭐ 12K) - Parallel computing with task scheduling. BSD-3 -- [GitHub](https://github.com/dask/dask) (πŸ‘¨β€πŸ’» 600 Β· πŸ”€ 1.7K Β· πŸ“¦ 61K Β· πŸ“‹ 5.2K - 20% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/dask/dask) (πŸ‘¨β€πŸ’» 610 Β· πŸ”€ 1.7K Β· πŸ“¦ 64K Β· πŸ“‹ 5.3K - 20% open Β· ⏱️ 04.09.2024): ``` git clone https://github.com/dask/dask ``` -- [PyPi](https://pypi.org/project/dask) (πŸ“₯ 8.9M / month Β· πŸ“¦ 2.1K Β· ⏱️ 31.05.2024): +- [PyPi](https://pypi.org/project/dask) (πŸ“₯ 11M / month Β· πŸ“¦ 2.3K Β· ⏱️ 30.08.2024): ``` pip install dask ``` -- [Conda](https://anaconda.org/conda-forge/dask) (πŸ“₯ 11M Β· ⏱️ 31.05.2024): +- [Conda](https://anaconda.org/conda-forge/dask) (πŸ“₯ 12M Β· ⏱️ 31.08.2024): ``` conda install -c conda-forge dask ```
-
DeepSpeed (πŸ₯‡41 Β· ⭐ 33K) - DeepSpeed is a deep learning optimization library that makes.. Apache-2 +
DeepSpeed (πŸ₯‡41 Β· ⭐ 35K) - DeepSpeed is a deep learning optimization library that makes.. Apache-2 -- [GitHub](https://github.com/microsoft/DeepSpeed) (πŸ‘¨β€πŸ’» 320 Β· πŸ”€ 3.9K Β· πŸ“¦ 7.3K Β· πŸ“‹ 2.7K - 39% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/microsoft/DeepSpeed) (πŸ‘¨β€πŸ’» 340 Β· πŸ”€ 4K Β· πŸ“¦ 8.6K Β· πŸ“‹ 2.8K - 39% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/microsoft/DeepSpeed ``` -- [PyPi](https://pypi.org/project/deepspeed) (πŸ“₯ 530K / month Β· πŸ“¦ 170 Β· ⏱️ 23.04.2024): +- [PyPi](https://pypi.org/project/deepspeed) (πŸ“₯ 460K / month Β· πŸ“¦ 200 Β· ⏱️ 05.09.2024): ``` pip install deepspeed ``` @@ -4484,78 +4426,78 @@ _Libraries that provide capabilities to distribute and parallelize machine learn docker pull deepspeed/deepspeed ```
-
dask.distributed (πŸ₯‡40 Β· ⭐ 1.5K) - A distributed task scheduler for Dask. BSD-3 +
dask.distributed (πŸ₯‡40 Β· ⭐ 1.6K) - A distributed task scheduler for Dask. BSD-3 -- [GitHub](https://github.com/dask/distributed) (πŸ‘¨β€πŸ’» 320 Β· πŸ”€ 710 Β· πŸ“¦ 35K Β· πŸ“‹ 3.9K - 39% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/dask/distributed) (πŸ‘¨β€πŸ’» 330 Β· πŸ”€ 720 Β· πŸ“¦ 36K Β· πŸ“‹ 3.9K - 39% open Β· ⏱️ 04.09.2024): ``` git clone https://github.com/dask/distributed ``` -- [PyPi](https://pypi.org/project/distributed) (πŸ“₯ 4.2M / month Β· πŸ“¦ 750 Β· ⏱️ 31.05.2024): +- [PyPi](https://pypi.org/project/distributed) (πŸ“₯ 5.8M / month Β· πŸ“¦ 810 Β· ⏱️ 30.08.2024): ``` pip install distributed ``` -- [Conda](https://anaconda.org/conda-forge/distributed) (πŸ“₯ 14M Β· ⏱️ 31.05.2024): +- [Conda](https://anaconda.org/conda-forge/distributed) (πŸ“₯ 15M Β· ⏱️ 30.08.2024): ``` conda install -c conda-forge distributed ```
-
horovod (πŸ₯ˆ35 Β· ⭐ 14K) - Distributed training framework for TensorFlow, Keras, PyTorch, and.. Apache-2 +
horovod (πŸ₯ˆ36 Β· ⭐ 14K) - Distributed training framework for TensorFlow, Keras, PyTorch, and.. Apache-2 -- [GitHub](https://github.com/horovod/horovod) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 2.2K Β· πŸ“¦ 1.2K Β· πŸ“‹ 2.2K - 17% open Β· ⏱️ 25.03.2024): +- [GitHub](https://github.com/horovod/horovod) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 2.2K Β· πŸ“¦ 1.2K Β· πŸ“‹ 2.3K - 17% open Β· ⏱️ 31.08.2024): ``` git clone https://github.com/horovod/horovod ``` -- [PyPi](https://pypi.org/project/horovod) (πŸ“₯ 95K / month Β· πŸ“¦ 29 Β· ⏱️ 12.06.2023): +- [PyPi](https://pypi.org/project/horovod) (πŸ“₯ 150K / month Β· πŸ“¦ 33 Β· ⏱️ 12.06.2023): ``` pip install horovod ```
-
H2O-3 (πŸ₯ˆ35 Β· ⭐ 6.8K) - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning.. Apache-2 +
metrics (πŸ₯ˆ36 Β· ⭐ 2.1K) - Torchmetrics - Machine learning metrics for distributed,.. Apache-2 -- [GitHub](https://github.com/h2oai/h2o-3) (πŸ‘¨β€πŸ’» 260 Β· πŸ”€ 2K Β· πŸ“¦ 21 Β· πŸ“‹ 9.4K - 29% open Β· ⏱️ 04.06.2024): +- [GitHub](https://github.com/Lightning-AI/torchmetrics) (πŸ‘¨β€πŸ’» 250 Β· πŸ”€ 390 Β· πŸ“₯ 5.5K Β· πŸ“¦ 29K Β· πŸ“‹ 860 - 9% open Β· ⏱️ 04.09.2024): ``` - git clone https://github.com/h2oai/h2o-3 + git clone https://github.com/Lightning-AI/metrics ``` -- [PyPi](https://pypi.org/project/h2o) (πŸ“₯ 290K / month Β· πŸ“¦ 46 Β· ⏱️ 13.05.2024): +- [PyPi](https://pypi.org/project/metrics) (πŸ“₯ 4.2K / month Β· πŸ“¦ 2 Β· ⏱️ 28.04.2018): ``` - pip install h2o + pip install metrics + ``` +- [Conda](https://anaconda.org/conda-forge/torchmetrics) (πŸ“₯ 1.5M Β· ⏱️ 16.05.2024): + ``` + conda install -c conda-forge torchmetrics ```
-
metrics (πŸ₯ˆ35 Β· ⭐ 2K) - Torchmetrics - Machine learning metrics for distributed, scalable.. Apache-2 +
H2O-3 (πŸ₯ˆ35 Β· ⭐ 6.9K) - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning.. Apache-2 -- [GitHub](https://github.com/Lightning-AI/torchmetrics) (πŸ‘¨β€πŸ’» 240 Β· πŸ”€ 380 Β· πŸ“₯ 5.2K Β· πŸ“¦ 26K Β· πŸ“‹ 830 - 8% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/h2oai/h2o-3) (πŸ‘¨β€πŸ’» 270 Β· πŸ”€ 2K Β· πŸ“¦ 21 Β· πŸ“‹ 9.5K - 29% open Β· ⏱️ 29.08.2024): ``` - git clone https://github.com/Lightning-AI/metrics - ``` -- [PyPi](https://pypi.org/project/metrics) (πŸ“₯ 4.3K / month Β· πŸ“¦ 2 Β· ⏱️ 28.04.2018): - ``` - pip install metrics + git clone https://github.com/h2oai/h2o-3 ``` -- [Conda](https://anaconda.org/conda-forge/torchmetrics) (πŸ“₯ 1.4M Β· ⏱️ 16.05.2024): +- [PyPi](https://pypi.org/project/h2o) (πŸ“₯ 310K / month Β· πŸ“¦ 46 Β· ⏱️ 29.08.2024): ``` - conda install -c conda-forge torchmetrics + pip install h2o ```
-
ColossalAI (πŸ₯ˆ34 Β· ⭐ 38K) - Making large AI models cheaper, faster and more accessible. Apache-2 +
ColossalAI (πŸ₯ˆ34 Β· ⭐ 39K) - Making large AI models cheaper, faster and more accessible. Apache-2 -- [GitHub](https://github.com/hpcaitech/ColossalAI) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 4.2K Β· πŸ“¦ 380 Β· πŸ“‹ 1.6K - 25% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/hpcaitech/ColossalAI) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 4.3K Β· πŸ“¦ 410 Β· πŸ“‹ 1.7K - 24% open Β· ⏱️ 03.09.2024): ``` git clone https://github.com/hpcaitech/colossalai ```
-
BigDL (πŸ₯ˆ33 Β· ⭐ 6.1K) - Accelerate local LLM inference and finetuning (LLaMA, Mistral,.. Apache-2 +
BigDL (πŸ₯ˆ32 Β· ⭐ 6.4K) - Accelerate local LLM inference and finetuning (LLaMA, Mistral,.. Apache-2 -- [GitHub](https://github.com/intel-analytics/ipex-llm) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 1.2K Β· πŸ“₯ 500 Β· πŸ“¦ 51 Β· πŸ“‹ 2.3K - 35% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/intel-analytics/ipex-llm) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 1.2K Β· πŸ“₯ 630 Β· πŸ“‹ 2.5K - 37% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/intel-analytics/BigDL ``` -- [PyPi](https://pypi.org/project/bigdl) (πŸ“₯ 3.3K / month Β· πŸ“¦ 2 Β· ⏱️ 24.03.2024): +- [PyPi](https://pypi.org/project/bigdl) (πŸ“₯ 4.2K / month Β· πŸ“¦ 2 Β· ⏱️ 24.03.2024): ``` pip install bigdl ``` @@ -4568,187 +4510,176 @@ _Libraries that provide capabilities to distribute and parallelize machine learn ```
-
FairScale (πŸ₯ˆ32 Β· ⭐ 3K) - PyTorch extensions for high performance and large scale training. BSD-3 +
FairScale (πŸ₯ˆ32 Β· ⭐ 3.1K) - PyTorch extensions for high performance and large scale training. BSD-3 -- [GitHub](https://github.com/facebookresearch/fairscale) (πŸ‘¨β€πŸ’» 75 Β· πŸ”€ 260 Β· πŸ“¦ 5.3K Β· πŸ“‹ 380 - 25% open Β· ⏱️ 03.05.2024): +- [GitHub](https://github.com/facebookresearch/fairscale) (πŸ‘¨β€πŸ’» 75 Β· πŸ”€ 270 Β· πŸ“¦ 6.1K Β· πŸ“‹ 390 - 26% open Β· ⏱️ 03.05.2024): ``` git clone https://github.com/facebookresearch/fairscale ``` -- [PyPi](https://pypi.org/project/fairscale) (πŸ“₯ 510K / month Β· πŸ“¦ 66 Β· ⏱️ 11.12.2022): - ``` - pip install fairscale - ``` -- [Conda](https://anaconda.org/conda-forge/fairscale) (πŸ“₯ 210K Β· ⏱️ 28.11.2023): - ``` - conda install -c conda-forge fairscale - ``` -
-
dask-ml (πŸ₯ˆ30 Β· ⭐ 880) - Scalable Machine Learning with Dask. BSD-3 - -- [GitHub](https://github.com/dask/dask-ml) (πŸ‘¨β€πŸ’» 78 Β· πŸ”€ 250 Β· πŸ“¦ 1K Β· πŸ“‹ 530 - 51% open Β· ⏱️ 02.04.2024): - - ``` - git clone https://github.com/dask/dask-ml - ``` -- [PyPi](https://pypi.org/project/dask-ml) (πŸ“₯ 250K / month Β· πŸ“¦ 89 Β· ⏱️ 02.04.2024): +- [PyPi](https://pypi.org/project/fairscale) (πŸ“₯ 500K / month Β· πŸ“¦ 150 Β· ⏱️ 11.12.2022): ``` - pip install dask-ml + pip install fairscale ``` -- [Conda](https://anaconda.org/conda-forge/dask-ml) (πŸ“₯ 830K Β· ⏱️ 21.03.2024): +- [Conda](https://anaconda.org/conda-forge/fairscale) (πŸ“₯ 280K Β· ⏱️ 28.11.2023): ``` - conda install -c conda-forge dask-ml + conda install -c conda-forge fairscale ```
-
mpi4py (πŸ₯ˆ30 Β· ⭐ 760) - Python bindings for MPI. BSD-2 +
mpi4py (πŸ₯ˆ31 Β· ⭐ 780) - Python bindings for MPI. BSD-3 -- [GitHub](https://github.com/mpi4py/mpi4py) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 110 Β· πŸ“₯ 24K Β· πŸ“‹ 160 - 4% open Β· ⏱️ 03.06.2024): +- [GitHub](https://github.com/mpi4py/mpi4py) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 120 Β· πŸ“₯ 26K Β· πŸ“‹ 170 - 3% open Β· ⏱️ 31.08.2024): ``` git clone https://github.com/mpi4py/mpi4py ``` -- [PyPi](https://pypi.org/project/mpi4py) (πŸ“₯ 300K / month Β· πŸ“¦ 680 Β· ⏱️ 14.04.2024): +- [PyPi](https://pypi.org/project/mpi4py) (πŸ“₯ 890K / month Β· πŸ“¦ 730 Β· ⏱️ 28.07.2024): ``` pip install mpi4py ``` -- [Conda](https://anaconda.org/conda-forge/mpi4py) (πŸ“₯ 2.5M Β· ⏱️ 25.05.2024): +- [Conda](https://anaconda.org/conda-forge/mpi4py) (πŸ“₯ 2.9M Β· ⏱️ 04.09.2024): ``` conda install -c conda-forge mpi4py ```
SynapseML (πŸ₯ˆ29 Β· ⭐ 5K) - Simple and Distributed Machine Learning. MIT -- [GitHub](https://github.com/microsoft/SynapseML) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 820 Β· πŸ“‹ 750 - 46% open Β· ⏱️ 21.05.2024): +- [GitHub](https://github.com/microsoft/SynapseML) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 830 Β· πŸ“‹ 770 - 47% open Β· ⏱️ 30.08.2024): ``` git clone https://github.com/microsoft/SynapseML ``` -- [PyPi](https://pypi.org/project/synapseml) (πŸ“₯ 220K / month Β· πŸ“¦ 5 Β· ⏱️ 11.04.2024): +- [PyPi](https://pypi.org/project/synapseml) (πŸ“₯ 240K / month Β· πŸ“¦ 5 Β· ⏱️ 30.08.2024): ``` pip install synapseml ```
-
petastorm (πŸ₯‰27 Β· ⭐ 1.8K) - Petastorm library enables single machine or distributed training.. Apache-2 +
dask-ml (πŸ₯ˆ29 Β· ⭐ 890) - Scalable Machine Learning with Dask. BSD-3 -- [GitHub](https://github.com/uber/petastorm) (πŸ‘¨β€πŸ’» 50 Β· πŸ”€ 280 Β· πŸ“₯ 460 Β· πŸ“¦ 170 Β· πŸ“‹ 320 - 53% open Β· ⏱️ 02.12.2023): +- [GitHub](https://github.com/dask/dask-ml) (πŸ‘¨β€πŸ’» 80 Β· πŸ”€ 260 Β· πŸ“¦ 1.1K Β· πŸ“‹ 540 - 51% open Β· ⏱️ 20.07.2024): ``` - git clone https://github.com/uber/petastorm + git clone https://github.com/dask/dask-ml ``` -- [PyPi](https://pypi.org/project/petastorm) (πŸ“₯ 75K / month Β· πŸ“¦ 8 Β· ⏱️ 03.02.2023): +- [PyPi](https://pypi.org/project/dask-ml) (πŸ“₯ 230K / month Β· πŸ“¦ 93 Β· ⏱️ 02.04.2024): ``` - pip install petastorm + pip install dask-ml + ``` +- [Conda](https://anaconda.org/conda-forge/dask-ml) (πŸ“₯ 880K Β· ⏱️ 17.06.2024): + ``` + conda install -c conda-forge dask-ml ```
-
Submit it (πŸ₯‰26 Β· ⭐ 1.1K Β· πŸ’€) - Python 3.8+ toolbox for submitting jobs to Slurm. MIT +
Submit it (πŸ₯‰28 Β· ⭐ 1.3K) - Python 3.8+ toolbox for submitting jobs to Slurm. MIT -- [GitHub](https://github.com/facebookincubator/submitit) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 110 Β· πŸ“¦ 2.7K Β· πŸ“‹ 120 - 36% open Β· ⏱️ 09.11.2023): +- [GitHub](https://github.com/facebookincubator/submitit) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 120 Β· πŸ“¦ 3.1K Β· πŸ“‹ 120 - 36% open Β· ⏱️ 29.07.2024): ``` git clone https://github.com/facebookincubator/submitit ``` -- [PyPi](https://pypi.org/project/submitit) (πŸ“₯ 300K / month Β· πŸ“¦ 39 Β· ⏱️ 09.11.2023): +- [PyPi](https://pypi.org/project/submitit) (πŸ“₯ 460K / month Β· πŸ“¦ 45 Β· ⏱️ 09.11.2023): ``` pip install submitit ``` -- [Conda](https://anaconda.org/conda-forge/submitit) (πŸ“₯ 37K Β· ⏱️ 24.11.2023): +- [Conda](https://anaconda.org/conda-forge/submitit) (πŸ“₯ 40K Β· ⏱️ 24.11.2023): ``` conda install -c conda-forge submitit ```
+
petastorm (πŸ₯‰27 Β· ⭐ 1.8K Β· πŸ’€) - Petastorm library enables single machine or distributed.. Apache-2 + +- [GitHub](https://github.com/uber/petastorm) (πŸ‘¨β€πŸ’» 50 Β· πŸ”€ 280 Β· πŸ“₯ 480 Β· πŸ“¦ 180 Β· πŸ“‹ 320 - 53% open Β· ⏱️ 02.12.2023): + + ``` + git clone https://github.com/uber/petastorm + ``` +- [PyPi](https://pypi.org/project/petastorm) (πŸ“₯ 150K / month Β· πŸ“¦ 8 Β· ⏱️ 03.02.2023): + ``` + pip install petastorm + ``` +
Apache Singa (πŸ₯‰25 Β· ⭐ 3.3K) - a distributed deep learning platform. Apache-2 -- [GitHub](https://github.com/apache/singa) (πŸ‘¨β€πŸ’» 90 Β· πŸ”€ 1.2K Β· πŸ“¦ 3 Β· πŸ“‹ 130 - 40% open Β· ⏱️ 23.05.2024): +- [GitHub](https://github.com/apache/singa) (πŸ‘¨β€πŸ’» 91 Β· πŸ”€ 1.2K Β· πŸ“¦ 4 Β· πŸ“‹ 130 - 40% open Β· ⏱️ 17.08.2024): ``` git clone https://github.com/apache/singa ``` -- [Conda](https://anaconda.org/nusdbsystem/singa) (πŸ“₯ 750 Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/nusdbsystem/singa) (πŸ“₯ 770 Β· ⏱️ 16.06.2023): ``` conda install -c nusdbsystem singa ``` -- [Docker Hub](https://hub.docker.com/r/apache/singa) (πŸ“₯ 6.6K Β· ⭐ 4 Β· ⏱️ 31.05.2022): +- [Docker Hub](https://hub.docker.com/r/apache/singa) (πŸ“₯ 7.9K Β· ⭐ 4 Β· ⏱️ 31.05.2022): ``` docker pull apache/singa ```
-
Hivemind (πŸ₯‰24 Β· ⭐ 1.9K) - Decentralized deep learning in PyTorch. Built to train models on.. MIT +
Hivemind (πŸ₯‰24 Β· ⭐ 2K) - Decentralized deep learning in PyTorch. Built to train models on thousands.. MIT -- [GitHub](https://github.com/learning-at-home/hivemind) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 130 Β· πŸ“¦ 100 Β· πŸ“‹ 170 - 40% open Β· ⏱️ 04.12.2023): +- [GitHub](https://github.com/learning-at-home/hivemind) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 150 Β· πŸ“¦ 110 Β· πŸ“‹ 180 - 41% open Β· ⏱️ 15.07.2024): ``` git clone https://github.com/learning-at-home/hivemind ``` -- [PyPi](https://pypi.org/project/hivemind) (πŸ“₯ 3.4K / month Β· πŸ“¦ 10 Β· ⏱️ 31.08.2023): +- [PyPi](https://pypi.org/project/hivemind) (πŸ“₯ 920 / month Β· πŸ“¦ 10 Β· ⏱️ 31.08.2023): ``` pip install hivemind ```
-
MMLSpark (πŸ₯‰22 Β· ⭐ 5K) - Simple and Distributed Machine Learning. MIT - -- [GitHub](https://github.com/microsoft/SynapseML) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 820 Β· πŸ“‹ 750 - 46% open Β· ⏱️ 21.05.2024): - - ``` - git clone https://github.com/microsoft/SynapseML - ``` -- [PyPi](https://pypi.org/project/mmlspark) (πŸ“₯ 1 / month Β· ⏱️ 18.03.2020): - ``` - pip install mmlspark - ``` -
-
Mesh (πŸ₯‰22 Β· ⭐ 1.6K Β· πŸ’€) - Mesh TensorFlow: Model Parallelism Made Easier. Apache-2 +
Mesh (πŸ₯‰23 Β· ⭐ 1.6K Β· πŸ’€) - Mesh TensorFlow: Model Parallelism Made Easier. Apache-2 -- [GitHub](https://github.com/tensorflow/mesh) (πŸ‘¨β€πŸ’» 50 Β· πŸ”€ 260 Β· πŸ“‹ 120 - 84% open Β· ⏱️ 17.11.2023): +- [GitHub](https://github.com/tensorflow/mesh) (πŸ‘¨β€πŸ’» 50 Β· πŸ”€ 250 Β· πŸ“‹ 120 - 84% open Β· ⏱️ 17.11.2023): ``` git clone https://github.com/tensorflow/mesh ``` -- [PyPi](https://pypi.org/project/mesh-tensorflow) (πŸ“₯ 42K / month Β· πŸ“¦ 3 Β· ⏱️ 15.05.2022): +- [PyPi](https://pypi.org/project/mesh-tensorflow) (πŸ“₯ 72K / month Β· πŸ“¦ 3 Β· ⏱️ 15.05.2022): ``` pip install mesh-tensorflow ```
-
analytics-zoo (πŸ₯‰21 Β· ⭐ 2.6K Β· 🐣) - Distributed Tensorflow, Keras and PyTorch on Apache.. Apache-2 +
MMLSpark (πŸ₯‰22 Β· ⭐ 5K) - Simple and Distributed Machine Learning. MIT -- [GitHub](https://github.com/intel-analytics/analytics-zoo) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 730 Β· πŸ“‹ 1.3K - 32% open Β· ⏱️ 08.04.2024): +- [GitHub](https://github.com/microsoft/SynapseML) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 830 Β· πŸ“‹ 770 - 47% open Β· ⏱️ 30.08.2024): ``` - git clone https://github.com/intel-analytics/analytics-zoo + git clone https://github.com/microsoft/SynapseML ``` -- [PyPi](https://pypi.org/project/analytics-zoo) (πŸ“₯ 350 / month Β· πŸ“¦ 1 Β· ⏱️ 22.08.2022): +- [PyPi](https://pypi.org/project/mmlspark) (πŸ“₯ 1 / month Β· ⏱️ 18.03.2020): ``` - pip install analytics-zoo + pip install mmlspark ```
-
launchpad (πŸ₯‰21 Β· ⭐ 310 Β· πŸ’€) - Launchpad is a library that simplifies writing.. Apache-2 +
analytics-zoo (πŸ₯‰22 Β· ⭐ 2.6K Β· 🐣) - Distributed Tensorflow, Keras and PyTorch on Apache.. Apache-2 -- [GitHub](https://github.com/google-deepmind/launchpad) (πŸ‘¨β€πŸ’» 28 Β· πŸ”€ 34 Β· πŸ“¦ 98 Β· πŸ“‹ 40 - 47% open Β· ⏱️ 22.08.2023): +- [GitHub](https://github.com/intel-analytics/analytics-zoo) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 730 Β· πŸ“‹ 1.3K - 32% open Β· ⏱️ 05.08.2024): ``` - git clone https://github.com/deepmind/launchpad + git clone https://github.com/intel-analytics/analytics-zoo ``` -- [PyPi](https://pypi.org/project/dm-launchpad) (πŸ“₯ 1.5K / month Β· πŸ“¦ 1 Β· ⏱️ 28.04.2022): +- [PyPi](https://pypi.org/project/analytics-zoo) (πŸ“₯ 580 / month Β· πŸ“¦ 1 Β· ⏱️ 22.08.2022): ``` - pip install dm-launchpad + pip install analytics-zoo ```
-
Show 15 hidden projects... +
Show 16 hidden projects... -- DEAP (πŸ₯ˆ32 Β· ⭐ 5.6K) - Distributed Evolutionary Algorithms in Python. ❗️LGPL-3.0 -- ipyparallel (πŸ₯ˆ30 Β· ⭐ 2.6K) - IPython Parallel: Interactive Parallel Computing in.. ❗Unlicensed +- DEAP (πŸ₯ˆ33 Β· ⭐ 5.8K) - Distributed Evolutionary Algorithms in Python. ❗️LGPL-3.0 +- ipyparallel (πŸ₯ˆ29 Β· ⭐ 2.6K) - IPython Parallel: Interactive Parallel Computing in.. ❗Unlicensed - TensorFlowOnSpark (πŸ₯‰27 Β· ⭐ 3.9K Β· πŸ’€) - TensorFlowOnSpark brings TensorFlow programs to.. Apache-2 -- Elephas (πŸ₯‰27 Β· ⭐ 1.6K Β· πŸ’€) - Distributed Deep learning with Keras & Spark. MIT keras -- sk-dist (πŸ₯‰22 Β· ⭐ 280 Β· πŸ’€) - Distributed scikit-learn meta-estimators in PySpark. Apache-2 -- somoclu (πŸ₯‰21 Β· ⭐ 260) - Massively parallel self-organizing maps: accelerate training on multicore.. MIT +- Elephas (πŸ₯‰25 Β· ⭐ 1.6K Β· πŸ’€) - Distributed Deep learning with Keras & Spark. MIT keras +- launchpad (πŸ₯‰21 Β· ⭐ 310 Β· πŸ’€) - Launchpad is a library that simplifies writing.. Apache-2 +- sk-dist (πŸ₯‰21 Β· ⭐ 280 Β· πŸ’€) - Distributed scikit-learn meta-estimators in PySpark. Apache-2 - BytePS (πŸ₯‰20 Β· ⭐ 3.6K Β· πŸ’€) - A high performance and generic framework for distributed DNN.. Apache-2 -- TensorFrames (πŸ₯‰20 Β· ⭐ 750 Β· πŸ’€) - [DEPRECATED] Tensorflow wrapper for DataFrames on.. Apache-2 -- mesh-transformer-jax (πŸ₯‰18 Β· ⭐ 6.2K Β· πŸ’€) - Model parallel transformers in JAX and Haiku. Apache-2 -- parallelformers (πŸ₯‰18 Β· ⭐ 760 Β· πŸ’€) - Parallelformers: An Efficient Model Parallelization.. Apache-2 +- somoclu (πŸ₯‰20 Β· ⭐ 260 Β· πŸ’€) - Massively parallel self-organizing maps: accelerate training on.. MIT +- mesh-transformer-jax (πŸ₯‰18 Β· ⭐ 6.3K Β· πŸ’€) - Model parallel transformers in JAX and Haiku. Apache-2 - bluefog (πŸ₯‰18 Β· ⭐ 290 Β· πŸ’€) - Distributed and decentralized training framework for PyTorch.. Apache-2 -- Fiber (πŸ₯‰17 Β· ⭐ 1K Β· πŸ’€) - Distributed Computing for AI Made Simple. Apache-2 -- LazyCluster (πŸ₯‰13 Β· ⭐ 50 Β· πŸ’€) - Distributed machine learning made simple. Apache-2 +- parallelformers (πŸ₯‰17 Β· ⭐ 780 Β· πŸ’€) - Parallelformers: An Efficient Model Parallelization.. Apache-2 +- Fiber (πŸ₯‰16 Β· ⭐ 1K Β· πŸ’€) - Distributed Computing for AI Made Simple. Apache-2 +- TensorFrames (πŸ₯‰16 Β· ⭐ 720 Β· πŸ’€) - Tensorflow wrapper for DataFrames on Apache Spark. Apache-2 +- LazyCluster (πŸ₯‰14 Β· ⭐ 49 Β· πŸ’€) - Distributed machine learning made simple. Apache-2 - moolib (πŸ₯‰11 Β· ⭐ 360 Β· πŸ’€) - A library for distributed ML training with PyTorch. MIT -- autodist (πŸ₯‰10 Β· ⭐ 130 Β· πŸ’€) - Simple Distributed Deep Learning on TensorFlow. Apache-2 +- autodist (πŸ₯‰11 Β· ⭐ 130 Β· πŸ’€) - Simple Distributed Deep Learning on TensorFlow. Apache-2

@@ -4758,316 +4689,335 @@ _Libraries that provide capabilities to distribute and parallelize machine learn _Libraries for hyperparameter optimization, automl and neural architecture search._ -
featuretools (πŸ₯‡34 Β· ⭐ 7.1K) - An open source python library for automated feature engineering. BSD-3 +
Optuna (πŸ₯‡43 Β· ⭐ 10K Β· πŸ“ˆ) - A hyperparameter optimization framework. MIT -- [GitHub](https://github.com/alteryx/featuretools) (πŸ‘¨β€πŸ’» 72 Β· πŸ”€ 860 Β· πŸ“¦ 1.7K Β· πŸ“‹ 1K - 14% open Β· ⏱️ 03.06.2024): +- [GitHub](https://github.com/optuna/optuna) (πŸ‘¨β€πŸ’» 270 Β· πŸ”€ 990 Β· πŸ“¦ 17K Β· πŸ“‹ 1.7K - 4% open Β· ⏱️ 05.09.2024): ``` - git clone https://github.com/alteryx/featuretools + git clone https://github.com/optuna/optuna ``` -- [PyPi](https://pypi.org/project/featuretools) (πŸ“₯ 67K / month Β· πŸ“¦ 73 Β· ⏱️ 14.05.2024): +- [PyPi](https://pypi.org/project/optuna) (πŸ“₯ 3.3M / month Β· πŸ“¦ 950 Β· ⏱️ 02.09.2024): ``` - pip install featuretools + pip install optuna ``` -- [Conda](https://anaconda.org/conda-forge/featuretools) (πŸ“₯ 190K Β· ⏱️ 15.05.2024): +- [Conda](https://anaconda.org/conda-forge/optuna) (πŸ“₯ 1.5M Β· ⏱️ 03.09.2024): ``` - conda install -c conda-forge featuretools + conda install -c conda-forge optuna + ``` +
+
NNI (πŸ₯‡34 Β· ⭐ 14K Β· πŸ’€) - An open source AutoML toolkit for automate machine learning lifecycle,.. MIT + +- [GitHub](https://github.com/microsoft/nni) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 1.8K Β· πŸ“¦ 710 Β· πŸ“‹ 2.1K - 19% open Β· ⏱️ 26.10.2023): + + ``` + git clone https://github.com/microsoft/nni + ``` +- [PyPi](https://pypi.org/project/nni) (πŸ“₯ 160K / month Β· πŸ“¦ 47 Β· ⏱️ 14.09.2023): + ``` + pip install nni ```
-
BoTorch (πŸ₯‡34 Β· ⭐ 3K) - Bayesian optimization in PyTorch. MIT +
BoTorch (πŸ₯‡34 Β· ⭐ 3.1K) - Bayesian optimization in PyTorch. MIT -- [GitHub](https://github.com/pytorch/botorch) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 370 Β· πŸ“¦ 1K Β· πŸ“‹ 500 - 14% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/pytorch/botorch) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 390 Β· πŸ“¦ 1.1K Β· πŸ“‹ 520 - 12% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/pytorch/botorch ``` -- [PyPi](https://pypi.org/project/botorch) (πŸ“₯ 160K / month Β· πŸ“¦ 74 Β· ⏱️ 01.05.2024): +- [PyPi](https://pypi.org/project/botorch) (πŸ“₯ 180K / month Β· πŸ“¦ 83 Β· ⏱️ 22.07.2024): ``` pip install botorch ``` -- [Conda](https://anaconda.org/conda-forge/botorch) (πŸ“₯ 110K Β· ⏱️ 01.05.2024): +- [Conda](https://anaconda.org/conda-forge/botorch) (πŸ“₯ 120K Β· ⏱️ 23.07.2024): ``` conda install -c conda-forge botorch ```
Ax (πŸ₯‡34 Β· ⭐ 2.3K) - Adaptive Experimentation Platform. MIT -- [GitHub](https://github.com/facebook/Ax) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 290 Β· πŸ“¦ 730 Β· πŸ“‹ 740 - 15% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/facebook/Ax) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 300 Β· πŸ“¦ 780 Β· πŸ“‹ 770 - 7% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/facebook/Ax ``` -- [PyPi](https://pypi.org/project/ax-platform) (πŸ“₯ 95K / month Β· πŸ“¦ 48 Β· ⏱️ 02.05.2024): +- [PyPi](https://pypi.org/project/ax-platform) (πŸ“₯ 94K / month Β· πŸ“¦ 50 Β· ⏱️ 23.07.2024): ``` pip install ax-platform ``` -- [Conda](https://anaconda.org/conda-forge/ax-platform) (πŸ“₯ 20K Β· ⏱️ 03.05.2024): +- [Conda](https://anaconda.org/conda-forge/ax-platform) (πŸ“₯ 26K Β· ⏱️ 24.07.2024): ``` conda install -c conda-forge ax-platform ```
-
NNI (πŸ₯‡33 Β· ⭐ 14K Β· πŸ’€) - An open source AutoML toolkit for automate machine learning lifecycle,.. MIT +
Bayesian Optimization (πŸ₯‡33 Β· ⭐ 7.8K) - A Python implementation of global optimization with.. MIT -- [GitHub](https://github.com/microsoft/nni) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 1.8K Β· πŸ“¦ 660 Β· πŸ“‹ 2.1K - 18% open Β· ⏱️ 26.10.2023): +- [GitHub](https://github.com/bayesian-optimization/BayesianOptimization) (πŸ‘¨β€πŸ’» 47 Β· πŸ”€ 1.5K Β· πŸ“₯ 160 Β· πŸ“¦ 2.9K Β· πŸ“‹ 360 - 3% open Β· ⏱️ 23.07.2024): ``` - git clone https://github.com/microsoft/nni + git clone https://github.com/fmfn/BayesianOptimization ``` -- [PyPi](https://pypi.org/project/nni) (πŸ“₯ 15K / month Β· πŸ“¦ 38 Β· ⏱️ 14.09.2023): +- [PyPi](https://pypi.org/project/bayesian-optimization) (πŸ“₯ 440K / month Β· πŸ“¦ 140 Β· ⏱️ 10.07.2024): ``` - pip install nni + pip install bayesian-optimization ```
-
AutoGluon (πŸ₯‡33 Β· ⭐ 7.3K) - Fast and Accurate ML in 3 Lines of Code. Apache-2 +
AutoGluon (πŸ₯‡33 Β· ⭐ 7.6K) - Fast and Accurate ML in 3 Lines of Code. Apache-2 -- [GitHub](https://github.com/autogluon/autogluon) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 860 Β· πŸ“¦ 720 Β· πŸ“‹ 1.3K - 26% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/autogluon/autogluon) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 900 Β· πŸ“¦ 800 Β· πŸ“‹ 1.4K - 24% open Β· ⏱️ 04.09.2024): ``` git clone https://github.com/autogluon/autogluon ``` -- [PyPi](https://pypi.org/project/autogluon) (πŸ“₯ 77K / month Β· πŸ“¦ 24 Β· ⏱️ 06.06.2024): +- [PyPi](https://pypi.org/project/autogluon) (πŸ“₯ 87K / month Β· πŸ“¦ 25 Β· ⏱️ 05.09.2024): ``` pip install autogluon ``` -- [Docker Hub](https://hub.docker.com/r/autogluon/autogluon) (πŸ“₯ 8K Β· ⭐ 17 Β· ⏱️ 07.03.2024): +- [Conda](https://anaconda.org/conda-forge/autogluon) (πŸ“₯ 18K Β· ⏱️ 18.06.2024): + ``` + conda install -c conda-forge autogluon + ``` +- [Docker Hub](https://hub.docker.com/r/autogluon/autogluon) (πŸ“₯ 9.8K Β· ⭐ 17 Β· ⏱️ 07.03.2024): ``` docker pull autogluon/autogluon ```
-
AutoKeras (πŸ₯ˆ32 Β· ⭐ 9.1K) - AutoML library for deep learning. Apache-2 +
Hyperopt (πŸ₯‡33 Β· ⭐ 7.2K) - Distributed Asynchronous Hyperparameter Optimization in Python. BSD-3 -- [GitHub](https://github.com/keras-team/autokeras) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 1.4K Β· πŸ“₯ 18K Β· πŸ“¦ 680 Β· πŸ“‹ 900 - 15% open Β· ⏱️ 20.03.2024): +- [GitHub](https://github.com/hyperopt/hyperopt) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 1K Β· πŸ“¦ 17K Β· πŸ“‹ 670 - 26% open Β· ⏱️ 13.03.2024): ``` - git clone https://github.com/keras-team/autokeras - ``` -- [PyPi](https://pypi.org/project/autokeras) (πŸ“₯ 18K / month Β· πŸ“¦ 13 Β· ⏱️ 20.03.2024): - ``` - pip install autokeras + git clone https://github.com/hyperopt/hyperopt ``` -
-
Bayesian Optimization (πŸ₯ˆ32 Β· ⭐ 7.6K) - A Python implementation of global optimization with.. MIT - -- [GitHub](https://github.com/bayesian-optimization/BayesianOptimization) (πŸ‘¨β€πŸ’» 44 Β· πŸ”€ 1.5K Β· πŸ“₯ 150 Β· πŸ“¦ 2.7K Β· πŸ“‹ 340 - 3% open Β· ⏱️ 06.03.2024): - +- [PyPi](https://pypi.org/project/hyperopt) (πŸ“₯ 2.3M / month Β· πŸ“¦ 440 Β· ⏱️ 17.11.2021): ``` - git clone https://github.com/fmfn/BayesianOptimization + pip install hyperopt ``` -- [PyPi](https://pypi.org/project/bayesian-optimization) (πŸ“₯ 530K / month Β· πŸ“¦ 130 Β· ⏱️ 25.04.2023): +- [Conda](https://anaconda.org/conda-forge/hyperopt) (πŸ“₯ 780K Β· ⏱️ 16.06.2023): ``` - pip install bayesian-optimization + conda install -c conda-forge hyperopt ```
-
Hyperopt (πŸ₯ˆ32 Β· ⭐ 7.1K) - Distributed Asynchronous Hyperparameter Optimization in Python. BSD-3 +
featuretools (πŸ₯‡33 Β· ⭐ 7.2K) - An open source python library for automated feature engineering. BSD-3 -- [GitHub](https://github.com/hyperopt/hyperopt) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 1K Β· πŸ“¦ 15K Β· πŸ“‹ 660 - 31% open Β· ⏱️ 13.03.2024): +- [GitHub](https://github.com/alteryx/featuretools) (πŸ‘¨β€πŸ’» 72 Β· πŸ”€ 870 Β· πŸ“¦ 1.7K Β· πŸ“‹ 1K - 14% open Β· ⏱️ 21.06.2024): ``` - git clone https://github.com/hyperopt/hyperopt + git clone https://github.com/alteryx/featuretools ``` -- [PyPi](https://pypi.org/project/hyperopt) (πŸ“₯ 2.4M / month Β· πŸ“¦ 430 Β· ⏱️ 17.11.2021): +- [PyPi](https://pypi.org/project/featuretools) (πŸ“₯ 59K / month Β· πŸ“¦ 74 Β· ⏱️ 14.05.2024): ``` - pip install hyperopt + pip install featuretools ``` -- [Conda](https://anaconda.org/conda-forge/hyperopt) (πŸ“₯ 770K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/featuretools) (πŸ“₯ 200K Β· ⏱️ 15.05.2024): ``` - conda install -c conda-forge hyperopt + conda install -c conda-forge featuretools ```
-
Keras Tuner (πŸ₯ˆ32 Β· ⭐ 2.8K) - A Hyperparameter Tuning Library for Keras. Apache-2 +
AutoKeras (πŸ₯ˆ31 Β· ⭐ 9.1K) - AutoML library for deep learning. Apache-2 -- [GitHub](https://github.com/keras-team/keras-tuner) (πŸ‘¨β€πŸ’» 61 Β· πŸ”€ 380 Β· πŸ“¦ 3.8K Β· πŸ“‹ 480 - 43% open Β· ⏱️ 04.03.2024): +- [GitHub](https://github.com/keras-team/autokeras) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 1.4K Β· πŸ“₯ 19K Β· πŸ“¦ 730 Β· πŸ“‹ 900 - 15% open Β· ⏱️ 20.03.2024): ``` - git clone https://github.com/keras-team/keras-tuner - ``` -- [PyPi](https://pypi.org/project/keras-tuner) (πŸ“₯ 270K / month Β· πŸ“¦ 100 Β· ⏱️ 04.03.2024): - ``` - pip install keras-tuner + git clone https://github.com/keras-team/autokeras ``` -- [Conda](https://anaconda.org/conda-forge/keras-tuner) (πŸ“₯ 32K Β· ⏱️ 05.03.2024): +- [PyPi](https://pypi.org/project/autokeras) (πŸ“₯ 48K / month Β· πŸ“¦ 13 Β· ⏱️ 20.03.2024): ``` - conda install -c conda-forge keras-tuner + pip install autokeras ```
-
nevergrad (πŸ₯ˆ30 Β· ⭐ 3.9K) - A Python toolbox for performing gradient-free optimization. MIT +
nevergrad (πŸ₯ˆ31 Β· ⭐ 3.9K) - A Python toolbox for performing gradient-free optimization. MIT -- [GitHub](https://github.com/facebookresearch/nevergrad) (πŸ‘¨β€πŸ’» 55 Β· πŸ”€ 350 Β· πŸ“¦ 690 Β· πŸ“‹ 300 - 42% open Β· ⏱️ 08.04.2024): +- [GitHub](https://github.com/facebookresearch/nevergrad) (πŸ‘¨β€πŸ’» 56 Β· πŸ”€ 350 Β· πŸ“¦ 740 Β· πŸ“‹ 310 - 43% open Β· ⏱️ 28.08.2024): ``` git clone https://github.com/facebookresearch/nevergrad ``` -- [PyPi](https://pypi.org/project/nevergrad) (πŸ“₯ 240K / month Β· πŸ“¦ 46 Β· ⏱️ 20.02.2024): +- [PyPi](https://pypi.org/project/nevergrad) (πŸ“₯ 150K / month Β· πŸ“¦ 58 Β· ⏱️ 16.08.2024): ``` pip install nevergrad ``` -- [Conda](https://anaconda.org/conda-forge/nevergrad) (πŸ“₯ 49K Β· ⏱️ 09.01.2024): +- [Conda](https://anaconda.org/conda-forge/nevergrad) (πŸ“₯ 53K Β· ⏱️ 09.01.2024): ``` conda install -c conda-forge nevergrad ```
-
mljar-supervised (πŸ₯ˆ28 Β· ⭐ 3K) - Python package for AutoML on Tabular Data with Feature.. MIT +
Keras Tuner (πŸ₯ˆ30 Β· ⭐ 2.8K) - A Hyperparameter Tuning Library for Keras. Apache-2 -- [GitHub](https://github.com/mljar/mljar-supervised) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 390 Β· πŸ“¦ 110 Β· πŸ“‹ 630 - 24% open Β· ⏱️ 03.06.2024): +- [GitHub](https://github.com/keras-team/keras-tuner) (πŸ‘¨β€πŸ’» 61 Β· πŸ”€ 390 Β· πŸ“¦ 4.3K Β· πŸ“‹ 490 - 44% open Β· ⏱️ 24.06.2024): ``` - git clone https://github.com/mljar/mljar-supervised + git clone https://github.com/keras-team/keras-tuner ``` -- [PyPi](https://pypi.org/project/mljar-supervised) (πŸ“₯ 2.9K / month Β· πŸ“¦ 3 Β· ⏱️ 03.06.2024): +- [PyPi](https://pypi.org/project/keras-tuner) (πŸ“₯ 330K / month Β· πŸ“¦ 120 Β· ⏱️ 04.03.2024): ``` - pip install mljar-supervised + pip install keras-tuner ``` -- [Conda](https://anaconda.org/conda-forge/mljar-supervised) (πŸ“₯ 15K Β· ⏱️ 03.06.2024): +- [Conda](https://anaconda.org/conda-forge/keras-tuner) (πŸ“₯ 38K Β· ⏱️ 05.03.2024): ``` - conda install -c conda-forge mljar-supervised + conda install -c conda-forge keras-tuner ```
-
Talos (πŸ₯ˆ27 Β· ⭐ 1.6K) - Hyperparameter Experiments with TensorFlow and Keras. MIT +
mljar-supervised (πŸ₯ˆ29 Β· ⭐ 3K) - Python package for AutoML on Tabular Data with Feature.. MIT -- [GitHub](https://github.com/autonomio/talos) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 270 Β· πŸ“¦ 170 Β· πŸ“‹ 400 - 2% open Β· ⏱️ 22.04.2024): +- [GitHub](https://github.com/mljar/mljar-supervised) (πŸ‘¨β€πŸ’» 28 Β· πŸ”€ 400 Β· πŸ“¦ 130 Β· πŸ“‹ 660 - 24% open Β· ⏱️ 02.09.2024): ``` - git clone https://github.com/autonomio/talos + git clone https://github.com/mljar/mljar-supervised ``` -- [PyPi](https://pypi.org/project/talos) (πŸ“₯ 1.3K / month Β· πŸ“¦ 8 Β· ⏱️ 21.04.2024): +- [PyPi](https://pypi.org/project/mljar-supervised) (πŸ“₯ 4.9K / month Β· πŸ“¦ 4 Β· ⏱️ 03.06.2024): ``` - pip install talos + pip install mljar-supervised + ``` +- [Conda](https://anaconda.org/conda-forge/mljar-supervised) (πŸ“₯ 21K Β· ⏱️ 03.06.2024): + ``` + conda install -c conda-forge mljar-supervised ```
-
lazypredict (πŸ₯ˆ26 Β· ⭐ 2.7K) - Lazy Predict help build a lot of basic models without much code.. MIT +
lazypredict (πŸ₯ˆ26 Β· ⭐ 2.9K) - Lazy Predict help build a lot of basic models without much code.. MIT -- [GitHub](https://github.com/shankarpandala/lazypredict) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 310 Β· πŸ“¦ 960 Β· πŸ“‹ 120 - 66% open Β· ⏱️ 02.06.2024): +- [GitHub](https://github.com/shankarpandala/lazypredict) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 330 Β· πŸ“¦ 1K Β· πŸ“‹ 120 - 67% open Β· ⏱️ 02.06.2024): ``` git clone https://github.com/shankarpandala/lazypredict ``` -- [PyPi](https://pypi.org/project/lazypredict) (πŸ“₯ 19K / month Β· πŸ“¦ 1 Β· ⏱️ 28.09.2022): +- [PyPi](https://pypi.org/project/lazypredict) (πŸ“₯ 17K / month Β· πŸ“¦ 1 Β· ⏱️ 28.09.2022): ``` pip install lazypredict ``` -- [Conda](https://anaconda.org/conda-forge/lazypredict) (πŸ“₯ 3K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/lazypredict) (πŸ“₯ 3.4K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge lazypredict ```
-
FEDOT (πŸ₯‰24 Β· ⭐ 620) - Automated modeling and machine learning framework FEDOT. BSD-3 +
Talos (πŸ₯ˆ26 Β· ⭐ 1.6K) - Hyperparameter Experiments with TensorFlow and Keras. MIT -- [GitHub](https://github.com/aimclub/FEDOT) (πŸ‘¨β€πŸ’» 33 Β· πŸ”€ 84 Β· πŸ“¦ 46 Β· πŸ“‹ 540 - 17% open Β· ⏱️ 29.05.2024): +- [GitHub](https://github.com/autonomio/talos) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 270 Β· πŸ“¦ 190 Β· πŸ“‹ 400 - 2% open Β· ⏱️ 22.04.2024): + + ``` + git clone https://github.com/autonomio/talos + ``` +- [PyPi](https://pypi.org/project/talos) (πŸ“₯ 1.8K / month Β· πŸ“¦ 8 Β· ⏱️ 21.04.2024): + ``` + pip install talos + ``` +
+
FEDOT (πŸ₯ˆ25 Β· ⭐ 630) - Automated modeling and machine learning framework FEDOT. BSD-3 + +- [GitHub](https://github.com/aimclub/FEDOT) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 86 Β· πŸ“¦ 52 Β· πŸ“‹ 540 - 17% open Β· ⏱️ 04.09.2024): ``` git clone https://github.com/nccr-itmo/FEDOT ``` -- [PyPi](https://pypi.org/project/fedot) (πŸ“₯ 1.3K / month Β· πŸ“¦ 5 Β· ⏱️ 03.05.2024): +- [PyPi](https://pypi.org/project/fedot) (πŸ“₯ 1.1K / month Β· πŸ“¦ 5 Β· ⏱️ 28.08.2024): ``` pip install fedot ```
-
featurewiz (πŸ₯‰23 Β· ⭐ 560) - Use advanced feature engineering strategies and select best.. Apache-2 +
Hyperactive (πŸ₯ˆ25 Β· ⭐ 500) - An optimization and data collection toolbox for convenient and fast.. MIT -- [GitHub](https://github.com/AutoViML/featurewiz) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 85 Β· πŸ“¦ 68 Β· πŸ“‹ 92 - 1% open Β· ⏱️ 02.05.2024): +- [GitHub](https://github.com/SimonBlanke/Hyperactive) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 41 Β· πŸ“₯ 210 Β· πŸ“¦ 34 Β· πŸ“‹ 73 - 16% open Β· ⏱️ 30.08.2024): ``` - git clone https://github.com/AutoViML/featurewiz + git clone https://github.com/SimonBlanke/Hyperactive ``` -- [PyPi](https://pypi.org/project/featurewiz) (πŸ“₯ 8.9K / month Β· πŸ“¦ 2 Β· ⏱️ 10.02.2024): +- [PyPi](https://pypi.org/project/hyperactive) (πŸ“₯ 3.3K / month Β· πŸ“¦ 13 Β· ⏱️ 15.08.2024): ``` - pip install featurewiz + pip install hyperactive ```
-
Auto ViML (πŸ₯‰23 Β· ⭐ 510) - Automatically Build Multiple ML Models with a Single Line of Code... Apache-2 +
Auto ViML (πŸ₯‰22 Β· ⭐ 520) - Automatically Build Multiple ML Models with a Single Line of Code... Apache-2 -- [GitHub](https://github.com/AutoViML/Auto_ViML) (πŸ‘¨β€πŸ’» 9 Β· πŸ”€ 99 Β· πŸ“¦ 25 Β· πŸ“‹ 34 - 2% open Β· ⏱️ 11.05.2024): +- [GitHub](https://github.com/AutoViML/Auto_ViML) (πŸ‘¨β€πŸ’» 9 Β· πŸ”€ 99 Β· πŸ“¦ 26 Β· πŸ“‹ 34 - 2% open Β· ⏱️ 11.05.2024): ``` git clone https://github.com/AutoViML/Auto_ViML ``` -- [PyPi](https://pypi.org/project/autoviml) (πŸ“₯ 2K / month Β· πŸ“¦ 3 Β· ⏱️ 11.05.2024): +- [PyPi](https://pypi.org/project/autoviml) (πŸ“₯ 2.9K / month Β· πŸ“¦ 3 Β· ⏱️ 11.05.2024): ``` pip install autoviml ```
-
Hyperactive (πŸ₯‰23 Β· ⭐ 490) - An optimization and data collection toolbox for convenient and fast.. MIT +
featurewiz (πŸ₯‰21 Β· ⭐ 580) - Use advanced feature engineering strategies and select best.. Apache-2 -- [GitHub](https://github.com/SimonBlanke/Hyperactive) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 41 Β· πŸ“₯ 140 Β· πŸ“¦ 29 Β· πŸ“‹ 60 - 13% open Β· ⏱️ 01.06.2024): +- [GitHub](https://github.com/AutoViML/featurewiz) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 85 Β· πŸ“¦ 72 Β· πŸ“‹ 95 - 3% open Β· ⏱️ 02.05.2024): ``` - git clone https://github.com/SimonBlanke/Hyperactive + git clone https://github.com/AutoViML/featurewiz ``` -- [PyPi](https://pypi.org/project/hyperactive) (πŸ“₯ 2.9K / month Β· πŸ“¦ 13 Β· ⏱️ 17.05.2024): +- [PyPi](https://pypi.org/project/featurewiz) (πŸ“₯ 9.5K / month Β· πŸ“¦ 2 Β· ⏱️ 10.02.2024): ``` - pip install hyperactive + pip install featurewiz ```
-
AlphaPy (πŸ₯‰19 Β· ⭐ 1.1K) - Python AutoML for Trading Systems and Sports Betting. Apache-2 +
AlphaPy (πŸ₯‰20 Β· ⭐ 1.1K Β· πŸ’€) - Python AutoML for Trading Systems and Sports Betting. Apache-2 -- [GitHub](https://github.com/ScottfreeLLC/AlphaPy) (πŸ‘¨β€πŸ’» 5 Β· πŸ”€ 190 Β· πŸ“¦ 4 Β· πŸ“‹ 42 - 30% open Β· ⏱️ 10.02.2024): +- [GitHub](https://github.com/ScottfreeLLC/AlphaPy) (πŸ‘¨β€πŸ’» 5 Β· πŸ”€ 200 Β· πŸ“¦ 5 Β· πŸ“‹ 42 - 30% open Β· ⏱️ 10.02.2024): ``` git clone https://github.com/ScottfreeLLC/AlphaPy ``` -- [PyPi](https://pypi.org/project/alphapy) (πŸ“₯ 150 / month Β· ⏱️ 29.08.2020): +- [PyPi](https://pypi.org/project/alphapy) (πŸ“₯ 240 / month Β· ⏱️ 29.08.2020): ``` pip install alphapy ```
-
shap-hypetune (πŸ₯‰19 Β· ⭐ 540) - A python package for simultaneous Hyperparameters Tuning and.. MIT +
opytimizer (πŸ₯‰19 Β· ⭐ 600) - Opytimizer is a Python library consisting of meta-heuristic.. Apache-2 -- [GitHub](https://github.com/cerlymarco/shap-hypetune) (πŸ‘¨β€πŸ’» 3 Β· πŸ”€ 68 Β· πŸ“¦ 16 Β· πŸ“‹ 33 - 12% open Β· ⏱️ 21.02.2024): +- [GitHub](https://github.com/gugarosa/opytimizer) (πŸ‘¨β€πŸ’» 4 Β· πŸ”€ 40 Β· πŸ“¦ 17 Β· πŸ“‹ 23 - 4% open Β· ⏱️ 18.08.2024): ``` - git clone https://github.com/cerlymarco/shap-hypetune + git clone https://github.com/gugarosa/opytimizer ``` -- [PyPi](https://pypi.org/project/shap-hypetune) (πŸ“₯ 1.2K / month Β· πŸ“¦ 2 Β· ⏱️ 21.02.2024): +- [PyPi](https://pypi.org/project/opytimizer) (πŸ“₯ 630 / month Β· ⏱️ 18.08.2024): ``` - pip install shap-hypetune + pip install opytimizer ```
-
opytimizer (πŸ₯‰17 Β· ⭐ 600) - Opytimizer is a Python library consisting of meta-heuristic.. Apache-2 +
shap-hypetune (πŸ₯‰18 Β· ⭐ 560 Β· πŸ’€) - A python package for simultaneous Hyperparameters Tuning and.. MIT -- [GitHub](https://github.com/gugarosa/opytimizer) (πŸ‘¨β€πŸ’» 4 Β· πŸ”€ 41 Β· πŸ“¦ 16 Β· πŸ“‹ 21 - 4% open Β· ⏱️ 21.12.2023): +- [GitHub](https://github.com/cerlymarco/shap-hypetune) (πŸ‘¨β€πŸ’» 3 Β· πŸ”€ 70 Β· πŸ“¦ 19 Β· πŸ“‹ 36 - 11% open Β· ⏱️ 21.02.2024): ``` - git clone https://github.com/gugarosa/opytimizer + git clone https://github.com/cerlymarco/shap-hypetune ``` -- [PyPi](https://pypi.org/project/opytimizer) (πŸ“₯ 250 / month Β· ⏱️ 04.05.2022): +- [PyPi](https://pypi.org/project/shap-hypetune) (πŸ“₯ 1.4K / month Β· πŸ“¦ 2 Β· ⏱️ 21.02.2024): ``` - pip install opytimizer + pip install shap-hypetune ```
-
Show 32 hidden projects... +
Show 31 hidden projects... -- Optuna (πŸ₯‡39 Β· ⭐ 9.9K) - A hyperparameter optimization framework. ❗Unlicensed -- scikit-optimize (πŸ₯‡34 Β· ⭐ 2.7K Β· πŸ’€) - Sequential model-based optimization with a.. BSD-3 -- TPOT (πŸ₯‡33 Β· ⭐ 9.5K) - A Python Automated Machine Learning tool that optimizes machine.. ❗️LGPL-3.0 -- auto-sklearn (πŸ₯ˆ30 Β· ⭐ 7.4K Β· πŸ’€) - Automated Machine Learning with scikit-learn. BSD-3 +- scikit-optimize (πŸ₯‡33 Β· ⭐ 2.7K Β· πŸ’€) - Sequential model-based optimization with a.. BSD-3 +- TPOT (πŸ₯ˆ32 Β· ⭐ 9.7K Β· πŸ’€) - A Python Automated Machine Learning tool that optimizes.. ❗️LGPL-3.0 +- auto-sklearn (πŸ₯ˆ31 Β· ⭐ 7.5K Β· πŸ’€) - Automated Machine Learning with scikit-learn. BSD-3 - Hyperas (πŸ₯ˆ27 Β· ⭐ 2.2K Β· πŸ’€) - Keras + Hyperopt: A very simple wrapper for convenient.. MIT -- lightwood (πŸ₯ˆ26 Β· ⭐ 430) - Lightwood is Legos for Machine Learning. ❗️GPL-3.0 -- SMAC3 (πŸ₯ˆ25 Β· ⭐ 1K) - SMAC3: A Versatile Bayesian Optimization Package for.. ❗️BSD-1-Clause -- GPyOpt (πŸ₯ˆ25 Β· ⭐ 920 Β· πŸ’€) - Gaussian Process Optimization using GPy. BSD-3 -- AdaNet (πŸ₯‰23 Β· ⭐ 3.5K Β· πŸ’€) - Fast and flexible AutoML with learning guarantees. Apache-2 +- GPyOpt (πŸ₯ˆ26 Β· ⭐ 930 Β· πŸ’€) - Gaussian Process Optimization using GPy. BSD-3 +- SMAC3 (πŸ₯ˆ25 Β· ⭐ 1.1K) - SMAC3: A Versatile Bayesian Optimization Package for.. ❗️BSD-1-Clause +- AdaNet (πŸ₯‰24 Β· ⭐ 3.5K Β· πŸ’€) - Fast and flexible AutoML with learning guarantees. Apache-2 +- lightwood (πŸ₯‰23 Β· ⭐ 440) - Lightwood is Legos for Machine Learning. ❗️GPL-3.0 - auto_ml (πŸ₯‰22 Β· ⭐ 1.6K Β· πŸ’€) - [UNMAINTAINED] Automated machine learning for analytics & production. MIT -- Test Tube (πŸ₯‰22 Β· ⭐ 740 Β· πŸ’€) - Python library to easily log experiments and parallelize.. MIT - HpBandSter (πŸ₯‰22 Β· ⭐ 610 Β· πŸ’€) - a distributed Hyperband implementation on Steroids. BSD-3 - Orion (πŸ₯‰22 Β· ⭐ 280 Β· πŸ’€) - Asynchronous Distributed Hyperparameter Optimization. BSD-3 - MLBox (πŸ₯‰21 Β· ⭐ 1.5K Β· πŸ’€) - MLBox is a powerful Automated Machine Learning python library. ❗️BSD-1-Clause +- Test Tube (πŸ₯‰21 Β· ⭐ 740 Β· πŸ’€) - Python library to easily log experiments and parallelize.. MIT - Neuraxle (πŸ₯‰21 Β· ⭐ 600 Β· πŸ’€) - The worlds cleanest AutoML library - Do hyperparameter tuning.. Apache-2 - optunity (πŸ₯‰21 Β· ⭐ 410 Β· πŸ’€) - optimization routines for hyperparameter tuning. BSD-3 -- sklearn-deap (πŸ₯‰20 Β· ⭐ 760 Β· πŸ’€) - Use evolutionary algorithms instead of gridsearch in.. MIT -- igel (πŸ₯‰19 Β· ⭐ 3.1K Β· πŸ’€) - a delightful machine learning tool that allows you to train, test, and.. MIT -- Dragonfly (πŸ₯‰19 Β· ⭐ 840 Β· πŸ’€) - An open source python library for scalable Bayesian optimisation. MIT +- igel (πŸ₯‰20 Β· ⭐ 3.1K Β· πŸ’€) - a delightful machine learning tool that allows you to train, test, and.. MIT +- sklearn-deap (πŸ₯‰20 Β· ⭐ 770 Β· πŸ’€) - Use evolutionary algorithms instead of gridsearch in.. MIT +- Dragonfly (πŸ₯‰19 Β· ⭐ 850 Β· πŸ’€) - An open source python library for scalable Bayesian optimisation. MIT +- Xcessiv (πŸ₯‰18 Β· ⭐ 1.3K Β· πŸ’€) - A web-based application for quick, scalable, and automated.. Apache-2 - Auto Tune Models (πŸ₯‰18 Β· ⭐ 520 Β· πŸ’€) - Auto Tune Models - A multi-tenant, multi-data system for.. MIT - Sherpa (πŸ₯‰18 Β· ⭐ 330 Β· πŸ’€) - Hyperparameter optimization that enables researchers to.. ❗️GPL-3.0 - Advisor (πŸ₯‰17 Β· ⭐ 1.5K Β· πŸ’€) - Open-source implementation of Google Vizier for hyper parameters.. Apache-2 -- Xcessiv (πŸ₯‰17 Β· ⭐ 1.3K Β· πŸ’€) - A web-based application for quick, scalable, and automated.. Apache-2 -- HyperparameterHunter (πŸ₯‰16 Β· ⭐ 700 Β· πŸ’€) - Easy hyperparameter optimization and automatic result.. MIT -- Parfit (πŸ₯‰16 Β· ⭐ 200 Β· πŸ’€) - A package for parallelizing the fit and flexibly scoring of.. MIT -- automl-gs (πŸ₯‰15 Β· ⭐ 1.8K Β· πŸ’€) - Provide an input CSV and a target field to predict, generate a.. MIT +- HyperparameterHunter (πŸ₯‰17 Β· ⭐ 700 Β· πŸ’€) - Easy hyperparameter optimization and automatic result.. MIT +- automl-gs (πŸ₯‰16 Β· ⭐ 1.8K Β· πŸ’€) - Provide an input CSV and a target field to predict, generate a.. MIT +- Parfit (πŸ₯‰15 Β· ⭐ 200 Β· πŸ’€) - A package for parallelizing the fit and flexibly scoring of.. MIT - ENAS (πŸ₯‰13 Β· ⭐ 2.7K Β· πŸ’€) - PyTorch implementation of Efficient Neural Architecture Search via.. Apache-2 +- model_search (πŸ₯‰12 Β· ⭐ 3.3K Β· πŸ’€) - AutoML algorithms for model architecture search at scale. Apache-2 - Auptimizer (πŸ₯‰12 Β· ⭐ 200 Β· πŸ’€) - An automatic ML model optimization tool. ❗️GPL-3.0 -- model_search (πŸ₯‰11 Β· ⭐ 3.3K Β· πŸ’€) - AutoML algorithms for model architecture search at scale. Apache-2 +- Hypermax (πŸ₯‰12 Β· ⭐ 110 Β· πŸ’€) - Better, faster hyper-parameter optimization. BSD-3 - Devol (πŸ₯‰11 Β· ⭐ 950 Β· πŸ’€) - Genetic neural architecture search with Keras. MIT -- Hypermax (πŸ₯‰11 Β· ⭐ 110) - Better, faster hyper-parameter optimization. BSD-3 -- Hypertunity (πŸ₯‰9 Β· ⭐ 140 Β· πŸ’€) - A toolset for black-box hyperparameter optimisation. Apache-2 +- Hypertunity (πŸ₯‰10 Β· ⭐ 140 Β· πŸ’€) - A toolset for black-box hyperparameter optimisation. Apache-2

@@ -5077,133 +5027,133 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc _Libraries for building and evaluating reinforcement learning & agent-based systems._ -
FinRL (πŸ₯‡29 Β· ⭐ 9.3K) - FinRL: Financial Reinforcement Learning. MIT +
FinRL (πŸ₯‡30 Β· ⭐ 9.6K) - FinRL: Financial Reinforcement Learning. MIT -- [GitHub](https://github.com/AI4Finance-Foundation/FinRL) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 2.2K Β· πŸ“¦ 40 Β· πŸ“‹ 700 - 31% open Β· ⏱️ 04.06.2024): +- [GitHub](https://github.com/AI4Finance-Foundation/FinRL) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 2.3K Β· πŸ“¦ 45 Β· πŸ“‹ 720 - 33% open Β· ⏱️ 04.09.2024): ``` git clone https://github.com/AI4Finance-Foundation/FinRL ``` -- [PyPi](https://pypi.org/project/finrl) (πŸ“₯ 940 / month Β· ⏱️ 08.01.2022): +- [PyPi](https://pypi.org/project/finrl) (πŸ“₯ 930 / month Β· ⏱️ 08.01.2022): ``` pip install finrl ```
-
Dopamine (πŸ₯ˆ28 Β· ⭐ 10K) - Dopamine is a research framework for fast prototyping of.. Apache-2 +
ViZDoom (πŸ₯‡30 Β· ⭐ 1.7K) - Reinforcement Learning environments based on the 1993 game Doom. MIT -- [GitHub](https://github.com/google/dopamine) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 1.4K Β· πŸ“¦ 21 Β· πŸ“‹ 190 - 53% open Β· ⏱️ 06.05.2024): +- [GitHub](https://github.com/Farama-Foundation/ViZDoom) (πŸ‘¨β€πŸ’» 54 Β· πŸ”€ 380 Β· πŸ“₯ 12K Β· πŸ“¦ 260 Β· πŸ“‹ 460 - 8% open Β· ⏱️ 20.08.2024): ``` - git clone https://github.com/google/dopamine + git clone https://github.com/mwydmuch/ViZDoom ``` -- [PyPi](https://pypi.org/project/dopamine-rl) (πŸ“₯ 32K / month Β· πŸ“¦ 10 Β· ⏱️ 06.05.2024): +- [PyPi](https://pypi.org/project/vizdoom) (πŸ“₯ 2.1K / month Β· πŸ“¦ 15 Β· ⏱️ 20.08.2024): ``` - pip install dopamine-rl + pip install vizdoom ```
-
Acme (πŸ₯ˆ28 Β· ⭐ 3.4K) - A library of reinforcement learning components and agents. Apache-2 +
TF-Agents (πŸ₯ˆ29 Β· ⭐ 2.8K) - TF-Agents: A reliable, scalable and easy to use TensorFlow.. Apache-2 -- [GitHub](https://github.com/google-deepmind/acme) (πŸ‘¨β€πŸ’» 85 Β· πŸ”€ 410 Β· πŸ“¦ 200 Β· πŸ“‹ 260 - 23% open Β· ⏱️ 20.05.2024): +- [GitHub](https://github.com/tensorflow/agents) (πŸ‘¨β€πŸ’» 150 Β· πŸ”€ 710 Β· πŸ“‹ 670 - 29% open Β· ⏱️ 22.08.2024): ``` - git clone https://github.com/deepmind/acme - ``` -- [PyPi](https://pypi.org/project/dm-acme) (πŸ“₯ 1.5K / month Β· πŸ“¦ 3 Β· ⏱️ 10.02.2022): - ``` - pip install dm-acme + git clone https://github.com/tensorflow/agents ``` -- [Conda](https://anaconda.org/conda-forge/dm-acme) (πŸ“₯ 8.7K Β· ⏱️ 16.06.2023): +- [PyPi](https://pypi.org/project/tf-agents) (πŸ“₯ 70K / month Β· πŸ“¦ 14 Β· ⏱️ 14.12.2023): ``` - conda install -c conda-forge dm-acme + pip install tf-agents ```
-
ViZDoom (πŸ₯ˆ27 Β· ⭐ 1.7K) - Reinforcement Learning environments based on the 1993 game Doom. MIT +
Acme (πŸ₯ˆ28 Β· ⭐ 3.5K) - A library of reinforcement learning components and agents. Apache-2 -- [GitHub](https://github.com/Farama-Foundation/ViZDoom) (πŸ‘¨β€πŸ’» 54 Β· πŸ”€ 380 Β· πŸ“₯ 12K Β· πŸ“¦ 240 Β· πŸ“‹ 460 - 8% open Β· ⏱️ 13.02.2024): +- [GitHub](https://github.com/google-deepmind/acme) (πŸ‘¨β€πŸ’» 86 Β· πŸ”€ 420 Β· πŸ“¦ 220 Β· πŸ“‹ 260 - 23% open Β· ⏱️ 26.08.2024): ``` - git clone https://github.com/mwydmuch/ViZDoom + git clone https://github.com/deepmind/acme ``` -- [PyPi](https://pypi.org/project/vizdoom) (πŸ“₯ 2.3K / month Β· πŸ“¦ 13 Β· ⏱️ 16.12.2023): +- [PyPi](https://pypi.org/project/dm-acme) (πŸ“₯ 1.5K / month Β· πŸ“¦ 3 Β· ⏱️ 10.02.2022): ``` - pip install vizdoom + pip install dm-acme + ``` +- [Conda](https://anaconda.org/conda-forge/dm-acme) (πŸ“₯ 9.6K Β· ⏱️ 16.06.2023): + ``` + conda install -c conda-forge dm-acme ```
-
TF-Agents (πŸ₯ˆ26 Β· ⭐ 2.7K Β· πŸ“‰) - TF-Agents: A reliable, scalable and easy to use.. Apache-2 +
Dopamine (πŸ₯ˆ27 Β· ⭐ 10K) - Dopamine is a research framework for fast prototyping of.. Apache-2 -- [GitHub](https://github.com/tensorflow/agents) (πŸ‘¨β€πŸ’» 150 Β· πŸ”€ 720 Β· πŸ“‹ 660 - 29% open Β· ⏱️ 20.03.2024): +- [GitHub](https://github.com/google/dopamine) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 1.4K Β· πŸ“¦ 21 Β· πŸ“‹ 190 - 53% open Β· ⏱️ 06.05.2024): ``` - git clone https://github.com/tensorflow/agents + git clone https://github.com/google/dopamine ``` -- [PyPi](https://pypi.org/project/tf-agents) (πŸ“₯ 40K / month Β· πŸ“¦ 12 Β· ⏱️ 14.12.2023): +- [PyPi](https://pypi.org/project/dopamine-rl) (πŸ“₯ 32K / month Β· πŸ“¦ 10 Β· ⏱️ 06.05.2024): ``` - pip install tf-agents + pip install dopamine-rl ```
-
RLax (πŸ₯ˆ26 Β· ⭐ 1.2K) - A library of reinforcement learning building blocks in JAX. Apache-2 +
TensorForce (πŸ₯‰26 Β· ⭐ 3.3K) - Tensorforce: a TensorFlow library for applied.. Apache-2 -- [GitHub](https://github.com/google-deepmind/rlax) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 83 Β· πŸ“¦ 230 Β· πŸ“‹ 25 - 28% open Β· ⏱️ 24.05.2024): +- [GitHub](https://github.com/tensorforce/tensorforce) (πŸ‘¨β€πŸ’» 85 Β· πŸ”€ 530 Β· πŸ“¦ 450 Β· πŸ“‹ 680 - 6% open Β· ⏱️ 31.07.2024): ``` - git clone https://github.com/deepmind/rlax + git clone https://github.com/tensorforce/tensorforce ``` -- [PyPi](https://pypi.org/project/rlax) (πŸ“₯ 1.9M / month Β· πŸ“¦ 11 Β· ⏱️ 09.01.2023): +- [PyPi](https://pypi.org/project/tensorforce) (πŸ“₯ 660 / month Β· πŸ“¦ 4 Β· ⏱️ 30.08.2021): ``` - pip install rlax + pip install tensorforce ```
-
PARL (πŸ₯‰25 Β· ⭐ 3.2K) - A high-performance distributed training framework for Reinforcement.. Apache-2 +
PARL (πŸ₯‰24 Β· ⭐ 3.2K) - A high-performance distributed training framework for Reinforcement.. Apache-2 -- [GitHub](https://github.com/PaddlePaddle/PARL) (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 810 Β· πŸ“¦ 130 Β· πŸ“‹ 530 - 25% open Β· ⏱️ 23.05.2024): +- [GitHub](https://github.com/PaddlePaddle/PARL) (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 810 Β· πŸ“¦ 130 Β· πŸ“‹ 540 - 24% open Β· ⏱️ 09.07.2024): ``` git clone https://github.com/PaddlePaddle/PARL ``` -- [PyPi](https://pypi.org/project/parl) (πŸ“₯ 910 / month Β· πŸ“¦ 1 Β· ⏱️ 13.05.2022): +- [PyPi](https://pypi.org/project/parl) (πŸ“₯ 750 / month Β· πŸ“¦ 1 Β· ⏱️ 13.05.2022): ``` pip install parl ```
-
TensorForce (πŸ₯‰24 Β· ⭐ 3.3K Β· πŸ“‰) - Tensorforce: a TensorFlow library for applied.. Apache-2 +
RLax (πŸ₯‰24 Β· ⭐ 1.2K) - A library of reinforcement learning building blocks in JAX. Apache-2 -- [GitHub](https://github.com/tensorforce/tensorforce) (πŸ‘¨β€πŸ’» 85 Β· πŸ”€ 540 Β· πŸ“‹ 670 - 5% open Β· ⏱️ 09.04.2024): +- [GitHub](https://github.com/google-deepmind/rlax) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 85 Β· πŸ“¦ 260 Β· πŸ“‹ 26 - 30% open Β· ⏱️ 24.05.2024): ``` - git clone https://github.com/tensorforce/tensorforce + git clone https://github.com/deepmind/rlax ``` -- [PyPi](https://pypi.org/project/tensorforce) (πŸ“₯ 700 / month Β· πŸ“¦ 4 Β· ⏱️ 30.08.2021): +- [PyPi](https://pypi.org/project/rlax) (πŸ“₯ 20K / month Β· πŸ“¦ 11 Β· ⏱️ 09.01.2023): ``` - pip install tensorforce + pip install rlax ```
-
ReAgent (πŸ₯‰23 Β· ⭐ 3.5K) - A platform for Reasoning systems (Reinforcement Learning,.. BSD-3 +
PFRL (πŸ₯‰23 Β· ⭐ 1.2K) - PFRL: a PyTorch-based deep reinforcement learning library. MIT -- [GitHub](https://github.com/facebookresearch/ReAgent) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 510 Β· πŸ“‹ 160 - 53% open Β· ⏱️ 15.05.2024): +- [GitHub](https://github.com/pfnet/pfrl) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 150 Β· πŸ“¦ 110 Β· πŸ“‹ 79 - 41% open Β· ⏱️ 04.08.2024): ``` - git clone https://github.com/facebookresearch/ReAgent + git clone https://github.com/pfnet/pfrl ``` -- [PyPi](https://pypi.org/project/reagent) (πŸ“₯ 23 / month Β· ⏱️ 27.05.2020): +- [PyPi](https://pypi.org/project/pfrl) (πŸ“₯ 250 / month Β· πŸ“¦ 1 Β· ⏱️ 16.07.2023): ``` - pip install reagent + pip install pfrl ```
-
PFRL (πŸ₯‰23 Β· ⭐ 1.2K) - PFRL: a PyTorch-based deep reinforcement learning library. MIT +
ReAgent (πŸ₯‰22 Β· ⭐ 3.6K) - A platform for Reasoning systems (Reinforcement Learning,.. BSD-3 -- [GitHub](https://github.com/pfnet/pfrl) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 150 Β· πŸ“¦ 110 Β· πŸ“‹ 79 - 41% open Β· ⏱️ 29.04.2024): +- [GitHub](https://github.com/facebookresearch/ReAgent) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 510 Β· πŸ“‹ 160 - 53% open Β· ⏱️ 12.08.2024): ``` - git clone https://github.com/pfnet/pfrl + git clone https://github.com/facebookresearch/ReAgent ``` -- [PyPi](https://pypi.org/project/pfrl) (πŸ“₯ 380 / month Β· πŸ“¦ 1 Β· ⏱️ 16.07.2023): +- [PyPi](https://pypi.org/project/reagent) (πŸ“₯ 41 / month Β· ⏱️ 27.05.2020): ``` - pip install pfrl + pip install reagent ```
-
rliable (πŸ₯‰13 Β· ⭐ 710) - [NeurIPS21 Outstanding Paper] Library for reliable evaluation on RL.. Apache-2 +
rliable (πŸ₯‰14 Β· ⭐ 740) - [NeurIPS21 Outstanding Paper] Library for reliable evaluation on RL.. Apache-2 -- [GitHub](https://github.com/google-research/rliable) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 43 Β· πŸ“¦ 140 Β· πŸ“‹ 17 - 23% open Β· ⏱️ 28.05.2024): +- [GitHub](https://github.com/google-research/rliable) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 45 Β· πŸ“¦ 140 Β· πŸ“‹ 16 - 6% open Β· ⏱️ 12.08.2024): ``` git clone https://github.com/google-research/rliable @@ -5215,18 +5165,18 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst
Show 12 hidden projects... -- OpenAI Gym (πŸ₯‡40 Β· ⭐ 34K Β· πŸ’€) - A toolkit for developing and comparing reinforcement learning.. MIT -- baselines (πŸ₯‡29 Β· ⭐ 15K Β· πŸ’€) - OpenAI Baselines: high-quality implementations of reinforcement.. MIT -- keras-rl (πŸ₯ˆ28 Β· ⭐ 5.5K Β· πŸ’€) - Deep Reinforcement Learning for Keras. MIT +- OpenAI Gym (πŸ₯‡39 Β· ⭐ 34K Β· πŸ’€) - A toolkit for developing and comparing reinforcement learning.. MIT +- baselines (πŸ₯ˆ29 Β· ⭐ 16K Β· πŸ’€) - OpenAI Baselines: high-quality implementations of reinforcement.. MIT - TensorLayer (πŸ₯ˆ27 Β· ⭐ 7.3K Β· πŸ’€) - Deep Learning and Reinforcement Learning Library for.. Apache-2 -- garage (πŸ₯‰25 Β· ⭐ 1.8K Β· πŸ’€) - A toolkit for reproducible reinforcement learning research. MIT +- keras-rl (πŸ₯ˆ27 Β· ⭐ 5.5K Β· πŸ’€) - Deep Reinforcement Learning for Keras. MIT +- garage (πŸ₯‰25 Β· ⭐ 1.9K Β· πŸ’€) - A toolkit for reproducible reinforcement learning research. MIT - Stable Baselines (πŸ₯‰24 Β· ⭐ 4.1K Β· πŸ’€) - A fork of OpenAI Baselines, implementations of.. MIT - ChainerRL (πŸ₯‰24 Β· ⭐ 1.2K Β· πŸ’€) - ChainerRL is a deep reinforcement learning library built on top of.. MIT - TRFL (πŸ₯‰22 Β· ⭐ 3.1K Β· πŸ’€) - TensorFlow Reinforcement Learning. Apache-2 - Coach (πŸ₯‰20 Β· ⭐ 2.3K Β· πŸ’€) - Reinforcement Learning Coach by Intel AI Lab enables easy.. Apache-2 - SerpentAI (πŸ₯‰18 Β· ⭐ 6.7K Β· πŸ’€) - Game Agent Framework. Helping you create AIs / Bots that learn to.. MIT -- DeepMind Lab (πŸ₯‰17 Β· ⭐ 7K Β· πŸ’€) - A customisable 3D platform for agent-based AI research. ❗Unlicensed -- Maze (πŸ₯‰12 Β· ⭐ 260 Β· πŸ’€) - Maze Applied Reinforcement Learning Framework. ❗️Custom +- DeepMind Lab (πŸ₯‰17 Β· ⭐ 7.1K Β· πŸ’€) - A customisable 3D platform for agent-based AI research. ❗Unlicensed +- Maze (πŸ₯‰13 Β· ⭐ 260 Β· πŸ’€) - Maze Applied Reinforcement Learning Framework. ❗️Custom

@@ -5236,140 +5186,140 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst _Libraries for building and evaluating recommendation systems._ -
Recommenders (πŸ₯‡35 Β· ⭐ 18K) - Best Practices on Recommendation Systems. MIT +
Recommenders (πŸ₯‡35 Β· ⭐ 19K) - Best Practices on Recommendation Systems. MIT -- [GitHub](https://github.com/recommenders-team/recommenders) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 3K Β· πŸ“₯ 500 Β· πŸ“¦ 120 Β· πŸ“‹ 840 - 18% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/recommenders-team/recommenders) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 3K Β· πŸ“₯ 550 Β· πŸ“¦ 120 Β· πŸ“‹ 860 - 18% open Β· ⏱️ 27.08.2024): ``` git clone https://github.com/microsoft/recommenders ``` -- [PyPi](https://pypi.org/project/recommenders) (πŸ“₯ 29K / month Β· πŸ“¦ 4 Β· ⏱️ 01.05.2024): +- [PyPi](https://pypi.org/project/recommenders) (πŸ“₯ 31K / month Β· πŸ“¦ 4 Β· ⏱️ 01.05.2024): ``` pip install recommenders ```
-
torchrec (πŸ₯‡31 Β· ⭐ 1.8K) - Pytorch domain library for recommendation systems. BSD-3 - -- [GitHub](https://github.com/pytorch/torchrec) (πŸ‘¨β€πŸ’» 240 Β· πŸ”€ 360 Β· πŸ“¦ 120 Β· πŸ“‹ 360 - 70% open Β· ⏱️ 06.06.2024): - - ``` - git clone https://github.com/pytorch/torchrec - ``` -- [PyPi](https://pypi.org/project/torchrec-nightly-cpu) (πŸ“₯ 1.1K / month Β· ⏱️ 12.05.2022): - ``` - pip install torchrec-nightly-cpu - ``` -
-
implicit (πŸ₯ˆ30 Β· ⭐ 3.4K Β· πŸ’€) - Fast Python Collaborative Filtering for Implicit Feedback Datasets. MIT +
implicit (πŸ₯‡30 Β· ⭐ 3.5K Β· πŸ’€) - Fast Python Collaborative Filtering for Implicit Feedback Datasets. MIT -- [GitHub](https://github.com/benfred/implicit) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 600 Β· πŸ“₯ 790 Β· πŸ“¦ 1.3K Β· πŸ“‹ 490 - 17% open Β· ⏱️ 21.11.2023): +- [GitHub](https://github.com/benfred/implicit) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 600 Β· πŸ“₯ 1.2K Β· πŸ“¦ 1.4K Β· πŸ“‹ 500 - 17% open Β· ⏱️ 21.11.2023): ``` git clone https://github.com/benfred/implicit ``` -- [PyPi](https://pypi.org/project/implicit) (πŸ“₯ 220K / month Β· πŸ“¦ 28 Β· ⏱️ 29.09.2023): +- [PyPi](https://pypi.org/project/implicit) (πŸ“₯ 210K / month Β· πŸ“¦ 29 Β· ⏱️ 29.09.2023): ``` pip install implicit ``` -- [Conda](https://anaconda.org/conda-forge/implicit) (πŸ“₯ 650K Β· ⏱️ 21.11.2023): +- [Conda](https://anaconda.org/conda-forge/implicit) (πŸ“₯ 820K Β· ⏱️ 23.08.2024): ``` conda install -c conda-forge implicit ```
-
TF Recommenders (πŸ₯ˆ30 Β· ⭐ 1.8K) - TensorFlow Recommenders is a library for building.. Apache-2 +
torchrec (πŸ₯‡30 Β· ⭐ 1.9K) - Pytorch domain library for recommendation systems. BSD-3 -- [GitHub](https://github.com/tensorflow/recommenders) (πŸ‘¨β€πŸ’» 43 Β· πŸ”€ 260 Β· πŸ“¦ 330 Β· πŸ“‹ 430 - 57% open Β· ⏱️ 16.02.2024): +- [GitHub](https://github.com/pytorch/torchrec) (πŸ‘¨β€πŸ’» 260 Β· πŸ”€ 390 Β· πŸ“¦ 130 Β· πŸ“‹ 410 - 72% open Β· ⏱️ 05.09.2024): ``` - git clone https://github.com/tensorflow/recommenders + git clone https://github.com/pytorch/torchrec ``` -- [PyPi](https://pypi.org/project/tensorflow-recommenders) (πŸ“₯ 470K / month Β· πŸ“¦ 1 Β· ⏱️ 03.02.2023): +- [PyPi](https://pypi.org/project/torchrec-nightly-cpu) (πŸ“₯ 720 / month Β· ⏱️ 12.05.2022): ``` - pip install tensorflow-recommenders + pip install torchrec-nightly-cpu ```
-
scikit-surprise (πŸ₯ˆ29 Β· ⭐ 6.2K) - A Python scikit for building and analyzing recommender.. BSD-3 +
Cornac (πŸ₯ˆ28 Β· ⭐ 860) - A Comparative Framework for Multimodal Recommender Systems. Apache-2 -- [GitHub](https://github.com/NicolasHug/Surprise) (πŸ‘¨β€πŸ’» 46 Β· πŸ”€ 1K Β· πŸ“¦ 21 Β· πŸ“‹ 400 - 22% open Β· ⏱️ 19.05.2024): +- [GitHub](https://github.com/PreferredAI/cornac) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 140 Β· πŸ“¦ 230 Β· πŸ“‹ 160 - 10% open Β· ⏱️ 04.09.2024): ``` - git clone https://github.com/NicolasHug/Surprise + git clone https://github.com/PreferredAI/cornac ``` -- [PyPi](https://pypi.org/project/scikit-surprise) (πŸ“₯ 100K / month Β· πŸ“¦ 36 Β· ⏱️ 19.05.2024): +- [PyPi](https://pypi.org/project/cornac) (πŸ“₯ 42K / month Β· πŸ“¦ 18 Β· ⏱️ 15.08.2024): ``` - pip install scikit-surprise + pip install cornac ``` -- [Conda](https://anaconda.org/conda-forge/scikit-surprise) (πŸ“₯ 370K Β· ⏱️ 20.05.2024): +- [Conda](https://anaconda.org/conda-forge/cornac) (πŸ“₯ 540K Β· ⏱️ 15.08.2024): ``` - conda install -c conda-forge scikit-surprise + conda install -c conda-forge cornac ```
-
Cornac (πŸ₯ˆ28 Β· ⭐ 840) - A Comparative Framework for Multimodal Recommender Systems. Apache-2 +
scikit-surprise (πŸ₯ˆ27 Β· ⭐ 6.3K) - A Python scikit for building and analyzing recommender.. BSD-3 -- [GitHub](https://github.com/PreferredAI/cornac) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 130 Β· πŸ“¦ 220 Β· πŸ“‹ 150 - 9% open Β· ⏱️ 24.05.2024): +- [GitHub](https://github.com/NicolasHug/Surprise) (πŸ‘¨β€πŸ’» 46 Β· πŸ”€ 1K Β· πŸ“¦ 21 Β· πŸ“‹ 400 - 21% open Β· ⏱️ 14.06.2024): ``` - git clone https://github.com/PreferredAI/cornac + git clone https://github.com/NicolasHug/Surprise ``` -- [PyPi](https://pypi.org/project/cornac) (πŸ“₯ 38K / month Β· πŸ“¦ 18 Β· ⏱️ 24.05.2024): +- [PyPi](https://pypi.org/project/scikit-surprise) (πŸ“₯ 80K / month Β· πŸ“¦ 37 Β· ⏱️ 19.05.2024): ``` - pip install cornac + pip install scikit-surprise ``` -- [Conda](https://anaconda.org/conda-forge/cornac) (πŸ“₯ 390K Β· ⏱️ 24.05.2024): +- [Conda](https://anaconda.org/conda-forge/scikit-surprise) (πŸ“₯ 400K Β· ⏱️ 20.05.2024): ``` - conda install -c conda-forge cornac + conda install -c conda-forge scikit-surprise ```
-
TF Ranking (πŸ₯‰27 Β· ⭐ 2.7K) - Learning to Rank in TensorFlow. Apache-2 +
TF Ranking (πŸ₯ˆ26 Β· ⭐ 2.7K) - Learning to Rank in TensorFlow. Apache-2 - [GitHub](https://github.com/tensorflow/ranking) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 470 Β· πŸ“‹ 330 - 27% open Β· ⏱️ 18.03.2024): ``` git clone https://github.com/tensorflow/ranking ``` -- [PyPi](https://pypi.org/project/tensorflow_ranking) (πŸ“₯ 120K / month Β· πŸ“¦ 15 Β· ⏱️ 18.03.2024): +- [PyPi](https://pypi.org/project/tensorflow_ranking) (πŸ“₯ 99K / month Β· πŸ“¦ 15 Β· ⏱️ 18.03.2024): ``` pip install tensorflow_ranking ```
-
RecBole (πŸ₯‰25 Β· ⭐ 3.2K) - A unified, comprehensive and efficient recommendation library. MIT +
RecBole (πŸ₯‰25 Β· ⭐ 3.3K) - A unified, comprehensive and efficient recommendation library. MIT -- [GitHub](https://github.com/RUCAIBox/RecBole) (πŸ‘¨β€πŸ’» 71 Β· πŸ”€ 590 Β· πŸ“‹ 940 - 26% open Β· ⏱️ 30.03.2024): +- [GitHub](https://github.com/RUCAIBox/RecBole) (πŸ‘¨β€πŸ’» 74 Β· πŸ”€ 600 Β· πŸ“‹ 990 - 28% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/RUCAIBox/RecBole ``` -- [PyPi](https://pypi.org/project/recbole) (πŸ“₯ 3.3K / month Β· πŸ“¦ 2 Β· ⏱️ 31.10.2023): +- [PyPi](https://pypi.org/project/recbole) (πŸ“₯ 54K / month Β· πŸ“¦ 2 Β· ⏱️ 31.10.2023): ``` pip install recbole ``` -- [Conda](https://anaconda.org/aibox/recbole) (πŸ“₯ 4.9K Β· ⏱️ 01.11.2023): +- [Conda](https://anaconda.org/aibox/recbole) (πŸ“₯ 5.7K Β· ⏱️ 01.11.2023): ``` conda install -c aibox recbole ```
-
recmetrics (πŸ₯‰20 Β· ⭐ 560 Β· πŸ’€) - A library of metrics for evaluating recommender systems. MIT +
TF Recommenders (πŸ₯‰24 Β· ⭐ 1.8K Β· πŸ“‰) - TensorFlow Recommenders is a library for building.. Apache-2 -- [GitHub](https://github.com/statisticianinstilettos/recmetrics) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 98 Β· πŸ“₯ 6 Β· πŸ“¦ 52 Β· πŸ“‹ 28 - 46% open Β· ⏱️ 04.10.2023): +- [GitHub](https://github.com/tensorflow/recommenders) (πŸ‘¨β€πŸ’» 43 Β· πŸ”€ 270 Β· πŸ“‹ 450 - 58% open Β· ⏱️ 16.08.2024): + + ``` + git clone https://github.com/tensorflow/recommenders + ``` +- [PyPi](https://pypi.org/project/tensorflow-recommenders) (πŸ“₯ 380K / month Β· πŸ“¦ 2 Β· ⏱️ 03.02.2023): + ``` + pip install tensorflow-recommenders + ``` +
+
recmetrics (πŸ₯‰19 Β· ⭐ 560 Β· πŸ’€) - A library of metrics for evaluating recommender systems. MIT + +- [GitHub](https://github.com/statisticianinstilettos/recmetrics) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 97 Β· πŸ“₯ 7 Β· πŸ“¦ 56 Β· πŸ“‹ 29 - 44% open Β· ⏱️ 04.10.2023): ``` git clone https://github.com/statisticianinstilettos/recmetrics ``` -- [PyPi](https://pypi.org/project/recmetrics) (πŸ“₯ 19K / month Β· ⏱️ 26.04.2022): +- [PyPi](https://pypi.org/project/recmetrics) (πŸ“₯ 4.1K / month Β· ⏱️ 26.04.2022): ``` pip install recmetrics ```
Show 8 hidden projects... -- lightfm (πŸ₯ˆ29 Β· ⭐ 4.6K Β· πŸ’€) - A Python implementation of LightFM, a hybrid recommendation.. Apache-2 -- lkpy (πŸ₯‰26 Β· ⭐ 260) - Python recommendation toolkit. MIT +- lightfm (πŸ₯ˆ29 Β· ⭐ 4.7K Β· πŸ’€) - A Python implementation of LightFM, a hybrid recommendation.. Apache-2 +- lkpy (πŸ₯‰25 Β· ⭐ 260) - Python recommendation toolkit. MIT - tensorrec (πŸ₯‰21 Β· ⭐ 1.3K Β· πŸ’€) - A TensorFlow recommendation algorithm and framework in.. Apache-2 - fastFM (πŸ₯‰21 Β· ⭐ 1.1K Β· πŸ’€) - fastFM: A Library for Factorization Machines. BSD-3 -- Spotlight (πŸ₯‰18 Β· ⭐ 2.9K Β· πŸ’€) - Deep recommender models using PyTorch. MIT -- Case Recommender (πŸ₯‰18 Β· ⭐ 460 Β· πŸ’€) - Case Recommender: A Flexible and Extensible Python.. MIT +- Spotlight (πŸ₯‰18 Β· ⭐ 3K Β· πŸ’€) - Deep recommender models using PyTorch. MIT +- Case Recommender (πŸ₯‰18 Β· ⭐ 480 Β· πŸ’€) - Case Recommender: A Flexible and Extensible Python.. MIT - OpenRec (πŸ₯‰16 Β· ⭐ 410 Β· πŸ’€) - OpenRec is an open-source and modular library for neural network-.. Apache-2 -- Collie (πŸ₯‰15 Β· ⭐ 100 Β· πŸ’€) - A library for preparing, training, and evaluating scalable deep.. BSD-3 +- Collie (πŸ₯‰16 Β· ⭐ 110 Β· πŸ’€) - A library for preparing, training, and evaluating scalable deep.. BSD-3

@@ -5379,66 +5329,66 @@ _Libraries for building and evaluating recommendation systems._ _Libraries for encrypted and privacy-preserving machine learning using methods like federated learning & differential privacy._ -
PySyft (πŸ₯‡37 Β· ⭐ 9.3K) - Perform data science on data that remains in someone elses server. Apache-2 +
PySyft (πŸ₯‡37 Β· ⭐ 9.4K) - Perform data science on data that remains in someone elses server. Apache-2 -- [GitHub](https://github.com/OpenMined/PySyft) (πŸ‘¨β€πŸ’» 510 Β· πŸ”€ 2K Β· πŸ“₯ 2.5K Β· πŸ“¦ 1 Β· πŸ“‹ 3.4K - 0% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/OpenMined/PySyft) (πŸ‘¨β€πŸ’» 520 Β· πŸ”€ 2K Β· πŸ“₯ 2.2K Β· πŸ“¦ 1 Β· πŸ“‹ 3.4K - 1% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/OpenMined/PySyft ``` -- [PyPi](https://pypi.org/project/syft) (πŸ“₯ 13K / month Β· πŸ“¦ 3 Β· ⏱️ 03.06.2024): +- [PyPi](https://pypi.org/project/syft) (πŸ“₯ 12K / month Β· πŸ“¦ 3 Β· ⏱️ 05.09.2024): ``` pip install syft ```
-
Opacus (πŸ₯ˆ29 Β· ⭐ 1.6K) - Training PyTorch models with differential privacy. Apache-2 +
Opacus (πŸ₯ˆ32 Β· ⭐ 1.7K) - Training PyTorch models with differential privacy. Apache-2 -- [GitHub](https://github.com/pytorch/opacus) (πŸ‘¨β€πŸ’» 79 Β· πŸ”€ 320 Β· πŸ“₯ 110 Β· πŸ“¦ 810 Β· πŸ“‹ 300 - 27% open Β· ⏱️ 31.05.2024): +- [GitHub](https://github.com/pytorch/opacus) (πŸ‘¨β€πŸ’» 81 Β· πŸ”€ 330 Β· πŸ“₯ 120 Β· πŸ“¦ 860 Β· πŸ“‹ 300 - 24% open Β· ⏱️ 29.08.2024): ``` git clone https://github.com/pytorch/opacus ``` -- [PyPi](https://pypi.org/project/opacus) (πŸ“₯ 150K / month Β· πŸ“¦ 32 Β· ⏱️ 11.02.2024): +- [PyPi](https://pypi.org/project/opacus) (πŸ“₯ 260K / month Β· πŸ“¦ 36 Β· ⏱️ 03.08.2024): ``` pip install opacus ``` -- [Conda](https://anaconda.org/conda-forge/opacus) (πŸ“₯ 14K Β· ⏱️ 11.02.2024): +- [Conda](https://anaconda.org/conda-forge/opacus) (πŸ“₯ 17K Β· ⏱️ 05.08.2024): ``` conda install -c conda-forge opacus ```
-
TensorFlow Privacy (πŸ₯ˆ26 Β· ⭐ 1.9K) - Library for training machine learning models with.. Apache-2 +
FATE (πŸ₯ˆ27 Β· ⭐ 5.6K) - An Industrial Grade Federated Learning Framework. Apache-2 -- [GitHub](https://github.com/tensorflow/privacy) (πŸ‘¨β€πŸ’» 59 Β· πŸ”€ 450 Β· πŸ“₯ 160 Β· πŸ“‹ 200 - 55% open Β· ⏱️ 13.05.2024): +- [GitHub](https://github.com/FederatedAI/FATE) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 1.5K Β· πŸ“‹ 2K - 2% open Β· ⏱️ 21.08.2024): ``` - git clone https://github.com/tensorflow/privacy + git clone https://github.com/FederatedAI/FATE ``` -- [PyPi](https://pypi.org/project/tensorflow-privacy) (πŸ“₯ 21K / month Β· πŸ“¦ 15 Β· ⏱️ 14.02.2024): +- [PyPi](https://pypi.org/project/ETAF) (⏱️ 06.05.2020): ``` - pip install tensorflow-privacy + pip install ETAF ```
-
FATE (πŸ₯‰25 Β· ⭐ 5.6K) - An Industrial Grade Federated Learning Framework. Apache-2 +
TensorFlow Privacy (πŸ₯‰26 Β· ⭐ 1.9K) - Library for training machine learning models with.. Apache-2 -- [GitHub](https://github.com/FederatedAI/FATE) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 1.5K Β· πŸ“‹ 2K - 43% open Β· ⏱️ 08.03.2024): +- [GitHub](https://github.com/tensorflow/privacy) (πŸ‘¨β€πŸ’» 59 Β· πŸ”€ 440 Β· πŸ“₯ 170 Β· πŸ“‹ 210 - 55% open Β· ⏱️ 04.09.2024): ``` - git clone https://github.com/FederatedAI/FATE + git clone https://github.com/tensorflow/privacy ``` -- [PyPi](https://pypi.org/project/ETAF) (⏱️ 06.05.2020): +- [PyPi](https://pypi.org/project/tensorflow-privacy) (πŸ“₯ 20K / month Β· πŸ“¦ 21 Β· ⏱️ 14.02.2024): ``` - pip install ETAF + pip install tensorflow-privacy ```
-
CrypTen (πŸ₯‰24 Β· ⭐ 1.5K) - A framework for Privacy Preserving Machine Learning. MIT +
CrypTen (πŸ₯‰25 Β· ⭐ 1.5K) - A framework for Privacy Preserving Machine Learning. MIT -- [GitHub](https://github.com/facebookresearch/CrypTen) (πŸ‘¨β€πŸ’» 36 Β· πŸ”€ 270 Β· πŸ“¦ 36 Β· πŸ“‹ 270 - 28% open Β· ⏱️ 23.05.2024): +- [GitHub](https://github.com/facebookresearch/CrypTen) (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 270 Β· πŸ“¦ 42 Β· πŸ“‹ 270 - 28% open Β· ⏱️ 18.07.2024): ``` git clone https://github.com/facebookresearch/CrypTen ``` -- [PyPi](https://pypi.org/project/crypten) (πŸ“₯ 290 / month Β· πŸ“¦ 1 Β· ⏱️ 08.12.2022): +- [PyPi](https://pypi.org/project/crypten) (πŸ“₯ 430 / month Β· πŸ“¦ 1 Β· ⏱️ 08.12.2022): ``` pip install crypten ``` @@ -5446,7 +5396,7 @@ _Libraries for encrypted and privacy-preserving machine learning using methods l
Show 2 hidden projects... - TFEncrypted (πŸ₯‰24 Β· ⭐ 1.2K Β· πŸ’€) - A Framework for Encrypted Machine Learning in.. Apache-2 -- PipelineDP (πŸ₯‰18 Β· ⭐ 270) - PipelineDP is a Python framework for applying differentially.. Apache-2 +- PipelineDP (πŸ₯‰19 Β· ⭐ 270) - PipelineDP is a Python framework for applying differentially.. Apache-2

@@ -5458,168 +5408,156 @@ _Libraries to organize, track, and visualize machine learning experiments._
mlflow (πŸ₯‡44 Β· ⭐ 18K) - Open source platform for the machine learning lifecycle. Apache-2 -- [GitHub](https://github.com/mlflow/mlflow) (πŸ‘¨β€πŸ’» 730 Β· πŸ”€ 4K Β· πŸ“¦ 37K Β· πŸ“‹ 3.9K - 37% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/mlflow/mlflow) (πŸ‘¨β€πŸ’» 760 Β· πŸ”€ 4.1K Β· πŸ“¦ 42K Β· πŸ“‹ 4.1K - 38% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/mlflow/mlflow ``` -- [PyPi](https://pypi.org/project/mlflow) (πŸ“₯ 14M / month Β· πŸ“¦ 780 Β· ⏱️ 06.06.2024): +- [PyPi](https://pypi.org/project/mlflow) (πŸ“₯ 15M / month Β· πŸ“¦ 860 Β· ⏱️ 30.08.2024): ``` pip install mlflow ``` -- [Conda](https://anaconda.org/conda-forge/mlflow) (πŸ“₯ 2M Β· ⏱️ 06.06.2024): +- [Conda](https://anaconda.org/conda-forge/mlflow) (πŸ“₯ 2.3M Β· ⏱️ 04.09.2024): ``` conda install -c conda-forge mlflow ```
-
Tensorboard (πŸ₯‡44 Β· ⭐ 6.6K) - TensorFlows Visualization Toolkit. Apache-2 +
DVC (πŸ₯‡42 Β· ⭐ 14K) - ML Experiments and Data Management with Git. Apache-2 -- [GitHub](https://github.com/tensorflow/tensorboard) (πŸ‘¨β€πŸ’» 320 Β· πŸ”€ 1.6K Β· πŸ“¦ 240K Β· πŸ“‹ 1.9K - 35% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/iterative/dvc) (πŸ‘¨β€πŸ’» 300 Β· πŸ”€ 1.2K Β· πŸ“¦ 17K Β· πŸ“‹ 4.7K - 4% open Β· ⏱️ 03.09.2024): ``` - git clone https://github.com/tensorflow/tensorboard + git clone https://github.com/iterative/dvc ``` -- [PyPi](https://pypi.org/project/tensorboard) (πŸ“₯ 27M / month Β· πŸ“¦ 2K Β· ⏱️ 16.02.2024): +- [PyPi](https://pypi.org/project/dvc) (πŸ“₯ 560K / month Β· πŸ“¦ 130 Β· ⏱️ 02.09.2024): ``` - pip install tensorboard + pip install dvc ``` -- [Conda](https://anaconda.org/conda-forge/tensorboard) (πŸ“₯ 4.7M Β· ⏱️ 18.02.2024): +- [Conda](https://anaconda.org/conda-forge/dvc) (πŸ“₯ 2.2M Β· ⏱️ 02.09.2024): ``` - conda install -c conda-forge tensorboard + conda install -c conda-forge dvc ```
-
wandb client (πŸ₯‡42 Β· ⭐ 8.4K) - A tool for visualizing and tracking your machine learning.. MIT +
wandb client (πŸ₯‡42 Β· ⭐ 8.9K) - The AI developer platform. Use Weights & Biases to train and fine-.. MIT -- [GitHub](https://github.com/wandb/wandb) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 610 Β· πŸ“¦ 47K Β· πŸ“‹ 3.1K - 26% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/wandb/wandb) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 650 Β· πŸ“₯ 280 Β· πŸ“¦ 53K Β· πŸ“‹ 3.3K - 25% open Β· ⏱️ 04.09.2024): ``` git clone https://github.com/wandb/client ``` -- [PyPi](https://pypi.org/project/wandb) (πŸ“₯ 14M / month Β· πŸ“¦ 1.2K Β· ⏱️ 07.05.2024): +- [PyPi](https://pypi.org/project/wandb) (πŸ“₯ 13M / month Β· πŸ“¦ 1.4K Β· ⏱️ 28.08.2024): ``` pip install wandb ``` -- [Conda](https://anaconda.org/conda-forge/wandb) (πŸ“₯ 520K Β· ⏱️ 25.03.2024): +- [Conda](https://anaconda.org/conda-forge/wandb) (πŸ“₯ 610K Β· ⏱️ 28.08.2024): ``` conda install -c conda-forge wandb ```
-
DVC (πŸ₯‡41 Β· ⭐ 13K) - ML Experiments and Data Management with Git. Apache-2 +
Tensorboard (πŸ₯‡42 Β· ⭐ 6.7K) - TensorFlows Visualization Toolkit. Apache-2 -- [GitHub](https://github.com/iterative/dvc) (πŸ‘¨β€πŸ’» 300 Β· πŸ”€ 1.2K Β· πŸ“₯ 40K Β· πŸ“¦ 16K Β· πŸ“‹ 4.6K - 4% open Β· ⏱️ 03.06.2024): +- [GitHub](https://github.com/tensorflow/tensorboard) (πŸ‘¨β€πŸ’» 320 Β· πŸ”€ 1.6K Β· πŸ“¦ 260K Β· πŸ“‹ 1.9K - 35% open Β· ⏱️ 27.08.2024): ``` - git clone https://github.com/iterative/dvc + git clone https://github.com/tensorflow/tensorboard ``` -- [PyPi](https://pypi.org/project/dvc) (πŸ“₯ 490K / month Β· πŸ“¦ 120 Β· ⏱️ 03.06.2024): +- [PyPi](https://pypi.org/project/tensorboard) (πŸ“₯ 21M / month Β· πŸ“¦ 2.2K Β· ⏱️ 14.08.2024): ``` - pip install dvc + pip install tensorboard ``` -- [Conda](https://anaconda.org/conda-forge/dvc) (πŸ“₯ 1.9M Β· ⏱️ 03.06.2024): +- [Conda](https://anaconda.org/conda-forge/tensorboard) (πŸ“₯ 5M Β· ⏱️ 15.08.2024): ``` - conda install -c conda-forge dvc + conda install -c conda-forge tensorboard ```
-
SageMaker SDK (πŸ₯‡41 Β· ⭐ 2.1K Β· πŸ“ˆ) - A library for training and deploying machine learning.. Apache-2 +
SageMaker SDK (πŸ₯ˆ41 Β· ⭐ 2.1K) - A library for training and deploying machine learning.. Apache-2 -- [GitHub](https://github.com/aws/sagemaker-python-sdk) (πŸ‘¨β€πŸ’» 440 Β· πŸ”€ 1.1K Β· πŸ“¦ 4K Β· πŸ“‹ 1.5K - 19% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/aws/sagemaker-python-sdk) (πŸ‘¨β€πŸ’» 460 Β· πŸ”€ 1.1K Β· πŸ“¦ 4.3K Β· πŸ“‹ 1.5K - 20% open Β· ⏱️ 04.09.2024): ``` git clone https://github.com/aws/sagemaker-python-sdk ``` -- [PyPi](https://pypi.org/project/sagemaker) (πŸ“₯ 24M / month Β· πŸ“¦ 130 Β· ⏱️ 22.05.2024): +- [PyPi](https://pypi.org/project/sagemaker) (πŸ“₯ 34M / month Β· πŸ“¦ 140 Β· ⏱️ 30.08.2024): ``` pip install sagemaker ``` -- [Conda](https://anaconda.org/conda-forge/sagemaker-python-sdk) (πŸ“₯ 820K Β· ⏱️ 23.05.2024): +- [Conda](https://anaconda.org/conda-forge/sagemaker-python-sdk) (πŸ“₯ 1M Β· ⏱️ 31.07.2024): ``` conda install -c conda-forge sagemaker-python-sdk ```
-
PyCaret (πŸ₯ˆ37 Β· ⭐ 8.6K) - An open-source, low-code machine learning library in Python. MIT +
PyCaret (πŸ₯ˆ38 Β· ⭐ 8.8K) - An open-source, low-code machine learning library in Python. MIT -- [GitHub](https://github.com/pycaret/pycaret) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 1.7K Β· πŸ“₯ 690 Β· πŸ“¦ 5.8K Β· πŸ“‹ 2.3K - 15% open Β· ⏱️ 28.04.2024): +- [GitHub](https://github.com/pycaret/pycaret) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 1.7K Β· πŸ“₯ 700 Β· πŸ“¦ 6.3K Β· πŸ“‹ 2.3K - 15% open Β· ⏱️ 30.08.2024): ``` git clone https://github.com/pycaret/pycaret ``` -- [PyPi](https://pypi.org/project/pycaret) (πŸ“₯ 330K / month Β· πŸ“¦ 30 Β· ⏱️ 28.04.2024): +- [PyPi](https://pypi.org/project/pycaret) (πŸ“₯ 270K / month Β· πŸ“¦ 31 Β· ⏱️ 28.04.2024): ``` pip install pycaret ``` -- [Conda](https://anaconda.org/conda-forge/pycaret) (πŸ“₯ 47K Β· ⏱️ 25.04.2024): +- [Conda](https://anaconda.org/conda-forge/pycaret) (πŸ“₯ 53K Β· ⏱️ 25.04.2024): ``` conda install -c conda-forge pycaret ```
-
ClearML (πŸ₯ˆ34 Β· ⭐ 5.3K) - ClearML - Auto-Magical CI/CD to streamline your AI workload... Apache-2 - -- [GitHub](https://github.com/allegroai/clearml) (πŸ‘¨β€πŸ’» 98 Β· πŸ”€ 640 Β· πŸ“₯ 2.5K Β· πŸ“¦ 1.1K Β· πŸ“‹ 1K - 45% open Β· ⏱️ 05.06.2024): - - ``` - git clone https://github.com/allegroai/clearml - ``` -- [PyPi](https://pypi.org/project/clearml) (πŸ“₯ 310K / month Β· πŸ“¦ 34 Β· ⏱️ 21.05.2024): - ``` - pip install clearml - ``` -- [Docker Hub](https://hub.docker.com/r/allegroai/trains) (πŸ“₯ 30K Β· ⏱️ 05.10.2020): - ``` - docker pull allegroai/trains - ``` -
-
Metaflow (πŸ₯ˆ33 Β· ⭐ 7.7K) - Build and manage real-life ML, AI, and data science projects with.. Apache-2 +
Metaflow (πŸ₯ˆ34 Β· ⭐ 8K) - Build and manage real-life ML, AI, and data science projects with.. Apache-2 -- [GitHub](https://github.com/Netflix/metaflow) (πŸ‘¨β€πŸ’» 90 Β· πŸ”€ 730 Β· πŸ“¦ 670 Β· πŸ“‹ 700 - 46% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/Netflix/metaflow) (πŸ‘¨β€πŸ’» 93 Β· πŸ”€ 750 Β· πŸ“¦ 720 Β· πŸ“‹ 730 - 43% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/Netflix/metaflow ``` -- [PyPi](https://pypi.org/project/metaflow) (πŸ“₯ 310K / month Β· πŸ“¦ 45 Β· ⏱️ 05.06.2024): +- [PyPi](https://pypi.org/project/metaflow) (πŸ“₯ 710K / month Β· πŸ“¦ 45 Β· ⏱️ 04.09.2024): ``` pip install metaflow ``` -- [Conda](https://anaconda.org/conda-forge/metaflow) (πŸ“₯ 180K Β· ⏱️ 04.06.2024): +- [Conda](https://anaconda.org/conda-forge/metaflow) (πŸ“₯ 210K Β· ⏱️ 23.08.2024): ``` conda install -c conda-forge metaflow ```
-
AzureML SDK (πŸ₯ˆ33 Β· ⭐ 4K) - Python notebooks with ML and deep learning examples with Azure Machine.. MIT +
ClearML (πŸ₯ˆ34 Β· ⭐ 5.6K) - ClearML - Auto-Magical CI/CD to streamline your AI workload... Apache-2 -- [GitHub](https://github.com/Azure/MachineLearningNotebooks) (πŸ‘¨β€πŸ’» 64 Β· πŸ”€ 2.5K Β· πŸ“₯ 620 Β· πŸ“‹ 1.5K - 26% open Β· ⏱️ 16.05.2024): +- [GitHub](https://github.com/allegroai/clearml) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 640 Β· πŸ“₯ 2.8K Β· πŸ“¦ 1.3K Β· πŸ“‹ 1K - 45% open Β· ⏱️ 04.09.2024): ``` - git clone https://github.com/Azure/MachineLearningNotebooks + git clone https://github.com/allegroai/clearml ``` -- [PyPi](https://pypi.org/project/azureml-sdk) (πŸ“₯ 540K / month Β· πŸ“¦ 48 Β· ⏱️ 29.04.2024): +- [PyPi](https://pypi.org/project/clearml) (πŸ“₯ 310K / month Β· πŸ“¦ 35 Β· ⏱️ 27.08.2024): ``` - pip install azureml-sdk + pip install clearml + ``` +- [Docker Hub](https://hub.docker.com/r/allegroai/trains) (πŸ“₯ 30K Β· ⏱️ 05.10.2020): + ``` + docker pull allegroai/trains ```
-
snakemake (πŸ₯ˆ33 Β· ⭐ 2.1K) - This is the development home of the workflow management system.. MIT +
snakemake (πŸ₯ˆ34 Β· ⭐ 2.2K) - This is the development home of the workflow management system.. MIT -- [GitHub](https://github.com/snakemake/snakemake) (πŸ‘¨β€πŸ’» 330 Β· πŸ”€ 520 Β· πŸ“¦ 2K Β· πŸ“‹ 1.7K - 61% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/snakemake/snakemake) (πŸ‘¨β€πŸ’» 340 Β· πŸ”€ 540 Β· πŸ“¦ 2.1K Β· πŸ“‹ 1.8K - 61% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/snakemake/snakemake ``` -- [PyPi](https://pypi.org/project/snakemake) (πŸ“₯ 43K / month Β· πŸ“¦ 220 Β· ⏱️ 05.06.2024): +- [PyPi](https://pypi.org/project/snakemake) (πŸ“₯ 98K / month Β· πŸ“¦ 230 Β· ⏱️ 05.09.2024): ``` pip install snakemake ``` -- [Conda](https://anaconda.org/bioconda/snakemake) (πŸ“₯ 1.1M Β· ⏱️ 05.06.2024): +- [Conda](https://anaconda.org/bioconda/snakemake) (πŸ“₯ 1.2M Β· ⏱️ 21.08.2024): ``` conda install -c bioconda snakemake ```
-
tensorboardX (πŸ₯ˆ32 Β· ⭐ 7.8K Β· πŸ’€) - tensorboard for pytorch (and chainer, mxnet, numpy, ...). MIT +
tensorboardX (πŸ₯ˆ33 Β· ⭐ 7.8K Β· πŸ’€) - tensorboard for pytorch (and chainer, mxnet, numpy, ...). MIT -- [GitHub](https://github.com/lanpa/tensorboardX) (πŸ‘¨β€πŸ’» 82 Β· πŸ”€ 870 Β· πŸ“₯ 420 Β· πŸ“¦ 44K Β· πŸ“‹ 450 - 17% open Β· ⏱️ 12.11.2023): +- [GitHub](https://github.com/lanpa/tensorboardX) (πŸ‘¨β€πŸ’» 82 Β· πŸ”€ 860 Β· πŸ“₯ 440 Β· πŸ“¦ 48K Β· πŸ“‹ 460 - 17% open Β· ⏱️ 12.11.2023): ``` git clone https://github.com/lanpa/tensorboardX ``` -- [PyPi](https://pypi.org/project/tensorboardX) (πŸ“₯ 2.2M / month Β· πŸ“¦ 600 Β· ⏱️ 20.08.2023): +- [PyPi](https://pypi.org/project/tensorboardX) (πŸ“₯ 2.8M / month Β· πŸ“¦ 620 Β· ⏱️ 20.08.2023): ``` pip install tensorboardX ``` @@ -5628,176 +5566,164 @@ _Libraries to organize, track, and visualize machine learning experiments._ conda install -c conda-forge tensorboardx ```
-
kaggle (πŸ₯ˆ32 Β· ⭐ 6K) - Official Kaggle API. Apache-2 +
kaggle (πŸ₯ˆ32 Β· ⭐ 6.1K) - Official Kaggle API. Apache-2 -- [GitHub](https://github.com/Kaggle/kaggle-api) (πŸ‘¨β€πŸ’» 42 Β· πŸ”€ 1K Β· πŸ“¦ 21 Β· πŸ“‹ 460 - 32% open Β· ⏱️ 17.05.2024): +- [GitHub](https://github.com/Kaggle/kaggle-api) (πŸ‘¨β€πŸ’» 46 Β· πŸ”€ 1.1K Β· πŸ“¦ 21 Β· πŸ“‹ 480 - 31% open Β· ⏱️ 04.09.2024): ``` git clone https://github.com/Kaggle/kaggle-api ``` -- [PyPi](https://pypi.org/project/kaggle) (πŸ“₯ 210K / month Β· πŸ“¦ 180 Β· ⏱️ 17.05.2024): +- [PyPi](https://pypi.org/project/kaggle) (πŸ“₯ 200K / month Β· πŸ“¦ 200 Β· ⏱️ 24.07.2024): ``` pip install kaggle ``` -- [Conda](https://anaconda.org/conda-forge/kaggle) (πŸ“₯ 160K Β· ⏱️ 17.05.2024): +- [Conda](https://anaconda.org/conda-forge/kaggle) (πŸ“₯ 180K Β· ⏱️ 27.07.2024): ``` conda install -c conda-forge kaggle ```
-
aim (πŸ₯ˆ32 Β· ⭐ 4.9K) - Aim An easy-to-use & supercharged open-source experiment tracker. Apache-2 - -- [GitHub](https://github.com/aimhubio/aim) (πŸ‘¨β€πŸ’» 64 Β· πŸ”€ 290 Β· πŸ“¦ 580 Β· πŸ“‹ 1K - 34% open Β· ⏱️ 03.06.2024): - - ``` - git clone https://github.com/aimhubio/aim - ``` -- [PyPi](https://pypi.org/project/aim) (πŸ“₯ 73K / month Β· πŸ“¦ 36 Β· ⏱️ 05.06.2024): - ``` - pip install aim - ``` -- [Conda](https://anaconda.org/conda-forge/aim) (πŸ“₯ 49K Β· ⏱️ 16.06.2023): - ``` - conda install -c conda-forge aim - ``` -
-
Neptune.ai (πŸ₯ˆ31 Β· ⭐ 550) - The MLOps stack component for experiment tracking. Apache-2 +
aim (πŸ₯ˆ32 Β· ⭐ 5.1K) - Aim An easy-to-use & supercharged open-source experiment tracker. Apache-2 -- [GitHub](https://github.com/neptune-ai/neptune-client) (πŸ‘¨β€πŸ’» 54 Β· πŸ”€ 61 Β· πŸ“¦ 500 Β· πŸ“‹ 230 - 9% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/aimhubio/aim) (πŸ‘¨β€πŸ’» 76 Β· πŸ”€ 320 Β· πŸ“¦ 660 Β· πŸ“‹ 1K - 35% open Β· ⏱️ 29.08.2024): ``` - git clone https://github.com/neptune-ai/neptune-client + git clone https://github.com/aimhubio/aim ``` -- [PyPi](https://pypi.org/project/neptune-client) (πŸ“₯ 520K / month Β· πŸ“¦ 77 Β· ⏱️ 15.05.2024): +- [PyPi](https://pypi.org/project/aim) (πŸ“₯ 95K / month Β· πŸ“¦ 38 Β· ⏱️ 02.09.2024): ``` - pip install neptune-client + pip install aim ``` -- [Conda](https://anaconda.org/conda-forge/neptune-client) (πŸ“₯ 250K Β· ⏱️ 15.05.2024): +- [Conda](https://anaconda.org/conda-forge/aim) (πŸ“₯ 72K Β· ⏱️ 14.06.2024): ``` - conda install -c conda-forge neptune-client + conda install -c conda-forge aim ```
-
VisualDL (πŸ₯ˆ29 Β· ⭐ 4.7K Β· πŸ’€) - Deep Learning Visualization Toolkit. Apache-2 +
AzureML SDK (πŸ₯ˆ32 Β· ⭐ 4.1K) - Python notebooks with ML and deep learning examples with Azure.. MIT -- [GitHub](https://github.com/PaddlePaddle/VisualDL) (πŸ‘¨β€πŸ’» 33 Β· πŸ”€ 630 Β· πŸ“₯ 380 Β· πŸ“¦ 2.9K Β· πŸ“‹ 500 - 28% open Β· ⏱️ 20.09.2023): +- [GitHub](https://github.com/Azure/MachineLearningNotebooks) (πŸ‘¨β€πŸ’» 64 Β· πŸ”€ 2.5K Β· πŸ“₯ 630 Β· πŸ“‹ 1.5K - 26% open Β· ⏱️ 08.08.2024): ``` - git clone https://github.com/PaddlePaddle/VisualDL + git clone https://github.com/Azure/MachineLearningNotebooks ``` -- [PyPi](https://pypi.org/project/visualdl) (πŸ“₯ 220K / month Β· πŸ“¦ 46 Β· ⏱️ 05.06.2023): +- [PyPi](https://pypi.org/project/azureml-sdk) (πŸ“₯ 490K / month Β· πŸ“¦ 31 Β· ⏱️ 05.08.2024): ``` - pip install visualdl + pip install azureml-sdk ```
-
sacred (πŸ₯ˆ29 Β· ⭐ 4.2K Β· πŸ’€) - Sacred is a tool to help you configure, organize, log and reproduce.. MIT +
sacred (πŸ₯ˆ31 Β· ⭐ 4.2K) - Sacred is a tool to help you configure, organize, log and reproduce.. MIT -- [GitHub](https://github.com/IDSIA/sacred) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 380 Β· πŸ“¦ 3K Β· πŸ“‹ 560 - 17% open Β· ⏱️ 13.11.2023): +- [GitHub](https://github.com/IDSIA/sacred) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 380 Β· πŸ“¦ 3.2K Β· πŸ“‹ 560 - 18% open Β· ⏱️ 26.08.2024): ``` git clone https://github.com/IDSIA/sacred ``` -- [PyPi](https://pypi.org/project/sacred) (πŸ“₯ 31K / month Β· πŸ“¦ 58 Β· ⏱️ 13.11.2023): +- [PyPi](https://pypi.org/project/sacred) (πŸ“₯ 31K / month Β· πŸ“¦ 60 Β· ⏱️ 26.08.2024): ``` pip install sacred ``` -- [Conda](https://anaconda.org/conda-forge/sacred) (πŸ“₯ 5.4K Β· ⏱️ 28.11.2023): +- [Conda](https://anaconda.org/conda-forge/sacred) (πŸ“₯ 6.3K Β· ⏱️ 28.11.2023): ``` conda install -c conda-forge sacred ```
-
Labml (πŸ₯‰27 Β· ⭐ 1.9K) - Monitor deep learning model training and hardware usage from your mobile.. MIT +
Neptune.ai (πŸ₯ˆ30 Β· ⭐ 570) - The experiment tracker for foundation model training. Apache-2 -- [GitHub](https://github.com/labmlai/labml) (πŸ‘¨β€πŸ’» 9 Β· πŸ”€ 130 Β· πŸ“¦ 150 Β· πŸ“‹ 39 - 43% open Β· ⏱️ 28.05.2024): +- [GitHub](https://github.com/neptune-ai/neptune-client) (πŸ‘¨β€πŸ’» 54 Β· πŸ”€ 63 Β· πŸ“¦ 580 Β· πŸ“‹ 240 - 11% open Β· ⏱️ 02.08.2024): ``` - git clone https://github.com/labmlai/labml + git clone https://github.com/neptune-ai/neptune-client ``` -- [PyPi](https://pypi.org/project/labml) (πŸ“₯ 2.5K / month Β· πŸ“¦ 12 Β· ⏱️ 23.05.2024): +- [PyPi](https://pypi.org/project/neptune-client) (πŸ“₯ 440K / month Β· πŸ“¦ 77 Β· ⏱️ 20.08.2024): ``` - pip install labml + pip install neptune-client + ``` +- [Conda](https://anaconda.org/conda-forge/neptune-client) (πŸ“₯ 270K Β· ⏱️ 20.08.2024): + ``` + conda install -c conda-forge neptune-client ```
-
TNT (πŸ₯‰26 Β· ⭐ 1.6K) - A lightweight library for PyTorch training tools and utilities. BSD-3 +
VisualDL (πŸ₯‰27 Β· ⭐ 4.8K Β· πŸ’€) - Deep Learning Visualization Toolkit. Apache-2 -- [GitHub](https://github.com/pytorch/tnt) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 260 Β· πŸ“‹ 140 - 53% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/PaddlePaddle/VisualDL) (πŸ‘¨β€πŸ’» 33 Β· πŸ”€ 630 Β· πŸ“₯ 430 Β· πŸ“¦ 2 Β· πŸ“‹ 500 - 28% open Β· ⏱️ 20.09.2023): ``` - git clone https://github.com/pytorch/tnt + git clone https://github.com/PaddlePaddle/VisualDL ``` -- [PyPi](https://pypi.org/project/torchnet) (πŸ“₯ 7.4K / month Β· πŸ“¦ 24 Β· ⏱️ 29.07.2018): +- [PyPi](https://pypi.org/project/visualdl) (πŸ“₯ 150K / month Β· πŸ“¦ 82 Β· ⏱️ 05.06.2023): ``` - pip install torchnet + pip install visualdl ```
-
ml-metadata (πŸ₯‰26 Β· ⭐ 600) - For recording and retrieving metadata associated with ML.. Apache-2 +
Labml (πŸ₯‰27 Β· ⭐ 2K) - Monitor deep learning model training and hardware usage from your mobile phone. MIT -- [GitHub](https://github.com/google/ml-metadata) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 130 Β· πŸ“₯ 2.2K Β· πŸ“¦ 460 Β· πŸ“‹ 120 - 34% open Β· ⏱️ 04.06.2024): +- [GitHub](https://github.com/labmlai/labml) (πŸ‘¨β€πŸ’» 9 Β· πŸ”€ 130 Β· πŸ“¦ 170 Β· πŸ“‹ 47 - 10% open Β· ⏱️ 03.09.2024): ``` - git clone https://github.com/google/ml-metadata + git clone https://github.com/labmlai/labml ``` -- [PyPi](https://pypi.org/project/ml-metadata) (πŸ“₯ 88K / month Β· πŸ“¦ 31 Β· ⏱️ 23.04.2024): +- [PyPi](https://pypi.org/project/labml) (πŸ“₯ 3.2K / month Β· πŸ“¦ 14 Β· ⏱️ 23.05.2024): ``` - pip install ml-metadata + pip install labml ```
-
quinn (πŸ₯‰26 Β· ⭐ 580 Β· πŸ“ˆ) - pyspark methods to enhance developer productivity. Apache-2 +
TNT (πŸ₯‰26 Β· ⭐ 1.7K) - A lightweight library for PyTorch training tools and utilities. BSD-3 -- [GitHub](https://github.com/MrPowers/quinn) (πŸ‘¨β€πŸ’» 28 Β· πŸ”€ 91 Β· πŸ“₯ 23 Β· πŸ“¦ 77 Β· πŸ“‹ 120 - 31% open Β· ⏱️ 07.05.2024): +- [GitHub](https://github.com/pytorch/tnt) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 270 Β· πŸ“‹ 140 - 54% open Β· ⏱️ 30.08.2024): ``` - git clone https://github.com/MrPowers/quinn + git clone https://github.com/pytorch/tnt ``` -- [PyPi](https://pypi.org/project/quinn) (πŸ“₯ 760K / month Β· πŸ“¦ 7 Β· ⏱️ 13.02.2024): +- [PyPi](https://pypi.org/project/torchnet) (πŸ“₯ 4.8K / month Β· πŸ“¦ 24 Β· ⏱️ 29.07.2018): ``` - pip install quinn + pip install torchnet ```
-
gokart (πŸ₯‰25 Β· ⭐ 300) - Gokart solves reproducibility, task dependencies, constraints of good code,.. MIT +
quinn (πŸ₯‰26 Β· ⭐ 620) - pyspark methods to enhance developer productivity. Apache-2 -- [GitHub](https://github.com/m3dev/gokart) (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 56 Β· πŸ“¦ 78 Β· πŸ“‹ 80 - 25% open Β· ⏱️ 21.05.2024): +- [GitHub](https://github.com/mrpowers-io/quinn) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 95 Β· πŸ“₯ 32 Β· πŸ“¦ 83 Β· πŸ“‹ 130 - 27% open Β· ⏱️ 29.08.2024): ``` - git clone https://github.com/m3dev/gokart + git clone https://github.com/MrPowers/quinn ``` -- [PyPi](https://pypi.org/project/gokart) (πŸ“₯ 2.7K / month Β· πŸ“¦ 8 Β· ⏱️ 21.05.2024): +- [PyPi](https://pypi.org/project/quinn) (πŸ“₯ 660K / month Β· πŸ“¦ 7 Β· ⏱️ 13.02.2024): ``` - pip install gokart + pip install quinn ```
-
Guild AI (πŸ₯‰23 Β· ⭐ 860 Β· πŸ’€) - Experiment tracking, ML developer tools. Apache-2 +
ml-metadata (πŸ₯‰26 Β· ⭐ 610) - For recording and retrieving metadata associated with ML.. Apache-2 -- [GitHub](https://github.com/guildai/guildai) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 85 Β· πŸ“₯ 16 Β· πŸ“¦ 96 Β· πŸ“‹ 440 - 50% open Β· ⏱️ 12.08.2023): +- [GitHub](https://github.com/google/ml-metadata) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 140 Β· πŸ“₯ 2.4K Β· πŸ“¦ 550 Β· πŸ“‹ 120 - 36% open Β· ⏱️ 30.08.2024): ``` - git clone https://github.com/guildai/guildai + git clone https://github.com/google/ml-metadata ``` -- [PyPi](https://pypi.org/project/guildai) (πŸ“₯ 1.3K / month Β· ⏱️ 11.05.2022): +- [PyPi](https://pypi.org/project/ml-metadata) (πŸ“₯ 73K / month Β· πŸ“¦ 31 Β· ⏱️ 23.04.2024): ``` - pip install guildai + pip install ml-metadata ```
-
Studio.ml (πŸ₯‰21 Β· ⭐ 380 Β· πŸ’€) - Studio: Simplify and expedite model building process. Apache-2 +
gokart (πŸ₯‰25 Β· ⭐ 300) - Gokart solves reproducibility, task dependencies, constraints of good code,.. MIT -- [GitHub](https://github.com/studioml/studio) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 52 Β· πŸ“¦ 5 Β· πŸ“‹ 250 - 22% open Β· ⏱️ 06.09.2023): +- [GitHub](https://github.com/m3dev/gokart) (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 57 Β· πŸ“¦ 80 Β· πŸ“‹ 84 - 27% open Β· ⏱️ 04.09.2024): ``` - git clone https://github.com/studioml/studio + git clone https://github.com/m3dev/gokart ``` -- [PyPi](https://pypi.org/project/studioml) (πŸ“₯ 770 / month Β· ⏱️ 14.09.2021): +- [PyPi](https://pypi.org/project/gokart) (πŸ“₯ 4K / month Β· πŸ“¦ 8 Β· ⏱️ 04.09.2024): ``` - pip install studioml + pip install gokart ```
-
TensorWatch (πŸ₯‰20 Β· ⭐ 3.4K Β· πŸ’€) - Debugging, monitoring and visualization for Python Machine.. MIT +
Studio.ml (πŸ₯‰22 Β· ⭐ 380 Β· πŸ’€) - Studio: Simplify and expedite model building process. Apache-2 -- [GitHub](https://github.com/microsoft/tensorwatch) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 360 Β· πŸ“¦ 140 Β· πŸ“‹ 70 - 75% open Β· ⏱️ 30.08.2023): +- [GitHub](https://github.com/studioml/studio) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 52 Β· πŸ“¦ 6 Β· πŸ“‹ 250 - 22% open Β· ⏱️ 06.09.2023): ``` - git clone https://github.com/microsoft/tensorwatch + git clone https://github.com/studioml/studio ``` -- [PyPi](https://pypi.org/project/tensorwatch) (πŸ“₯ 820 / month Β· πŸ“¦ 7 Β· ⏱️ 04.03.2020): +- [PyPi](https://pypi.org/project/studioml) (πŸ“₯ 720 / month Β· ⏱️ 14.09.2021): ``` - pip install tensorwatch + pip install studioml ```
CometML (πŸ₯‰16) - Supercharging Machine Learning. MIT @@ -5807,7 +5733,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ ``` git clone https://github.com/comet-ml/examples ``` -- [PyPi](https://pypi.org/project/comet_ml) (πŸ“₯ 710K / month Β· πŸ“¦ 68 Β· ⏱️ 29.05.2024): +- [PyPi](https://pypi.org/project/comet_ml) (πŸ“₯ 770K / month Β· πŸ“¦ 74 Β· ⏱️ 28.08.2024): ``` pip install comet_ml ``` @@ -5816,31 +5742,33 @@ _Libraries to organize, track, and visualize machine learning experiments._ conda install -c anaconda comet_ml ```
-
caliban (πŸ₯‰15 Β· ⭐ 490) - Research workflows made easy, locally and in the Cloud. Apache-2 +
caliban (πŸ₯‰15 Β· ⭐ 490 Β· πŸ’€) - Research workflows made easy, locally and in the Cloud. Apache-2 -- [GitHub](https://github.com/google/caliban) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 67 Β· πŸ“‹ 34 - 55% open Β· ⏱️ 25.01.2024): +- [GitHub](https://github.com/google/caliban) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 66 Β· πŸ“¦ 3 Β· πŸ“‹ 34 - 55% open Β· ⏱️ 25.01.2024): ``` git clone https://github.com/google/caliban ``` -- [PyPi](https://pypi.org/project/caliban) (πŸ“₯ 71 / month Β· ⏱️ 12.09.2020): +- [PyPi](https://pypi.org/project/caliban) (πŸ“₯ 110 / month Β· ⏱️ 12.09.2020): ``` pip install caliban ```
-
Show 14 hidden projects... +
Show 16 hidden projects... -- Catalyst (πŸ₯‰28 Β· ⭐ 3.2K Β· πŸ’€) - Accelerated deep learning R&D. Apache-2 +- Catalyst (πŸ₯ˆ28 Β· ⭐ 3.3K Β· πŸ’€) - Accelerated deep learning R&D. Apache-2 - knockknock (πŸ₯‰26 Β· ⭐ 2.8K Β· πŸ’€) - Knock Knock: Get notified when your training ends with only two.. MIT - livelossplot (πŸ₯‰25 Β· ⭐ 1.3K Β· πŸ’€) - Live training loss plot in Jupyter Notebook for Keras,.. MIT -- SKLL (πŸ₯‰23 Β· ⭐ 550) - SciKit-Learn Laboratory (SKLL) makes it easy to run machine.. ❗️BSD-1-Clause +- SKLL (πŸ₯‰24 Β· ⭐ 550) - SciKit-Learn Laboratory (SKLL) makes it easy to run machine.. ❗️BSD-1-Clause +- Guild AI (πŸ₯‰23 Β· ⭐ 860 Β· πŸ’€) - Experiment tracking, ML developer tools. Apache-2 - hiddenlayer (πŸ₯‰22 Β· ⭐ 1.8K Β· πŸ’€) - Neural network graphs and training metrics for.. MIT +- lore (πŸ₯‰21 Β· ⭐ 1.6K Β· πŸ’€) - Lore makes machine learning approachable for Software Engineers and.. MIT - TensorBoard Logger (πŸ₯‰21 Β· ⭐ 630 Β· πŸ’€) - Log TensorBoard events without touching TensorFlow. MIT -- lore (πŸ₯‰20 Β· ⭐ 1.6K Β· πŸ’€) - Lore makes machine learning approachable for Software Engineers and.. MIT +- TensorWatch (πŸ₯‰20 Β· ⭐ 3.4K Β· πŸ’€) - Debugging, monitoring and visualization for Python Machine.. MIT +- MXBoard (πŸ₯‰20 Β· ⭐ 320 Β· πŸ’€) - Logging MXNet data for visualization in TensorBoard. Apache-2 - keepsake (πŸ₯‰18 Β· ⭐ 1.6K Β· πŸ’€) - Version control for machine learning. Apache-2 -- datmo (πŸ₯‰17 Β· ⭐ 340 Β· πŸ’€) - Open source production model management tool for data scientists. MIT -- chitra (πŸ₯‰17 Β· ⭐ 220) - A multi-functional library for full-stack Deep Learning. Simplifies.. Apache-2 -- MXBoard (πŸ₯‰16 Β· ⭐ 320 Β· πŸ’€) - Logging MXNet data for visualization in TensorBoard. Apache-2 +- datmo (πŸ₯‰18 Β· ⭐ 340 Β· πŸ’€) - Open source production model management tool for data scientists. MIT +- chitra (πŸ₯‰18 Β· ⭐ 220) - A multi-functional library for full-stack Deep Learning. Simplifies.. Apache-2 - steppy (πŸ₯‰16 Β· ⭐ 130 Β· πŸ’€) - Lightweight, Python library for fast and reproducible experimentation. MIT - ModelChimp (πŸ₯‰12 Β· ⭐ 130 Β· πŸ’€) - Experiment tracking for machine and deep learning projects. BSD-2 - traintool (πŸ₯‰9 Β· ⭐ 12 Β· πŸ’€) - Train off-the-shelf machine learning models in one.. Apache-2 @@ -5853,166 +5781,166 @@ _Libraries to organize, track, and visualize machine learning experiments._ _Libraries to serialize models to files, convert between a variety of model formats, and optimize models for deployment._ -
onnx (πŸ₯‡43 Β· ⭐ 17K) - Open standard for machine learning interoperability. Apache-2 +
onnx (πŸ₯‡43 Β· ⭐ 18K) - Open standard for machine learning interoperability. Apache-2 -- [GitHub](https://github.com/onnx/onnx) (πŸ‘¨β€πŸ’» 320 Β· πŸ”€ 3.6K Β· πŸ“₯ 21K Β· πŸ“¦ 29K Β· πŸ“‹ 2.8K - 11% open Β· ⏱️ 03.06.2024): +- [GitHub](https://github.com/onnx/onnx) (πŸ‘¨β€πŸ’» 320 Β· πŸ”€ 3.6K Β· πŸ“₯ 22K Β· πŸ“¦ 33K Β· πŸ“‹ 2.8K - 12% open Β· ⏱️ 04.09.2024): ``` git clone https://github.com/onnx/onnx ``` -- [PyPi](https://pypi.org/project/onnx) (πŸ“₯ 5.7M / month Β· πŸ“¦ 930 Β· ⏱️ 23.05.2024): +- [PyPi](https://pypi.org/project/onnx) (πŸ“₯ 5.7M / month Β· πŸ“¦ 1K Β· ⏱️ 01.08.2024): ``` pip install onnx ``` -- [Conda](https://anaconda.org/conda-forge/onnx) (πŸ“₯ 1M Β· ⏱️ 24.05.2024): +- [Conda](https://anaconda.org/conda-forge/onnx) (πŸ“₯ 1.2M Β· ⏱️ 03.09.2024): ``` conda install -c conda-forge onnx ```
triton (πŸ₯‡43 Β· ⭐ 12K) - Development repository for the Triton language and compiler. MIT -- [GitHub](https://github.com/triton-lang/triton) (πŸ‘¨β€πŸ’» 280 Β· πŸ”€ 1.3K Β· πŸ“¦ 27K Β· πŸ“‹ 1.2K - 42% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/triton-lang/triton) (πŸ‘¨β€πŸ’» 320 Β· πŸ”€ 1.5K Β· πŸ“¦ 36K Β· πŸ“‹ 1.4K - 44% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/openai/triton ``` -- [PyPi](https://pypi.org/project/triton) (πŸ“₯ 12M / month Β· πŸ“¦ 180 Β· ⏱️ 27.05.2024): +- [PyPi](https://pypi.org/project/triton) (πŸ“₯ 14M / month Β· πŸ“¦ 230 Β· ⏱️ 09.07.2024): ``` pip install triton ```
-
huggingface_hub (πŸ₯ˆ38 Β· ⭐ 1.8K) - The official Python client for the Huggingface Hub. Apache-2 +
huggingface_hub (πŸ₯ˆ38 Β· ⭐ 2K) - The official Python client for the Huggingface Hub. Apache-2 -- [GitHub](https://github.com/huggingface/huggingface_hub) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 460 Β· πŸ“‹ 830 - 16% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/huggingface/huggingface_hub) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 510 Β· πŸ“‹ 920 - 15% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/huggingface/huggingface_hub ``` -- [PyPi](https://pypi.org/project/huggingface_hub) (πŸ“₯ 36M / month Β· πŸ“¦ 1.3K Β· ⏱️ 05.06.2024): +- [PyPi](https://pypi.org/project/huggingface_hub) (πŸ“₯ 41M / month Β· πŸ“¦ 1.7K Β· ⏱️ 19.08.2024): ``` pip install huggingface_hub ``` -- [Conda](https://anaconda.org/conda-forge/huggingface_hub) (πŸ“₯ 1.8M Β· ⏱️ 05.06.2024): +- [Conda](https://anaconda.org/conda-forge/huggingface_hub) (πŸ“₯ 2.1M Β· ⏱️ 19.08.2024): ``` conda install -c conda-forge huggingface_hub ```
-
BentoML (πŸ₯ˆ35 Β· ⭐ 6.7K) - The easiest way to serve AI/ML models in production - Build Model.. Apache-2 +
BentoML (πŸ₯ˆ35 Β· ⭐ 7K) - The easiest way to serve AI apps and models - Build reliable Inference.. Apache-2 -- [GitHub](https://github.com/bentoml/BentoML) (πŸ‘¨β€πŸ’» 200 Β· πŸ”€ 760 Β· πŸ“₯ 1.6K Β· πŸ“¦ 1.8K Β· πŸ“‹ 1.1K - 22% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/bentoml/BentoML) (πŸ‘¨β€πŸ’» 210 Β· πŸ”€ 770 Β· πŸ“₯ 1.3K Β· πŸ“¦ 2K Β· πŸ“‹ 1.1K - 15% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/bentoml/BentoML ``` -- [PyPi](https://pypi.org/project/bentoml) (πŸ“₯ 100K / month Β· πŸ“¦ 23 Β· ⏱️ 03.06.2024): +- [PyPi](https://pypi.org/project/bentoml) (πŸ“₯ 110K / month Β· πŸ“¦ 26 Β· ⏱️ 23.08.2024): ``` pip install bentoml ```
-
Core ML Tools (πŸ₯ˆ35 Β· ⭐ 4.1K) - Core ML tools contain supporting tools for Core ML model.. BSD-3 +
Core ML Tools (πŸ₯ˆ35 Β· ⭐ 4.3K) - Core ML tools contain supporting tools for Core ML model.. BSD-3 -- [GitHub](https://github.com/apple/coremltools) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 600 Β· πŸ“₯ 9.7K Β· πŸ“¦ 3.9K Β· πŸ“‹ 1.4K - 22% open Β· ⏱️ 17.05.2024): +- [GitHub](https://github.com/apple/coremltools) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 620 Β· πŸ“₯ 11K Β· πŸ“¦ 4.1K Β· πŸ“‹ 1.4K - 24% open Β· ⏱️ 31.08.2024): ``` git clone https://github.com/apple/coremltools ``` -- [PyPi](https://pypi.org/project/coremltools) (πŸ“₯ 550K / month Β· πŸ“¦ 71 Β· ⏱️ 23.04.2024): +- [PyPi](https://pypi.org/project/coremltools) (πŸ“₯ 900K / month Β· πŸ“¦ 76 Β· ⏱️ 16.08.2024): ``` pip install coremltools ``` -- [Conda](https://anaconda.org/conda-forge/coremltools) (πŸ“₯ 59K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/coremltools) (πŸ“₯ 68K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge coremltools ```
-
TorchServe (πŸ₯ˆ35 Β· ⭐ 4K) - Serve, optimize and scale PyTorch models in production. Apache-2 +
TorchServe (πŸ₯ˆ35 Β· ⭐ 4.2K) - Serve, optimize and scale PyTorch models in production. Apache-2 -- [GitHub](https://github.com/pytorch/serve) (πŸ‘¨β€πŸ’» 200 Β· πŸ”€ 820 Β· πŸ“₯ 5.7K Β· πŸ“¦ 660 Β· πŸ“‹ 1.6K - 23% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/pytorch/serve) (πŸ‘¨β€πŸ’» 210 Β· πŸ”€ 840 Β· πŸ“₯ 6.2K Β· πŸ“¦ 710 Β· πŸ“‹ 1.7K - 23% open Β· ⏱️ 24.08.2024): ``` git clone https://github.com/pytorch/serve ``` -- [PyPi](https://pypi.org/project/torchserve) (πŸ“₯ 59K / month Β· πŸ“¦ 21 Β· ⏱️ 16.05.2024): +- [PyPi](https://pypi.org/project/torchserve) (πŸ“₯ 52K / month Β· πŸ“¦ 22 Β· ⏱️ 18.07.2024): ``` pip install torchserve ``` -- [Conda](https://anaconda.org/pytorch/torchserve) (πŸ“₯ 190K Β· ⏱️ 16.05.2024): +- [Conda](https://anaconda.org/pytorch/torchserve) (πŸ“₯ 250K Β· ⏱️ 18.07.2024): ``` conda install -c pytorch torchserve ``` -- [Docker Hub](https://hub.docker.com/r/pytorch/torchserve) (πŸ“₯ 1.3M Β· ⭐ 27 Β· ⏱️ 16.05.2024): +- [Docker Hub](https://hub.docker.com/r/pytorch/torchserve) (πŸ“₯ 1.3M Β· ⭐ 28 Β· ⏱️ 18.07.2024): ``` docker pull pytorch/torchserve ```
-
hls4ml (πŸ₯ˆ26 Β· ⭐ 1.1K) - Machine learning on FPGAs using HLS. Apache-2 +
hls4ml (πŸ₯ˆ26 Β· ⭐ 1.2K) - Machine learning on FPGAs using HLS. Apache-2 -- [GitHub](https://github.com/fastmachinelearning/hls4ml) (πŸ‘¨β€πŸ’» 61 Β· πŸ”€ 360 Β· πŸ“‹ 410 - 38% open Β· ⏱️ 31.05.2024): +- [GitHub](https://github.com/fastmachinelearning/hls4ml) (πŸ‘¨β€πŸ’» 62 Β· πŸ”€ 390 Β· πŸ“‹ 430 - 40% open Β· ⏱️ 03.09.2024): ``` git clone https://github.com/fastmachinelearning/hls4ml ``` -- [PyPi](https://pypi.org/project/hls4ml) (πŸ“₯ 940 / month Β· ⏱️ 19.12.2023): +- [PyPi](https://pypi.org/project/hls4ml) (πŸ“₯ 990 / month Β· ⏱️ 19.12.2023): ``` pip install hls4ml ``` -- [Conda](https://anaconda.org/conda-forge/hls4ml) (πŸ“₯ 7.7K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/hls4ml) (πŸ“₯ 8.5K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge hls4ml ```
-
Hummingbird (πŸ₯‰25 Β· ⭐ 3.3K) - Hummingbird compiles trained ML models into tensor computation for.. MIT +
Hummingbird (πŸ₯‰24 Β· ⭐ 3.3K) - Hummingbird compiles trained ML models into tensor computation for.. MIT -- [GitHub](https://github.com/microsoft/hummingbird) (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 270 Β· πŸ“₯ 500 Β· πŸ“‹ 320 - 18% open Β· ⏱️ 30.05.2024): +- [GitHub](https://github.com/microsoft/hummingbird) (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 280 Β· πŸ“₯ 630 Β· πŸ“‹ 330 - 21% open Β· ⏱️ 12.08.2024): ``` git clone https://github.com/microsoft/hummingbird ``` -- [PyPi](https://pypi.org/project/hummingbird-ml) (πŸ“₯ 4.7K / month Β· πŸ“¦ 4 Β· ⏱️ 08.03.2024): +- [PyPi](https://pypi.org/project/hummingbird-ml) (πŸ“₯ 3.9K / month Β· πŸ“¦ 7 Β· ⏱️ 08.03.2024): ``` pip install hummingbird-ml ``` -- [Conda](https://anaconda.org/conda-forge/hummingbird-ml) (πŸ“₯ 41K Β· ⏱️ 08.03.2024): +- [Conda](https://anaconda.org/conda-forge/hummingbird-ml) (πŸ“₯ 47K Β· ⏱️ 08.03.2024): ``` conda install -c conda-forge hummingbird-ml ```
-
nebullvm (πŸ₯‰21 Β· ⭐ 8.4K Β· πŸ’€) - The user analytics platform for LLMs. Apache-2 +
nebullvm (πŸ₯‰22 Β· ⭐ 8.4K) - A collection of libraries to optimise AI model performances. Apache-2 -- [GitHub](https://github.com/nebuly-ai/nebuly) (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 640 Β· πŸ“‹ 200 - 48% open Β· ⏱️ 28.10.2023): +- [GitHub](https://github.com/nebuly-ai/optimate) (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 640 Β· πŸ“‹ 200 - 49% open Β· ⏱️ 22.07.2024): ``` git clone https://github.com/nebuly-ai/nebullvm ``` -- [PyPi](https://pypi.org/project/nebullvm) (πŸ“₯ 540 / month Β· πŸ“¦ 2 Β· ⏱️ 18.06.2023): +- [PyPi](https://pypi.org/project/nebullvm) (πŸ“₯ 980 / month Β· πŸ“¦ 2 Β· ⏱️ 18.06.2023): ``` pip install nebullvm ```
-
tfdeploy (πŸ₯‰16 Β· ⭐ 350) - Deploy tensorflow graphs for fast evaluation and export to.. BSD-3 +
tfdeploy (πŸ₯‰16 Β· ⭐ 350 Β· πŸ’€) - Deploy tensorflow graphs for fast evaluation and export to.. BSD-3 - [GitHub](https://github.com/riga/tfdeploy) (πŸ‘¨β€πŸ’» 4 Β· πŸ”€ 38 Β· πŸ“‹ 34 - 32% open Β· ⏱️ 25.02.2024): ``` git clone https://github.com/riga/tfdeploy ``` -- [PyPi](https://pypi.org/project/tfdeploy) (πŸ“₯ 54 / month Β· ⏱️ 30.03.2017): +- [PyPi](https://pypi.org/project/tfdeploy) (πŸ“₯ 93 / month Β· ⏱️ 30.03.2017): ``` pip install tfdeploy ```
Show 10 hidden projects... -- mmdnn (πŸ₯ˆ26 Β· ⭐ 5.8K Β· πŸ’€) - MMdnn is a set of tools to help users inter-operate among different deep.. MIT -- m2cgen (πŸ₯‰25 Β· ⭐ 2.7K Β· πŸ’€) - Transform ML models into a native code (Java, C, Python, Go,.. MIT -- sklearn-porter (πŸ₯‰24 Β· ⭐ 1.3K Β· πŸ’€) - Transpile trained scikit-learn estimators to C, Java,.. BSD-3 +- m2cgen (πŸ₯ˆ26 Β· ⭐ 2.8K Β· πŸ’€) - Transform ML models into a native code (Java, C, Python, Go,.. MIT +- mmdnn (πŸ₯‰25 Β· ⭐ 5.8K Β· πŸ’€) - MMdnn is a set of tools to help users inter-operate among different deep.. MIT +- sklearn-porter (πŸ₯‰23 Β· ⭐ 1.3K Β· πŸ’€) - Transpile trained scikit-learn estimators to C, Java,.. BSD-3 - cortex (πŸ₯‰22 Β· ⭐ 8K Β· πŸ’€) - Production infrastructure for machine learning at scale. Apache-2 -- OMLT (πŸ₯‰20 Β· ⭐ 250) - Represent trained machine learning models as Pyomo optimization formulations. BSD-3 -- pytorch2keras (πŸ₯‰19 Β· ⭐ 850 Β· πŸ’€) - PyTorch to Keras model convertor. MIT -- modelkit (πŸ₯‰19 Β· ⭐ 150) - Toolkit for developing and maintaining ML models. MIT -- Larq Compute Engine (πŸ₯‰18 Β· ⭐ 240) - Highly optimized inference engine for Binarized.. Apache-2 +- OMLT (πŸ₯‰21 Β· ⭐ 260) - Represent trained machine learning models as Pyomo optimization.. ❗Unlicensed +- Larq Compute Engine (πŸ₯‰21 Β· ⭐ 240) - Highly optimized inference engine for Binarized.. Apache-2 +- pytorch2keras (πŸ₯‰19 Β· ⭐ 860 Β· πŸ’€) - PyTorch to Keras model convertor. MIT +- backprop (πŸ₯‰16 Β· ⭐ 240 Β· πŸ’€) - Backprop makes it simple to use, finetune, and deploy state-of-.. Apache-2 +- modelkit (πŸ₯‰16 Β· ⭐ 150) - Toolkit for developing and maintaining ML models. MIT - ml-ane-transformers (πŸ₯‰13 Β· ⭐ 2.5K Β· πŸ’€) - Reference implementation of the Transformer.. ❗Unlicensed -- backprop (πŸ₯‰13 Β· ⭐ 240 Β· πŸ’€) - Backprop makes it simple to use, finetune, and deploy state-of-.. Apache-2

@@ -6022,485 +5950,459 @@ _Libraries to serialize models to files, convert between a variety of model form _Libraries to visualize, explain, debug, evaluate, and interpret machine learning models._ -
shap (πŸ₯‡42 Β· ⭐ 22K) - A game theoretic approach to explain the output of any machine learning model. MIT +
shap (πŸ₯‡43 Β· ⭐ 22K) - A game theoretic approach to explain the output of any machine learning model. MIT -- [GitHub](https://github.com/shap/shap) (πŸ‘¨β€πŸ’» 240 Β· πŸ”€ 3.2K Β· πŸ“¦ 18K Β· πŸ“‹ 2.5K - 32% open Β· ⏱️ 04.06.2024): +- [GitHub](https://github.com/shap/shap) (πŸ‘¨β€πŸ’» 250 Β· πŸ”€ 3.2K Β· πŸ“¦ 20K Β· πŸ“‹ 2.5K - 30% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/slundberg/shap ``` -- [PyPi](https://pypi.org/project/shap) (πŸ“₯ 6.8M / month Β· πŸ“¦ 690 Β· ⏱️ 07.05.2024): +- [PyPi](https://pypi.org/project/shap) (πŸ“₯ 6.4M / month Β· πŸ“¦ 740 Β· ⏱️ 27.06.2024): ``` pip install shap ``` -- [Conda](https://anaconda.org/conda-forge/shap) (πŸ“₯ 2.9M Β· ⏱️ 08.05.2024): +- [Conda](https://anaconda.org/conda-forge/shap) (πŸ“₯ 3.7M Β· ⏱️ 08.05.2024): ``` conda install -c conda-forge shap ```
-
arviz (πŸ₯‡36 Β· ⭐ 1.5K) - Exploratory analysis of Bayesian models with Python. Apache-2 +
Netron (πŸ₯‡37 Β· ⭐ 27K Β· πŸ“ˆ) - Visualizer for neural network, deep learning and machine.. MIT -- [GitHub](https://github.com/arviz-devs/arviz) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 380 Β· πŸ“₯ 140 Β· πŸ“¦ 6.7K Β· πŸ“‹ 850 - 20% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/lutzroeder/netron) (πŸ‘¨β€πŸ’» 2 Β· πŸ”€ 2.7K Β· πŸ“₯ 99K Β· πŸ“¦ 550 Β· πŸ“‹ 1.1K - 1% open Β· ⏱️ 05.09.2024): ``` - git clone https://github.com/arviz-devs/arviz - ``` -- [PyPi](https://pypi.org/project/arviz) (πŸ“₯ 2.4M / month Β· πŸ“¦ 280 Β· ⏱️ 05.04.2024): - ``` - pip install arviz + git clone https://github.com/lutzroeder/netron ``` -- [Conda](https://anaconda.org/conda-forge/arviz) (πŸ“₯ 2.1M Β· ⏱️ 04.06.2024): +- [PyPi](https://pypi.org/project/netron) (πŸ“₯ 34K / month Β· πŸ“¦ 83 Β· ⏱️ 30.08.2024): ``` - conda install -c conda-forge arviz + pip install netron ```
-
Netron (πŸ₯‡34 Β· ⭐ 27K) - Visualizer for neural network, deep learning and machine learning.. MIT +
arviz (πŸ₯‡36 Β· ⭐ 1.6K) - Exploratory analysis of Bayesian models with Python. Apache-2 -- [GitHub](https://github.com/lutzroeder/netron) (πŸ‘¨β€πŸ’» 2 Β· πŸ”€ 2.7K Β· πŸ“₯ 110K Β· πŸ“¦ 12 Β· πŸ“‹ 1.1K - 2% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/arviz-devs/arviz) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 390 Β· πŸ“₯ 140 Β· πŸ“¦ 7.4K Β· πŸ“‹ 860 - 20% open Β· ⏱️ 28.08.2024): ``` - git clone https://github.com/lutzroeder/netron + git clone https://github.com/arviz-devs/arviz ``` -- [PyPi](https://pypi.org/project/netron) (πŸ“₯ 25K / month Β· πŸ“¦ 79 Β· ⏱️ 01.06.2024): +- [PyPi](https://pypi.org/project/arviz) (πŸ“₯ 1.5M / month Β· πŸ“¦ 290 Β· ⏱️ 19.07.2024): ``` - pip install netron + pip install arviz + ``` +- [Conda](https://anaconda.org/conda-forge/arviz) (πŸ“₯ 2.2M Β· ⏱️ 20.07.2024): + ``` + conda install -c conda-forge arviz ```
-
InterpretML (πŸ₯‡33 Β· ⭐ 6.1K) - Fit interpretable models. Explain blackbox machine learning. MIT +
InterpretML (πŸ₯‡33 Β· ⭐ 6.2K) - Fit interpretable models. Explain blackbox machine learning. MIT -- [GitHub](https://github.com/interpretml/interpret) (πŸ‘¨β€πŸ’» 44 Β· πŸ”€ 720 Β· πŸ“¦ 690 Β· πŸ“‹ 430 - 23% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/interpretml/interpret) (πŸ‘¨β€πŸ’» 46 Β· πŸ”€ 730 Β· πŸ“¦ 730 Β· πŸ“‹ 440 - 23% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/interpretml/interpret ``` -- [PyPi](https://pypi.org/project/interpret) (πŸ“₯ 81K / month Β· πŸ“¦ 45 Β· ⏱️ 14.04.2024): +- [PyPi](https://pypi.org/project/interpret) (πŸ“₯ 88K / month Β· πŸ“¦ 49 Β· ⏱️ 07.08.2024): ``` pip install interpret ```
-
Captum (πŸ₯‡32 Β· ⭐ 4.6K) - Model interpretability and understanding for PyTorch. BSD-3 +
Captum (πŸ₯‡33 Β· ⭐ 4.8K) - Model interpretability and understanding for PyTorch. BSD-3 -- [GitHub](https://github.com/pytorch/captum) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 460 Β· πŸ“¦ 2.1K Β· πŸ“‹ 550 - 38% open Β· ⏱️ 31.05.2024): +- [GitHub](https://github.com/pytorch/captum) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 480 Β· πŸ“¦ 2.3K Β· πŸ“‹ 570 - 40% open Β· ⏱️ 22.08.2024): ``` git clone https://github.com/pytorch/captum ``` -- [PyPi](https://pypi.org/project/captum) (πŸ“₯ 240K / month Β· πŸ“¦ 110 Β· ⏱️ 05.12.2023): +- [PyPi](https://pypi.org/project/captum) (πŸ“₯ 250K / month Β· πŸ“¦ 130 Β· ⏱️ 05.12.2023): ``` pip install captum ``` -- [Conda](https://anaconda.org/conda-forge/captum) (πŸ“₯ 26K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/captum) (πŸ“₯ 58K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge captum ```
-
explainerdashboard (πŸ₯‡32 Β· ⭐ 2.2K) - Quickly build Explainable AI dashboards that show the inner.. MIT - -- [GitHub](https://github.com/oegedijk/explainerdashboard) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 320 Β· πŸ“¦ 490 Β· πŸ“‹ 240 - 14% open Β· ⏱️ 18.03.2024): - - ``` - git clone https://github.com/oegedijk/explainerdashboard - ``` -- [PyPi](https://pypi.org/project/explainerdashboard) (πŸ“₯ 81K / month Β· πŸ“¦ 10 Β· ⏱️ 18.03.2024): - ``` - pip install explainerdashboard - ``` -- [Conda](https://anaconda.org/conda-forge/explainerdashboard) (πŸ“₯ 46K Β· ⏱️ 18.03.2024): - ``` - conda install -c conda-forge explainerdashboard - ``` -
-
evaluate (πŸ₯‡32 Β· ⭐ 1.9K) - Evaluate: A library for easily evaluating machine learning models.. Apache-2 +
evaluate (πŸ₯ˆ31 Β· ⭐ 1.9K) - Evaluate: A library for easily evaluating machine learning models.. Apache-2 -- [GitHub](https://github.com/huggingface/evaluate) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 220 Β· πŸ“¦ 9.7K Β· πŸ“‹ 310 - 57% open Β· ⏱️ 30.04.2024): +- [GitHub](https://github.com/huggingface/evaluate) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 240 Β· πŸ“¦ 12K Β· πŸ“‹ 340 - 60% open Β· ⏱️ 10.06.2024): ``` git clone https://github.com/huggingface/evaluate ``` -- [PyPi](https://pypi.org/project/evaluate) (πŸ“₯ 2.7M / month Β· πŸ“¦ 340 Β· ⏱️ 30.04.2024): +- [PyPi](https://pypi.org/project/evaluate) (πŸ“₯ 2.2M / month Β· πŸ“¦ 400 Β· ⏱️ 30.04.2024): ``` pip install evaluate ```
pyLDAvis (πŸ₯ˆ30 Β· ⭐ 1.8K) - Python library for interactive topic model visualization. Port of.. BSD-3 -- [GitHub](https://github.com/bmabey/pyLDAvis) (πŸ‘¨β€πŸ’» 43 Β· πŸ”€ 360 Β· πŸ“¦ 6.1K Β· πŸ“‹ 190 - 40% open Β· ⏱️ 29.04.2024): +- [GitHub](https://github.com/bmabey/pyLDAvis) (πŸ‘¨β€πŸ’» 42 Β· πŸ”€ 360 Β· πŸ“¦ 6.4K Β· πŸ“‹ 190 - 40% open Β· ⏱️ 29.04.2024): ``` git clone https://github.com/bmabey/pyLDAvis ``` -- [PyPi](https://pypi.org/project/pyldavis) (πŸ“₯ 150K / month Β· πŸ“¦ 99 Β· ⏱️ 23.04.2023): +- [PyPi](https://pypi.org/project/pyldavis) (πŸ“₯ 130K / month Β· πŸ“¦ 100 Β· ⏱️ 23.04.2023): ``` pip install pyldavis ``` -- [Conda](https://anaconda.org/conda-forge/pyldavis) (πŸ“₯ 81K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/pyldavis) (πŸ“₯ 85K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge pyldavis ```
-
responsible-ai-widgets (πŸ₯ˆ30 Β· ⭐ 1.3K) - Responsible AI Toolbox is a suite of tools providing.. MIT +
Model Analysis (πŸ₯ˆ30 Β· ⭐ 1.3K) - Model analysis tools for TensorFlow. Apache-2 -- [GitHub](https://github.com/microsoft/responsible-ai-toolbox) (πŸ‘¨β€πŸ’» 42 Β· πŸ”€ 320 Β· πŸ“¦ 100 Β· πŸ“‹ 320 - 27% open Β· ⏱️ 21.05.2024): +- [GitHub](https://github.com/tensorflow/model-analysis) (πŸ‘¨β€πŸ’» 57 Β· πŸ”€ 270 Β· πŸ“‹ 88 - 37% open Β· ⏱️ 30.08.2024): ``` - git clone https://github.com/microsoft/responsible-ai-toolbox + git clone https://github.com/tensorflow/model-analysis ``` -- [PyPi](https://pypi.org/project/raiwidgets) (πŸ“₯ 12K / month Β· πŸ“¦ 6 Β· ⏱️ 20.05.2024): +- [PyPi](https://pypi.org/project/tensorflow-model-analysis) (πŸ“₯ 210K / month Β· πŸ“¦ 19 Β· ⏱️ 25.04.2024): ``` - pip install raiwidgets + pip install tensorflow-model-analysis ```
-
DoWhy (πŸ₯ˆ29 Β· ⭐ 6.8K) - DoWhy is a Python library for causal inference that supports explicit.. MIT +
DoWhy (πŸ₯ˆ29 Β· ⭐ 7K) - DoWhy is a Python library for causal inference that supports explicit modeling.. MIT -- [GitHub](https://github.com/py-why/dowhy) (πŸ‘¨β€πŸ’» 90 Β· πŸ”€ 900 Β· πŸ“₯ 35 Β· πŸ“¦ 380 Β· πŸ“‹ 450 - 28% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/py-why/dowhy) (πŸ‘¨β€πŸ’» 92 Β· πŸ”€ 910 Β· πŸ“₯ 39 Β· πŸ“¦ 420 Β· πŸ“‹ 470 - 27% open Β· ⏱️ 04.08.2024): ``` git clone https://github.com/py-why/dowhy ``` -- [PyPi](https://pypi.org/project/dowhy) (πŸ“₯ 45K / month Β· πŸ“¦ 7 Β· ⏱️ 25.12.2023): +- [PyPi](https://pypi.org/project/dowhy) (πŸ“₯ 40K / month Β· πŸ“¦ 7 Β· ⏱️ 25.12.2023): ``` pip install dowhy ``` -- [Conda](https://anaconda.org/conda-forge/dowhy) (πŸ“₯ 22K Β· ⏱️ 26.01.2024): +- [Conda](https://anaconda.org/conda-forge/dowhy) (πŸ“₯ 30K Β· ⏱️ 26.01.2024): ``` conda install -c conda-forge dowhy ```
shapash (πŸ₯ˆ29 Β· ⭐ 2.7K) - Shapash: User-friendly Explainability and Interpretability to.. Apache-2 -- [GitHub](https://github.com/MAIF/shapash) (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 320 Β· πŸ“¦ 160 Β· πŸ“‹ 190 - 17% open Β· ⏱️ 06.05.2024): +- [GitHub](https://github.com/MAIF/shapash) (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 330 Β· πŸ“¦ 170 Β· πŸ“‹ 200 - 17% open Β· ⏱️ 03.09.2024): ``` git clone https://github.com/MAIF/shapash ``` -- [PyPi](https://pypi.org/project/shapash) (πŸ“₯ 6.9K / month Β· πŸ“¦ 4 Β· ⏱️ 06.05.2024): +- [PyPi](https://pypi.org/project/shapash) (πŸ“₯ 7.3K / month Β· πŸ“¦ 4 Β· ⏱️ 04.07.2024): ``` pip install shapash ```
-
fairlearn (πŸ₯ˆ29 Β· ⭐ 1.8K) - A Python package to assess and improve fairness of machine.. MIT +
explainerdashboard (πŸ₯ˆ29 Β· ⭐ 2.3K) - Quickly build Explainable AI dashboards that show the inner.. MIT -- [GitHub](https://github.com/fairlearn/fairlearn) (πŸ‘¨β€πŸ’» 82 Β· πŸ”€ 390 Β· πŸ“¦ 3 Β· πŸ“‹ 460 - 36% open Β· ⏱️ 04.06.2024): +- [GitHub](https://github.com/oegedijk/explainerdashboard) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 320 Β· πŸ“¦ 530 Β· πŸ“‹ 240 - 14% open Β· ⏱️ 20.06.2024): ``` - git clone https://github.com/fairlearn/fairlearn + git clone https://github.com/oegedijk/explainerdashboard ``` -- [PyPi](https://pypi.org/project/fairlearn) (πŸ“₯ 230K / month Β· πŸ“¦ 50 Β· ⏱️ 19.12.2023): +- [PyPi](https://pypi.org/project/explainerdashboard) (πŸ“₯ 90K / month Β· πŸ“¦ 10 Β· ⏱️ 18.03.2024): ``` - pip install fairlearn + pip install explainerdashboard ``` -- [Conda](https://anaconda.org/conda-forge/fairlearn) (πŸ“₯ 33K Β· ⏱️ 20.12.2023): +- [Conda](https://anaconda.org/conda-forge/explainerdashboard) (πŸ“₯ 51K Β· ⏱️ 18.03.2024): ``` - conda install -c conda-forge fairlearn + conda install -c conda-forge explainerdashboard ```
-
Model Analysis (πŸ₯ˆ29 Β· ⭐ 1.2K) - Model analysis tools for TensorFlow. Apache-2 +
fairlearn (πŸ₯ˆ29 Β· ⭐ 1.9K) - A Python package to assess and improve fairness of machine.. MIT -- [GitHub](https://github.com/tensorflow/model-analysis) (πŸ‘¨β€πŸ’» 57 Β· πŸ”€ 270 Β· πŸ“¦ 2 Β· πŸ“‹ 88 - 37% open Β· ⏱️ 25.04.2024): +- [GitHub](https://github.com/fairlearn/fairlearn) (πŸ‘¨β€πŸ’» 83 Β· πŸ”€ 410 Β· πŸ“¦ 3 Β· πŸ“‹ 480 - 33% open Β· ⏱️ 03.09.2024): ``` - git clone https://github.com/tensorflow/model-analysis + git clone https://github.com/fairlearn/fairlearn ``` -- [PyPi](https://pypi.org/project/tensorflow-model-analysis) (πŸ“₯ 77K / month Β· πŸ“¦ 23 Β· ⏱️ 25.04.2024): +- [PyPi](https://pypi.org/project/fairlearn) (πŸ“₯ 180K / month Β· πŸ“¦ 55 Β· ⏱️ 19.12.2023): ``` - pip install tensorflow-model-analysis + pip install fairlearn + ``` +- [Conda](https://anaconda.org/conda-forge/fairlearn) (πŸ“₯ 36K Β· ⏱️ 20.12.2023): + ``` + conda install -c conda-forge fairlearn ```
dtreeviz (πŸ₯ˆ28 Β· ⭐ 2.9K) - A python library for decision tree visualization and model interpretation. MIT -- [GitHub](https://github.com/parrt/dtreeviz) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 330 Β· πŸ“¦ 1.2K Β· πŸ“‹ 200 - 32% open Β· ⏱️ 06.01.2024): +- [GitHub](https://github.com/parrt/dtreeviz) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 330 Β· πŸ“¦ 1.3K Β· πŸ“‹ 210 - 34% open Β· ⏱️ 29.08.2024): ``` git clone https://github.com/parrt/dtreeviz ``` -- [PyPi](https://pypi.org/project/dtreeviz) (πŸ“₯ 140K / month Β· πŸ“¦ 24 Β· ⏱️ 07.07.2022): +- [PyPi](https://pypi.org/project/dtreeviz) (πŸ“₯ 130K / month Β· πŸ“¦ 53 Β· ⏱️ 07.07.2022): ``` pip install dtreeviz ``` -- [Conda](https://anaconda.org/conda-forge/dtreeviz) (πŸ“₯ 71K Β· ⏱️ 13.07.2023): +- [Conda](https://anaconda.org/conda-forge/dtreeviz) (πŸ“₯ 81K Β· ⏱️ 13.07.2023): ``` conda install -c conda-forge dtreeviz ```
-
Fairness 360 (πŸ₯ˆ28 Β· ⭐ 2.3K) - A comprehensive set of fairness metrics for datasets and.. Apache-2 +
Fairness 360 (πŸ₯ˆ27 Β· ⭐ 2.4K) - A comprehensive set of fairness metrics for datasets and.. Apache-2 -- [GitHub](https://github.com/Trusted-AI/AIF360) (πŸ‘¨β€πŸ’» 73 Β· πŸ”€ 810 Β· πŸ“¦ 420 Β· πŸ“‹ 290 - 64% open Β· ⏱️ 08.04.2024): +- [GitHub](https://github.com/Trusted-AI/AIF360) (πŸ‘¨β€πŸ’» 73 Β· πŸ”€ 830 Β· πŸ“¦ 470 Β· πŸ“‹ 300 - 65% open Β· ⏱️ 05.07.2024): ``` git clone https://github.com/Trusted-AI/AIF360 ``` -- [PyPi](https://pypi.org/project/aif360) (πŸ“₯ 31K / month Β· πŸ“¦ 26 Β· ⏱️ 08.04.2024): +- [PyPi](https://pypi.org/project/aif360) (πŸ“₯ 33K / month Β· πŸ“¦ 32 Β· ⏱️ 08.04.2024): ``` pip install aif360 ``` -- [Conda](https://anaconda.org/conda-forge/aif360) (πŸ“₯ 11K Β· ⏱️ 09.04.2024): +- [Conda](https://anaconda.org/conda-forge/aif360) (πŸ“₯ 14K Β· ⏱️ 09.04.2024): ``` conda install -c conda-forge aif360 ```
-
imodels (πŸ₯ˆ28 Β· ⭐ 1.3K) - Interpretable ML package for concise, transparent, and accurate.. MIT +
responsible-ai-widgets (πŸ₯ˆ27 Β· ⭐ 1.3K) - Responsible AI Toolbox is a suite of tools providing.. MIT -- [GitHub](https://github.com/csinva/imodels) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 120 Β· πŸ“¦ 72 Β· πŸ“‹ 85 - 37% open Β· ⏱️ 26.05.2024): +- [GitHub](https://github.com/microsoft/responsible-ai-toolbox) (πŸ‘¨β€πŸ’» 43 Β· πŸ”€ 340 Β· πŸ“‹ 320 - 27% open Β· ⏱️ 07.08.2024): ``` - git clone https://github.com/csinva/imodels + git clone https://github.com/microsoft/responsible-ai-toolbox ``` -- [PyPi](https://pypi.org/project/imodels) (πŸ“₯ 65K / month Β· πŸ“¦ 9 Β· ⏱️ 23.05.2024): +- [PyPi](https://pypi.org/project/raiwidgets) (πŸ“₯ 10K / month Β· πŸ“¦ 6 Β· ⏱️ 08.07.2024): ``` - pip install imodels + pip install raiwidgets ```
-
yellowbrick (πŸ₯ˆ27 Β· ⭐ 4.2K Β· πŸ’€) - Visual analysis and diagnostic tools to facilitate.. Apache-2 +
LIT (πŸ₯ˆ26 Β· ⭐ 3.5K) - The Learning Interpretability Tool: Interactively analyze ML models to.. Apache-2 -- [GitHub](https://github.com/DistrictDataLabs/yellowbrick) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 550 Β· πŸ“‹ 700 - 13% open Β· ⏱️ 05.07.2023): +- [GitHub](https://github.com/PAIR-code/lit) (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 350 Β· πŸ“¦ 38 Β· πŸ“‹ 190 - 56% open Β· ⏱️ 26.06.2024): ``` - git clone https://github.com/DistrictDataLabs/yellowbrick + git clone https://github.com/PAIR-code/lit ``` -- [PyPi](https://pypi.org/project/yellowbrick) (πŸ“₯ 530K / month Β· πŸ“¦ 97 Β· ⏱️ 21.08.2022): +- [PyPi](https://pypi.org/project/lit-nlp) (πŸ“₯ 4.2K / month Β· πŸ“¦ 3 Β· ⏱️ 26.06.2024): ``` - pip install yellowbrick + pip install lit-nlp ``` -- [Conda](https://anaconda.org/conda-forge/yellowbrick) (πŸ“₯ 79K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/lit-nlp) (πŸ“₯ 86K Β· ⏱️ 16.06.2023): ``` - conda install -c conda-forge yellowbrick + conda install -c conda-forge lit-nlp ```
-
LIT (πŸ₯ˆ27 Β· ⭐ 3.4K) - The Learning Interpretability Tool: Interactively analyze ML models to.. Apache-2 +
imodels (πŸ₯ˆ26 Β· ⭐ 1.4K) - Interpretable ML package for concise, transparent, and accurate.. MIT -- [GitHub](https://github.com/PAIR-code/lit) (πŸ‘¨β€πŸ’» 36 Β· πŸ”€ 340 Β· πŸ“¦ 34 Β· πŸ“‹ 180 - 53% open Β· ⏱️ 17.04.2024): +- [GitHub](https://github.com/csinva/imodels) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 120 Β· πŸ“¦ 95 Β· πŸ“‹ 92 - 39% open Β· ⏱️ 16.08.2024): ``` - git clone https://github.com/PAIR-code/lit + git clone https://github.com/csinva/imodels ``` -- [PyPi](https://pypi.org/project/lit-nlp) (πŸ“₯ 3.4K / month Β· πŸ“¦ 3 Β· ⏱️ 09.04.2024): +- [PyPi](https://pypi.org/project/imodels) (πŸ“₯ 32K / month Β· πŸ“¦ 9 Β· ⏱️ 02.07.2024): ``` - pip install lit-nlp + pip install imodels + ``` +
+
Explainability 360 (πŸ₯‰25 Β· ⭐ 1.6K) - Interpretability and explainability of data and.. Apache-2 + +- [GitHub](https://github.com/Trusted-AI/AIX360) (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 300 Β· πŸ“¦ 98 Β· πŸ“‹ 85 - 63% open Β· ⏱️ 16.07.2024): + ``` -- [Conda](https://anaconda.org/conda-forge/lit-nlp) (πŸ“₯ 74K Β· ⏱️ 16.06.2023): + git clone https://github.com/Trusted-AI/AIX360 ``` - conda install -c conda-forge lit-nlp +- [PyPi](https://pypi.org/project/aix360) (πŸ“₯ 470 / month Β· πŸ“¦ 1 Β· ⏱️ 31.07.2023): + ``` + pip install aix360 ```
-
CausalNex (πŸ₯‰25 Β· ⭐ 2.2K) - A Python library that helps data scientists to infer.. Apache-2 +
iNNvestigate (πŸ₯‰25 Β· ⭐ 1.3K Β· πŸ’€) - A toolbox to iNNvestigate neural networks predictions!. BSD-2 -- [GitHub](https://github.com/mckinsey/causalnex) (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 250 Β· πŸ“¦ 110 Β· πŸ“‹ 140 - 16% open Β· ⏱️ 10.02.2024): +- [GitHub](https://github.com/albermax/innvestigate) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 240 Β· πŸ“₯ 130 Β· πŸ“¦ 140 Β· πŸ“‹ 260 - 21% open Β· ⏱️ 12.10.2023): ``` - git clone https://github.com/quantumblacklabs/causalnex + git clone https://github.com/albermax/innvestigate ``` -- [PyPi](https://pypi.org/project/causalnex) (πŸ“₯ 2.1K / month Β· πŸ“¦ 4 Β· ⏱️ 22.06.2023): +- [PyPi](https://pypi.org/project/innvestigate) (πŸ“₯ 710 / month Β· πŸ“¦ 2 Β· ⏱️ 12.10.2023): ``` - pip install causalnex + pip install innvestigate ```
-
aequitas (πŸ₯‰25 Β· ⭐ 640) - Bias Auditing & Fair ML Toolkit. MIT +
CausalNex (πŸ₯‰24 Β· ⭐ 2.2K Β· πŸ’€) - A Python library that helps data scientists to infer.. Apache-2 -- [GitHub](https://github.com/dssg/aequitas) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 110 Β· πŸ“¦ 160 Β· πŸ“‹ 100 - 54% open Β· ⏱️ 13.05.2024): +- [GitHub](https://github.com/mckinsey/causalnex) (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 260 Β· πŸ“¦ 130 Β· πŸ“‹ 140 - 16% open Β· ⏱️ 10.02.2024): ``` - git clone https://github.com/dssg/aequitas + git clone https://github.com/quantumblacklabs/causalnex ``` -- [PyPi](https://pypi.org/project/aequitas) (πŸ“₯ 22K / month Β· πŸ“¦ 7 Β· ⏱️ 30.01.2024): +- [PyPi](https://pypi.org/project/causalnex) (πŸ“₯ 3.2K / month Β· πŸ“¦ 4 Β· ⏱️ 22.06.2023): ``` - pip install aequitas + pip install causalnex ```
checklist (πŸ₯‰24 Β· ⭐ 2K Β· πŸ’€) - Beyond Accuracy: Behavioral Testing of NLP models with CheckList. MIT -- [GitHub](https://github.com/marcotcr/checklist) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 200 Β· πŸ“¦ 350 Β· πŸ“‹ 94 - 11% open Β· ⏱️ 26.09.2023): +- [GitHub](https://github.com/marcotcr/checklist) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 200 Β· πŸ“¦ 360 Β· πŸ“‹ 94 - 11% open Β· ⏱️ 26.09.2023): ``` git clone https://github.com/marcotcr/checklist ``` -- [PyPi](https://pypi.org/project/checklist) (πŸ“₯ 1.3K / month Β· πŸ“¦ 8 Β· ⏱️ 24.05.2021): +- [PyPi](https://pypi.org/project/checklist) (πŸ“₯ 1.1K / month Β· πŸ“¦ 8 Β· ⏱️ 24.05.2021): ``` pip install checklist ``` -- [Conda](https://anaconda.org/conda-forge/checklist) (πŸ“₯ 7.2K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/checklist) (πŸ“₯ 7.8K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge checklist ```
-
iNNvestigate (πŸ₯‰24 Β· ⭐ 1.2K Β· πŸ’€) - A toolbox to iNNvestigate neural networks predictions!. BSD-2 - -- [GitHub](https://github.com/albermax/innvestigate) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 240 Β· πŸ“₯ 100 Β· πŸ“¦ 130 Β· πŸ“‹ 260 - 21% open Β· ⏱️ 12.10.2023): - - ``` - git clone https://github.com/albermax/innvestigate - ``` -- [PyPi](https://pypi.org/project/innvestigate) (πŸ“₯ 800 / month Β· πŸ“¦ 2 Β· ⏱️ 12.10.2023): - ``` - pip install innvestigate - ``` -
-
Explainability 360 (πŸ₯‰23 Β· ⭐ 1.5K) - Interpretability and explainability of data and.. Apache-2 +
keract (πŸ₯‰24 Β· ⭐ 1K Β· πŸ’€) - Layers Outputs and Gradients in Keras. Made easy. MIT -- [GitHub](https://github.com/Trusted-AI/AIX360) (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 300 Β· πŸ“¦ 90 Β· πŸ“‹ 84 - 64% open Β· ⏱️ 05.03.2024): +- [GitHub](https://github.com/philipperemy/keract) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 180 Β· πŸ“¦ 220 Β· πŸ“‹ 89 - 3% open Β· ⏱️ 17.11.2023): ``` - git clone https://github.com/Trusted-AI/AIX360 + git clone https://github.com/philipperemy/keract ``` -- [PyPi](https://pypi.org/project/aix360) (πŸ“₯ 490 / month Β· πŸ“¦ 1 Β· ⏱️ 31.07.2023): +- [PyPi](https://pypi.org/project/keract) (πŸ“₯ 5.2K / month Β· πŸ“¦ 9 Β· ⏱️ 25.09.2022): ``` - pip install aix360 + pip install keract ```
-
keract (πŸ₯‰23 Β· ⭐ 1K Β· πŸ’€) - Layers Outputs and Gradients in Keras. Made easy. MIT +
aequitas (πŸ₯‰24 Β· ⭐ 660) - Bias Auditing & Fair ML Toolkit. MIT -- [GitHub](https://github.com/philipperemy/keract) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 180 Β· πŸ“¦ 210 Β· πŸ“‹ 89 - 3% open Β· ⏱️ 17.11.2023): +- [GitHub](https://github.com/dssg/aequitas) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 110 Β· πŸ“¦ 170 Β· πŸ“‹ 98 - 52% open Β· ⏱️ 28.08.2024): ``` - git clone https://github.com/philipperemy/keract + git clone https://github.com/dssg/aequitas ``` -- [PyPi](https://pypi.org/project/keract) (πŸ“₯ 5K / month Β· πŸ“¦ 9 Β· ⏱️ 25.09.2022): +- [PyPi](https://pypi.org/project/aequitas) (πŸ“₯ 21K / month Β· πŸ“¦ 8 Β· ⏱️ 30.01.2024): ``` - pip install keract + pip install aequitas ```
-
What-If Tool (πŸ₯‰22 Β· ⭐ 890) - Source code/webpage/demos for the What-If Tool. Apache-2 +
What-If Tool (πŸ₯‰22 Β· ⭐ 900 Β· πŸ’€) - Source code/webpage/demos for the What-If Tool. Apache-2 -- [GitHub](https://github.com/PAIR-code/what-if-tool) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 160 Β· πŸ“¦ 2 Β· πŸ“‹ 140 - 60% open Β· ⏱️ 01.02.2024): +- [GitHub](https://github.com/PAIR-code/what-if-tool) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 170 Β· πŸ“¦ 2 Β· πŸ“‹ 140 - 61% open Β· ⏱️ 01.02.2024): ``` git clone https://github.com/PAIR-code/what-if-tool ``` -- [PyPi](https://pypi.org/project/witwidget) (πŸ“₯ 3.4K / month Β· πŸ“¦ 6 Β· ⏱️ 12.10.2021): +- [PyPi](https://pypi.org/project/witwidget) (πŸ“₯ 5.6K / month Β· πŸ“¦ 6 Β· ⏱️ 12.10.2021): ``` pip install witwidget ``` -- [Conda](https://anaconda.org/conda-forge/tensorboard-plugin-wit) (πŸ“₯ 2.2M Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/tensorboard-plugin-wit) (πŸ“₯ 2.3M Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge tensorboard-plugin-wit ``` -- [npm](https://www.npmjs.com/package/wit-widget) (πŸ“₯ 1.1K / month Β· πŸ“¦ 3 Β· ⏱️ 12.10.2021): +- [npm](https://www.npmjs.com/package/wit-widget) (πŸ“₯ 720 / month Β· πŸ“¦ 3 Β· ⏱️ 12.10.2021): ``` npm install wit-widget ```
-
ecco (πŸ₯‰21 Β· ⭐ 1.9K Β· πŸ’€) - Explain, analyze, and visualize NLP language models. Ecco creates.. BSD-3 +
ecco (πŸ₯‰21 Β· ⭐ 2K) - Explain, analyze, and visualize NLP language models. Ecco creates.. BSD-3 -- [GitHub](https://github.com/jalammar/ecco) (πŸ‘¨β€πŸ’» 11 Β· πŸ”€ 160 Β· πŸ“₯ 94 Β· πŸ“¦ 28 Β· πŸ“‹ 63 - 50% open Β· ⏱️ 10.08.2023): +- [GitHub](https://github.com/jalammar/ecco) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 160 Β· πŸ“₯ 100 Β· πŸ“¦ 29 Β· πŸ“‹ 64 - 51% open Β· ⏱️ 15.08.2024): ``` git clone https://github.com/jalammar/ecco ``` -- [PyPi](https://pypi.org/project/ecco) (πŸ“₯ 300 / month Β· πŸ“¦ 1 Β· ⏱️ 09.01.2022): +- [PyPi](https://pypi.org/project/ecco) (πŸ“₯ 350 / month Β· πŸ“¦ 1 Β· ⏱️ 09.01.2022): ``` pip install ecco ``` -- [Conda](https://anaconda.org/conda-forge/ecco) (πŸ“₯ 4.7K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/ecco) (πŸ“₯ 5.3K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge ecco ```
-
DiCE (πŸ₯‰21 Β· ⭐ 1.3K) - Generate Diverse Counterfactual Explanations for any machine.. MIT +
DiCE (πŸ₯‰20 Β· ⭐ 1.3K) - Generate Diverse Counterfactual Explanations for any machine.. MIT - [GitHub](https://github.com/interpretml/DiCE) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 180 Β· πŸ“‹ 170 - 45% open Β· ⏱️ 17.04.2024): ``` git clone https://github.com/interpretml/DiCE ``` -- [PyPi](https://pypi.org/project/dice-ml) (πŸ“₯ 55K / month Β· πŸ“¦ 6 Β· ⏱️ 27.10.2023): +- [PyPi](https://pypi.org/project/dice-ml) (πŸ“₯ 42K / month Β· πŸ“¦ 6 Β· ⏱️ 27.10.2023): ``` pip install dice-ml ```
-
model-card-toolkit (πŸ₯‰21 Β· ⭐ 400 Β· πŸ’€) - A toolkit that streamlines and automates the.. Apache-2 +
fairness-indicators (πŸ₯‰20 Β· ⭐ 340) - Tensorflows Fairness Evaluation and Visualization.. Apache-2 -- [GitHub](https://github.com/tensorflow/model-card-toolkit) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 83 Β· πŸ“₯ 18 Β· πŸ“¦ 23 Β· πŸ“‹ 33 - 30% open Β· ⏱️ 26.07.2023): +- [GitHub](https://github.com/tensorflow/fairness-indicators) (πŸ‘¨β€πŸ’» 36 Β· πŸ”€ 78 Β· πŸ“‹ 36 - 72% open Β· ⏱️ 26.04.2024): ``` - git clone https://github.com/tensorflow/model-card-toolkit + git clone https://github.com/tensorflow/fairness-indicators ``` -- [PyPi](https://pypi.org/project/model-card-toolkit) (πŸ“₯ 1.2K / month Β· πŸ“¦ 1 Β· ⏱️ 28.04.2022): +- [PyPi](https://pypi.org/project/fairness-indicators) (πŸ“₯ 1.1K / month Β· ⏱️ 26.04.2024): ``` - pip install model-card-toolkit + pip install fairness-indicators ```
-
LOFO (πŸ₯‰19 Β· ⭐ 810) - Leave One Feature Out Importance. MIT +
LOFO (πŸ₯‰18 Β· ⭐ 810 Β· πŸ’€) - Leave One Feature Out Importance. MIT -- [GitHub](https://github.com/aerdem4/lofo-importance) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 82 Β· πŸ“¦ 28 Β· πŸ“‹ 26 - 11% open Β· ⏱️ 16.01.2024): +- [GitHub](https://github.com/aerdem4/lofo-importance) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 84 Β· πŸ“¦ 33 Β· πŸ“‹ 27 - 11% open Β· ⏱️ 16.01.2024): ``` git clone https://github.com/aerdem4/lofo-importance ``` -- [PyPi](https://pypi.org/project/lofo-importance) (πŸ“₯ 4.2K / month Β· πŸ“¦ 4 Β· ⏱️ 16.01.2024): +- [PyPi](https://pypi.org/project/lofo-importance) (πŸ“₯ 3.2K / month Β· πŸ“¦ 4 Β· ⏱️ 16.01.2024): ``` pip install lofo-importance ```
-
fairness-indicators (πŸ₯‰19 Β· ⭐ 330) - Tensorflows Fairness Evaluation and Visualization.. Apache-2 - -- [GitHub](https://github.com/tensorflow/fairness-indicators) (πŸ‘¨β€πŸ’» 36 Β· πŸ”€ 77 Β· πŸ“‹ 35 - 74% open Β· ⏱️ 26.04.2024): - - ``` - git clone https://github.com/tensorflow/fairness-indicators - ``` -- [PyPi](https://pypi.org/project/fairness-indicators) (πŸ“₯ 780 / month Β· ⏱️ 26.04.2024): - ``` - pip install fairness-indicators - ``` -
-
FlashTorch (πŸ₯‰15 Β· ⭐ 720 Β· πŸ’€) - Visualization toolkit for neural networks in PyTorch! Demo --. MIT +
FlashTorch (πŸ₯‰15 Β· ⭐ 730 Β· πŸ’€) - Visualization toolkit for neural networks in PyTorch! Demo --. MIT -- [GitHub](https://github.com/MisaOgura/flashtorch) (πŸ‘¨β€πŸ’» 2 Β· πŸ”€ 87 Β· πŸ“¦ 17 Β· πŸ“‹ 32 - 31% open Β· ⏱️ 21.09.2023): +- [GitHub](https://github.com/MisaOgura/flashtorch) (πŸ‘¨β€πŸ’» 2 Β· πŸ”€ 85 Β· πŸ“¦ 22 Β· πŸ“‹ 32 - 31% open Β· ⏱️ 21.09.2023): ``` git clone https://github.com/MisaOgura/flashtorch ``` -- [PyPi](https://pypi.org/project/flashtorch) (πŸ“₯ 130 / month Β· ⏱️ 29.05.2020): +- [PyPi](https://pypi.org/project/flashtorch) (πŸ“₯ 110 / month Β· ⏱️ 29.05.2020): ``` pip install flashtorch ```
-
ExplainX.ai (πŸ₯‰15 Β· ⭐ 400 Β· πŸ“‰) - Explainable AI framework for data scientists. Explain & debug any.. MIT +
ExplainX.ai (πŸ₯‰15 Β· ⭐ 400) - Explainable AI framework for data scientists. Explain & debug any.. MIT -- [GitHub](https://github.com/explainX/explainx) (πŸ‘¨β€πŸ’» 5 Β· πŸ”€ 53 Β· πŸ“₯ 16 Β· πŸ“‹ 39 - 25% open Β· ⏱️ 15.01.2024): +- [GitHub](https://github.com/explainX/explainx) (πŸ‘¨β€πŸ’» 5 Β· πŸ”€ 52 Β· πŸ“₯ 17 Β· πŸ“‹ 39 - 25% open Β· ⏱️ 21.08.2024): ``` git clone https://github.com/explainX/explainx ``` -- [PyPi](https://pypi.org/project/explainx) (πŸ“₯ 1.1K / month Β· ⏱️ 04.02.2021): +- [PyPi](https://pypi.org/project/explainx) (πŸ“₯ 210 / month Β· ⏱️ 04.02.2021): ``` pip install explainx ```
-
interpret-text (πŸ₯‰14 Β· ⭐ 400) - A library that incorporates state-of-the-art explainers for.. MIT +
interpret-text (πŸ₯‰14 Β· ⭐ 410 Β· πŸ’€) - A library that incorporates state-of-the-art explainers.. MIT -- [GitHub](https://github.com/interpretml/interpret-text) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 67 Β· πŸ“‹ 100 - 84% open Β· ⏱️ 05.02.2024): +- [GitHub](https://github.com/interpretml/interpret-text) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 68 Β· πŸ“‹ 100 - 84% open Β· ⏱️ 05.02.2024): ``` git clone https://github.com/interpretml/interpret-text ``` -- [PyPi](https://pypi.org/project/interpret-text) (πŸ“₯ 97 / month Β· ⏱️ 07.12.2021): +- [PyPi](https://pypi.org/project/interpret-text) (πŸ“₯ 140 / month Β· ⏱️ 07.12.2021): ``` pip install interpret-text ```
-
Show 21 hidden projects... +
Show 23 hidden projects... - Lime (πŸ₯‡33 Β· ⭐ 11K Β· πŸ’€) - Lime: Explaining the predictions of any machine learning classifier. BSD-2 -- Deep Checks (πŸ₯ˆ29 Β· ⭐ 3.4K) - Deepchecks: Tests for Continuous Validation of ML Models &.. ❗️AGPL-3.0 +- Deep Checks (πŸ₯ˆ28 Β· ⭐ 3.6K Β· πŸ’€) - Deepchecks: Tests for Continuous Validation of ML Models.. ❗️AGPL-3.0 - scikit-plot (πŸ₯ˆ28 Β· ⭐ 2.4K Β· πŸ’€) - An intuitive library to add plotting functionality to.. MIT -- Alibi (πŸ₯ˆ28 Β· ⭐ 2.3K) - Algorithms for explaining machine learning models. ❗️Intel -- DALEX (πŸ₯ˆ27 Β· ⭐ 1.3K) - moDel Agnostic Language for Exploration and eXplanation. ❗️GPL-3.0 -- eli5 (πŸ₯‰26 Β· ⭐ 2.7K Β· πŸ’€) - A library for debugging/inspecting machine learning classifiers and.. MIT +- Alibi (πŸ₯ˆ28 Β· ⭐ 2.4K) - Algorithms for explaining machine learning models. ❗️Intel +- yellowbrick (πŸ₯ˆ26 Β· ⭐ 4.3K Β· πŸ’€) - Visual analysis and diagnostic tools to facilitate.. Apache-2 +- eli5 (πŸ₯ˆ26 Β· ⭐ 2.8K Β· πŸ’€) - A library for debugging/inspecting machine learning classifiers and.. MIT +- DALEX (πŸ₯ˆ26 Β· ⭐ 1.4K) - moDel Agnostic Language for Exploration and eXplanation. ❗️GPL-3.0 - Lucid (πŸ₯‰25 Β· ⭐ 4.6K Β· πŸ’€) - A collection of infrastructure and tools for research in.. Apache-2 - keras-vis (πŸ₯‰25 Β· ⭐ 3K Β· πŸ’€) - Neural network visualization toolkit for keras. MIT -- tf-explain (πŸ₯‰23 Β· ⭐ 1K Β· πŸ’€) - Interpretability Methods for tf.keras models with Tensorflow.. MIT -- random-forest-importances (πŸ₯‰22 Β· ⭐ 590 Β· πŸ’€) - Code to compute permutation and drop-column.. MIT -- deeplift (πŸ₯‰21 Β· ⭐ 800 Β· πŸ’€) - Public facing deeplift repo. MIT +- tf-explain (πŸ₯‰22 Β· ⭐ 1K Β· πŸ’€) - Interpretability Methods for tf.keras models with Tensorflow.. MIT +- random-forest-importances (πŸ₯‰22 Β· ⭐ 600 Β· πŸ’€) - Code to compute permutation and drop-column.. MIT +- deeplift (πŸ₯‰21 Β· ⭐ 820 Β· πŸ’€) - Public facing deeplift repo. MIT - TreeInterpreter (πŸ₯‰21 Β· ⭐ 740 Β· πŸ’€) - Package for interpreting scikit-learns decision tree.. BSD-3 -- Quantus (πŸ₯‰21 Β· ⭐ 510) - Quantus is an eXplainable AI toolkit for responsible evaluation of.. ❗️GPL-3.0 -- tcav (πŸ₯‰20 Β· ⭐ 620 Β· πŸ’€) - Code for the TCAV ML interpretability project. Apache-2 +- tcav (πŸ₯‰20 Β· ⭐ 630 Β· πŸ’€) - Code for the TCAV ML interpretability project. Apache-2 +- model-card-toolkit (πŸ₯‰19 Β· ⭐ 420 Β· πŸ’€) - A toolkit that streamlines and automates the.. Apache-2 - XAI (πŸ₯‰18 Β· ⭐ 1.1K Β· πŸ’€) - XAI - An eXplainability toolbox for machine learning. MIT -- sklearn-evaluation (πŸ₯‰18 Β· ⭐ 430 Β· πŸ’€) - Machine learning model evaluation made easy: plots,.. MIT -- Anchor (πŸ₯‰16 Β· ⭐ 790 Β· πŸ’€) - Code for High-Precision Model-Agnostic Explanations paper. BSD-2 +- Quantus (πŸ₯‰18 Β· ⭐ 520) - Quantus is an eXplainable AI toolkit for responsible evaluation of.. ❗️GPL-3.0 +- sklearn-evaluation (πŸ₯‰17 Β· ⭐ 430 Β· πŸ’€) - Machine learning model evaluation made easy: plots,.. MIT +- Anchor (πŸ₯‰15 Β· ⭐ 790 Β· πŸ’€) - Code for High-Precision Model-Agnostic Explanations paper. BSD-2 - Skater (πŸ₯‰14 Β· ⭐ 1.1K Β· πŸ’€) - Python Library for Model Interpretation/Explanations. ❗️UPL-1.0 - Attribution Priors (πŸ₯‰12 Β· ⭐ 120 Β· πŸ’€) - Tools for training explainable models using.. MIT - contextual-ai (πŸ₯‰12 Β· ⭐ 85 Β· πŸ’€) - Contextual AI adds explainability to different stages of.. Apache-2 -- bias-detector (πŸ₯‰12 Β· ⭐ 44) - Bias Detector is a python package for detecting bias in machine.. MIT +- bias-detector (πŸ₯‰12 Β· ⭐ 44 Β· πŸ’€) - Bias Detector is a python package for detecting bias in machine.. MIT

@@ -6510,137 +6412,141 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarity Search._ -πŸ”— ANN Benchmarks ( ⭐ 4.7K) - Benchmarks of approximate nearest neighbor libraries in Python. +πŸ”— ANN Benchmarks ( ⭐ 4.8K) - Benchmarks of approximate nearest neighbor libraries in Python. -
Milvus (πŸ₯‡41 Β· ⭐ 28K) - A cloud-native vector database, storage for next generation AI.. Apache-2 +
Faiss (πŸ₯‡41 Β· ⭐ 30K) - A library for efficient similarity search and clustering of dense vectors. MIT -- [GitHub](https://github.com/milvus-io/milvus) (πŸ‘¨β€πŸ’» 280 Β· πŸ”€ 2.7K Β· πŸ“₯ 230K Β· πŸ“‹ 11K - 7% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/facebookresearch/faiss) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 3.5K Β· πŸ“¦ 3.9K Β· πŸ“‹ 2.5K - 9% open Β· ⏱️ 05.09.2024): ``` - git clone https://github.com/milvus-io/milvus + git clone https://github.com/facebookresearch/faiss ``` -- [PyPi](https://pypi.org/project/pymilvus) (πŸ“₯ 550K / month Β· πŸ“¦ 120 Β· ⏱️ 17.05.2024): +- [PyPi](https://pypi.org/project/pymilvus) (πŸ“₯ 790K / month Β· πŸ“¦ 160 Β· ⏱️ 30.08.2024): ``` pip install pymilvus ``` -- [Docker Hub](https://hub.docker.com/r/milvusdb/milvus) (πŸ“₯ 17M Β· ⭐ 45 Β· ⏱️ 06.06.2024): +- [Conda](https://anaconda.org/conda-forge/faiss) (πŸ“₯ 1.6M Β· ⏱️ 09.08.2024): ``` - docker pull milvusdb/milvus + conda install -c conda-forge faiss ```
-
Faiss (πŸ₯‡40 Β· ⭐ 29K) - A library for efficient similarity search and clustering of dense vectors. MIT +
Milvus (πŸ₯‡41 Β· ⭐ 29K) - A cloud-native vector database, storage for next generation AI.. Apache-2 -- [GitHub](https://github.com/facebookresearch/faiss) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 3.4K Β· πŸ“¦ 3.7K Β· πŸ“‹ 2.4K - 18% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/milvus-io/milvus) (πŸ‘¨β€πŸ’» 290 Β· πŸ”€ 2.8K Β· πŸ“₯ 260K Β· πŸ“‹ 12K - 5% open Β· ⏱️ 05.09.2024): ``` - git clone https://github.com/facebookresearch/faiss + git clone https://github.com/milvus-io/milvus ``` -- [PyPi](https://pypi.org/project/pymilvus) (πŸ“₯ 550K / month Β· πŸ“¦ 120 Β· ⏱️ 17.05.2024): +- [PyPi](https://pypi.org/project/pymilvus) (πŸ“₯ 790K / month Β· πŸ“¦ 160 Β· ⏱️ 30.08.2024): ``` pip install pymilvus ``` -- [Conda](https://anaconda.org/conda-forge/faiss) (πŸ“₯ 1.2M Β· ⏱️ 16.06.2023): +- [Docker Hub](https://hub.docker.com/r/milvusdb/milvus) (πŸ“₯ 66M Β· ⭐ 59 Β· ⏱️ 05.09.2024): ``` - conda install -c conda-forge faiss + docker pull milvusdb/milvus ```
-
Annoy (πŸ₯ˆ35 Β· ⭐ 13K Β· πŸ’€) - Approximate Nearest Neighbors in C++/Python optimized for memory.. Apache-2 +
Annoy (πŸ₯ˆ35 Β· ⭐ 13K) - Approximate Nearest Neighbors in C++/Python optimized for memory usage.. Apache-2 -- [GitHub](https://github.com/spotify/annoy) (πŸ‘¨β€πŸ’» 88 Β· πŸ”€ 1.1K Β· πŸ“¦ 3.9K Β· πŸ“‹ 400 - 14% open Β· ⏱️ 20.08.2023): +- [GitHub](https://github.com/spotify/annoy) (πŸ‘¨β€πŸ’» 89 Β· πŸ”€ 1.1K Β· πŸ“¦ 4.2K Β· πŸ“‹ 400 - 14% open Β· ⏱️ 29.07.2024): ``` git clone https://github.com/spotify/annoy ``` -- [PyPi](https://pypi.org/project/annoy) (πŸ“₯ 1.1M / month Β· πŸ“¦ 190 Β· ⏱️ 14.06.2023): +- [PyPi](https://pypi.org/project/annoy) (πŸ“₯ 1.1M / month Β· πŸ“¦ 200 Β· ⏱️ 14.06.2023): ``` pip install annoy ``` -- [Conda](https://anaconda.org/conda-forge/python-annoy) (πŸ“₯ 420K Β· ⏱️ 02.05.2024): +- [Conda](https://anaconda.org/conda-forge/python-annoy) (πŸ“₯ 500K Β· ⏱️ 05.09.2024): ``` conda install -c conda-forge python-annoy ```
-
hnswlib (πŸ₯ˆ32 Β· ⭐ 4.1K) - Header-only C++/python library for fast approximate nearest neighbors. Apache-2 +
hnswlib (πŸ₯ˆ31 Β· ⭐ 4.2K) - Header-only C++/python library for fast approximate nearest neighbors. Apache-2 -- [GitHub](https://github.com/nmslib/hnswlib) (πŸ‘¨β€πŸ’» 72 Β· πŸ”€ 590 Β· πŸ“¦ 6.5K Β· πŸ“‹ 370 - 57% open Β· ⏱️ 03.12.2023): +- [GitHub](https://github.com/nmslib/hnswlib) (πŸ‘¨β€πŸ’» 72 Β· πŸ”€ 620 Β· πŸ“¦ 6.9K Β· πŸ“‹ 380 - 57% open Β· ⏱️ 17.06.2024): ``` git clone https://github.com/nmslib/hnswlib ``` -- [PyPi](https://pypi.org/project/hnswlib) (πŸ“₯ 850K / month Β· πŸ“¦ 120 Β· ⏱️ 03.12.2023): +- [PyPi](https://pypi.org/project/hnswlib) (πŸ“₯ 860K / month Β· πŸ“¦ 130 Β· ⏱️ 03.12.2023): ``` pip install hnswlib ``` -- [Conda](https://anaconda.org/conda-forge/hnswlib) (πŸ“₯ 170K Β· ⏱️ 27.09.2023): +- [Conda](https://anaconda.org/conda-forge/hnswlib) (πŸ“₯ 220K Β· ⏱️ 27.09.2023): ``` conda install -c conda-forge hnswlib ```
-
USearch (πŸ₯‰30 Β· ⭐ 1.8K) - Fast Open-Source Search & Clustering engine for Vectors & Strings in.. Apache-2 +
NMSLIB (πŸ₯ˆ30 Β· ⭐ 3.4K) - Non-Metric Space Library (NMSLIB): An efficient similarity search.. Apache-2 + +- [GitHub](https://github.com/nmslib/nmslib) (πŸ‘¨β€πŸ’» 48 Β· πŸ”€ 450 Β· πŸ“¦ 1.2K Β· πŸ“‹ 440 - 20% open Β· ⏱️ 23.06.2024): + + ``` + git clone https://github.com/nmslib/nmslib + ``` +- [PyPi](https://pypi.org/project/nmslib) (πŸ“₯ 180K / month Β· πŸ“¦ 63 Β· ⏱️ 03.02.2021): + ``` + pip install nmslib + ``` +- [Conda](https://anaconda.org/conda-forge/nmslib) (πŸ“₯ 140K Β· ⏱️ 26.09.2023): + ``` + conda install -c conda-forge nmslib + ``` +
+
USearch (πŸ₯ˆ30 Β· ⭐ 2.1K) - Fast Open-Source Search & Clustering engine for Vectors & Strings in.. Apache-2 -- [GitHub](https://github.com/unum-cloud/usearch) (πŸ‘¨β€πŸ’» 36 Β· πŸ”€ 100 Β· πŸ“₯ 1.3K Β· πŸ“¦ 80 Β· πŸ“‹ 120 - 34% open Β· ⏱️ 29.04.2024): +- [GitHub](https://github.com/unum-cloud/usearch) (πŸ‘¨β€πŸ’» 52 Β· πŸ”€ 120 Β· πŸ“₯ 18K Β· πŸ“¦ 110 Β· πŸ“‹ 150 - 31% open Β· ⏱️ 28.08.2024): ``` git clone https://github.com/unum-cloud/usearch ``` -- [PyPi](https://pypi.org/project/usearch) (πŸ“₯ 63K / month Β· πŸ“¦ 6 Β· ⏱️ 29.04.2024): +- [PyPi](https://pypi.org/project/usearch) (πŸ“₯ 100K / month Β· πŸ“¦ 14 Β· ⏱️ 28.08.2024): ``` pip install usearch ``` -- [npm](https://www.npmjs.com/package/usearch) (πŸ“₯ 6K / month Β· πŸ“¦ 14 Β· ⏱️ 10.04.2024): +- [npm](https://www.npmjs.com/package/usearch) (πŸ“₯ 8.3K / month Β· πŸ“¦ 14 Β· ⏱️ 28.08.2024): ``` npm install usearch ``` -- [Docker Hub](https://hub.docker.com/r/unum/usearch) (πŸ“₯ 75 Β· ⭐ 1 Β· ⏱️ 29.04.2024): +- [Docker Hub](https://hub.docker.com/r/unum/usearch) (πŸ“₯ 110 Β· ⭐ 1 Β· ⏱️ 28.08.2024): ``` docker pull unum/usearch ```
-
PyNNDescent (πŸ₯‰29 Β· ⭐ 860) - A Python nearest neighbor descent for approximate nearest neighbors. BSD-2 +
PyNNDescent (πŸ₯‰28 Β· ⭐ 880) - A Python nearest neighbor descent for approximate nearest neighbors. BSD-2 -- [GitHub](https://github.com/lmcinnes/pynndescent) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 100 Β· πŸ“¦ 6.6K Β· πŸ“‹ 140 - 52% open Β· ⏱️ 15.05.2024): +- [GitHub](https://github.com/lmcinnes/pynndescent) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 100 Β· πŸ“¦ 7.6K Β· πŸ“‹ 140 - 52% open Β· ⏱️ 17.06.2024): ``` git clone https://github.com/lmcinnes/pynndescent ``` -- [PyPi](https://pypi.org/project/pynndescent) (πŸ“₯ 1.5M / month Β· πŸ“¦ 140 Β· ⏱️ 29.03.2024): +- [PyPi](https://pypi.org/project/pynndescent) (πŸ“₯ 1.7M / month Β· πŸ“¦ 160 Β· ⏱️ 17.06.2024): ``` pip install pynndescent ``` -- [Conda](https://anaconda.org/conda-forge/pynndescent) (πŸ“₯ 1.9M Β· ⏱️ 29.03.2024): +- [Conda](https://anaconda.org/conda-forge/pynndescent) (πŸ“₯ 2M Β· ⏱️ 17.06.2024): ``` conda install -c conda-forge pynndescent ```
NGT (πŸ₯‰22 Β· ⭐ 1.2K) - Nearest Neighbor Search with Neighborhood Graph and Tree for High-.. Apache-2 -- [GitHub](https://github.com/yahoojapan/NGT) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 110 Β· πŸ“‹ 130 - 12% open Β· ⏱️ 13.05.2024): +- [GitHub](https://github.com/yahoojapan/NGT) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 110 Β· πŸ“‹ 140 - 12% open Β· ⏱️ 26.07.2024): ``` git clone https://github.com/yahoojapan/NGT ``` -- [PyPi](https://pypi.org/project/ngt) (πŸ“₯ 5.1K / month Β· πŸ“¦ 8 Β· ⏱️ 06.12.2023): +- [PyPi](https://pypi.org/project/ngt) (πŸ“₯ 2.9K / month Β· πŸ“¦ 8 Β· ⏱️ 06.12.2023): ``` pip install ngt ```
-
N2 (πŸ₯‰19 Β· ⭐ 570 Β· πŸ’€) - TOROS N2 - lightweight approximate Nearest Neighbor library which runs.. Apache-2 - -- [GitHub](https://github.com/kakao/n2) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 75 Β· πŸ“¦ 31 Β· πŸ“‹ 35 - 37% open Β· ⏱️ 27.06.2023): - - ``` - git clone https://github.com/kakao/n2 - ``` -- [PyPi](https://pypi.org/project/n2) (πŸ“₯ 230 / month Β· πŸ“¦ 4 Β· ⏱️ 16.10.2020): - ``` - pip install n2 - ``` -
Show 4 hidden projects... -- NMSLIB (πŸ₯ˆ31 Β· ⭐ 3.3K Β· πŸ’€) - Non-Metric Space Library (NMSLIB): An efficient similarity search.. Apache-2 -- Magnitude (πŸ₯‰22 Β· ⭐ 1.6K Β· πŸ’€) - A fast, efficient universal vector embedding utility package. MIT +- Magnitude (πŸ₯‰20 Β· ⭐ 1.6K Β· πŸ’€) - A fast, efficient universal vector embedding utility package. MIT - NearPy (πŸ₯‰20 Β· ⭐ 760 Β· πŸ’€) - Python framework for fast (approximated) nearest neighbour search in.. MIT +- N2 (πŸ₯‰20 Β· ⭐ 560 Β· πŸ’€) - TOROS N2 - lightweight approximate Nearest Neighbor library which runs.. Apache-2 - PySparNN (πŸ₯‰11 Β· ⭐ 920 Β· πŸ’€) - Approximate Nearest Neighbor Search for Sparse Data in Python!. BSD-3

@@ -6651,262 +6557,277 @@ _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarit _Libraries providing capabilities for probabilistic programming/reasoning, bayesian inference, gaussian processes, or statistics._ -
PyMC3 (πŸ₯‡41 Β· ⭐ 8.2K) - Bayesian Modeling and Probabilistic Programming in Python. Apache-2 +
PyMC3 (πŸ₯‡41 Β· ⭐ 8.6K) - Bayesian Modeling and Probabilistic Programming in Python. Apache-2 -- [GitHub](https://github.com/pymc-devs/pymc) (πŸ‘¨β€πŸ’» 490 Β· πŸ”€ 1.9K Β· πŸ“₯ 1.9K Β· πŸ“¦ 3.4K Β· πŸ“‹ 3.3K - 8% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/pymc-devs/pymc) (πŸ‘¨β€πŸ’» 500 Β· πŸ”€ 2K Β· πŸ“₯ 1.9K Β· πŸ“¦ 4K Β· πŸ“‹ 3.4K - 8% open Β· ⏱️ 03.09.2024): ``` git clone https://github.com/pymc-devs/pymc ``` -- [PyPi](https://pypi.org/project/pymc3) (πŸ“₯ 900K / month Β· πŸ“¦ 190 Β· ⏱️ 31.05.2024): +- [PyPi](https://pypi.org/project/pymc3) (πŸ“₯ 260K / month Β· πŸ“¦ 190 Β· ⏱️ 31.05.2024): ``` pip install pymc3 ``` -- [Conda](https://anaconda.org/conda-forge/pymc3) (πŸ“₯ 570K Β· ⏱️ 02.06.2024): +- [Conda](https://anaconda.org/conda-forge/pymc3) (πŸ“₯ 600K Β· ⏱️ 02.06.2024): ``` conda install -c conda-forge pymc3 ```
-
tensorflow-probability (πŸ₯‡38 Β· ⭐ 4.1K) - Probabilistic reasoning and statistical analysis in.. Apache-2 +
tensorflow-probability (πŸ₯‡35 Β· ⭐ 4.2K Β· πŸ“‰) - Probabilistic reasoning and statistical analysis in.. Apache-2 -- [GitHub](https://github.com/tensorflow/probability) (πŸ‘¨β€πŸ’» 490 Β· πŸ”€ 1.1K Β· πŸ“‹ 1.4K - 47% open Β· ⏱️ 24.05.2024): +- [GitHub](https://github.com/tensorflow/probability) (πŸ‘¨β€πŸ’» 500 Β· πŸ”€ 1.1K Β· πŸ“¦ 1 Β· πŸ“‹ 1.4K - 47% open Β· ⏱️ 23.08.2024): ``` git clone https://github.com/tensorflow/probability ``` -- [PyPi](https://pypi.org/project/tensorflow-probability) (πŸ“₯ 3.3M / month Β· πŸ“¦ 570 Β· ⏱️ 12.03.2024): +- [PyPi](https://pypi.org/project/tensorflow-probability) (πŸ“₯ 1.5M / month Β· πŸ“¦ 610 Β· ⏱️ 12.03.2024): ``` pip install tensorflow-probability ``` -- [Conda](https://anaconda.org/conda-forge/tensorflow-probability) (πŸ“₯ 130K Β· ⏱️ 27.05.2024): +- [Conda](https://anaconda.org/conda-forge/tensorflow-probability) (πŸ“₯ 140K Β· ⏱️ 27.05.2024): ``` conda install -c conda-forge tensorflow-probability ```
-
Pyro (πŸ₯‡34 Β· ⭐ 8.4K) - Deep universal probabilistic programming with Python and PyTorch. Apache-2 +
Pyro (πŸ₯‡34 Β· ⭐ 8.5K) - Deep universal probabilistic programming with Python and PyTorch. Apache-2 -- [GitHub](https://github.com/pyro-ppl/pyro) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 990 Β· πŸ“‹ 1.1K - 23% open Β· ⏱️ 01.06.2024): +- [GitHub](https://github.com/pyro-ppl/pyro) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 980 Β· πŸ“‹ 1.1K - 23% open Β· ⏱️ 04.08.2024): ``` git clone https://github.com/pyro-ppl/pyro ``` -- [PyPi](https://pypi.org/project/pyro-ppl) (πŸ“₯ 290K / month Β· πŸ“¦ 180 Β· ⏱️ 02.06.2024): +- [PyPi](https://pypi.org/project/pyro-ppl) (πŸ“₯ 320K / month Β· πŸ“¦ 190 Β· ⏱️ 02.06.2024): ``` pip install pyro-ppl ``` -- [Conda](https://anaconda.org/conda-forge/pyro-ppl) (πŸ“₯ 170K Β· ⏱️ 03.06.2024): +- [Conda](https://anaconda.org/conda-forge/pyro-ppl) (πŸ“₯ 190K Β· ⏱️ 03.06.2024): ``` conda install -c conda-forge pyro-ppl ```
-
pgmpy (πŸ₯ˆ32 Β· ⭐ 2.6K) - Python Library for learning (Structure and Parameter), inference.. MIT +
pgmpy (πŸ₯ˆ33 Β· ⭐ 2.7K) - Python Library for learning (Structure and Parameter), inference.. MIT -- [GitHub](https://github.com/pgmpy/pgmpy) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 690 Β· πŸ“₯ 360 Β· πŸ“¦ 1K Β· πŸ“‹ 900 - 30% open Β· ⏱️ 01.06.2024): +- [GitHub](https://github.com/pgmpy/pgmpy) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 700 Β· πŸ“₯ 500 Β· πŸ“¦ 1.1K Β· πŸ“‹ 920 - 31% open Β· ⏱️ 04.09.2024): ``` git clone https://github.com/pgmpy/pgmpy ``` -- [PyPi](https://pypi.org/project/pgmpy) (πŸ“₯ 52K / month Β· πŸ“¦ 43 Β· ⏱️ 08.03.2024): +- [PyPi](https://pypi.org/project/pgmpy) (πŸ“₯ 74K / month Β· πŸ“¦ 52 Β· ⏱️ 09.08.2024): ``` pip install pgmpy ```
-
GPyTorch (πŸ₯ˆ31 Β· ⭐ 3.4K) - A highly efficient implementation of Gaussian Processes in PyTorch. MIT +
GPyTorch (πŸ₯ˆ32 Β· ⭐ 3.5K) - A highly efficient implementation of Gaussian Processes in PyTorch. MIT -- [GitHub](https://github.com/cornellius-gp/gpytorch) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 540 Β· πŸ“¦ 2.1K Β· πŸ“‹ 1.3K - 26% open Β· ⏱️ 22.04.2024): +- [GitHub](https://github.com/cornellius-gp/gpytorch) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 550 Β· πŸ“¦ 2.3K Β· πŸ“‹ 1.3K - 27% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/cornellius-gp/gpytorch ``` -- [PyPi](https://pypi.org/project/gpytorch) (πŸ“₯ 240K / month Β· πŸ“¦ 150 Β· ⏱️ 02.06.2023): +- [PyPi](https://pypi.org/project/gpytorch) (πŸ“₯ 240K / month Β· πŸ“¦ 170 Β· ⏱️ 27.06.2024): ``` pip install gpytorch ``` -- [Conda](https://anaconda.org/conda-forge/gpytorch) (πŸ“₯ 160K Β· ⏱️ 11.08.2023): +- [Conda](https://anaconda.org/conda-forge/gpytorch) (πŸ“₯ 170K Β· ⏱️ 28.06.2024): ``` conda install -c conda-forge gpytorch ```
-
emcee (πŸ₯ˆ31 Β· ⭐ 1.4K) - The Python ensemble sampling toolkit for affine-invariant MCMC. MIT +
pandas-ta (πŸ₯ˆ30 Β· ⭐ 5.2K) - Technical Analysis Indicators - Pandas TA is an easy to use.. MIT -- [GitHub](https://github.com/dfm/emcee) (πŸ‘¨β€πŸ’» 74 Β· πŸ”€ 430 Β· πŸ“¦ 2.4K Β· πŸ“‹ 300 - 18% open Β· ⏱️ 02.05.2024): +- [GitHub](https://github.com/twopirllc/pandas-ta) (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 1K Β· πŸ“¦ 4.1K Β· πŸ“‹ 580 - 18% open Β· ⏱️ 24.06.2024): ``` - git clone https://github.com/dfm/emcee + git clone https://github.com/twopirllc/pandas-ta ``` -- [PyPi](https://pypi.org/project/emcee) (πŸ“₯ 130K / month Β· πŸ“¦ 390 Β· ⏱️ 19.04.2024): +- [PyPi](https://pypi.org/project/pandas-ta) (πŸ“₯ 130K / month Β· πŸ“¦ 110 Β· ⏱️ 28.07.2021): ``` - pip install emcee + pip install pandas-ta ``` -- [Conda](https://anaconda.org/conda-forge/emcee) (πŸ“₯ 340K Β· ⏱️ 22.04.2024): +- [Conda](https://anaconda.org/conda-forge/pandas-ta) (πŸ“₯ 22K Β· ⏱️ 16.06.2023): ``` - conda install -c conda-forge emcee + conda install -c conda-forge pandas-ta ```
-
patsy (πŸ₯ˆ31 Β· ⭐ 930) - Describing statistical models in Python using symbolic formulas. BSD-2 +
pomegranate (πŸ₯ˆ30 Β· ⭐ 3.3K) - Fast, flexible and easy to use probabilistic modelling in Python. MIT -- [GitHub](https://github.com/pydata/patsy) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 100 Β· πŸ“¦ 97K Β· πŸ“‹ 150 - 47% open Β· ⏱️ 04.01.2024): +- [GitHub](https://github.com/jmschrei/pomegranate) (πŸ‘¨β€πŸ’» 75 Β· πŸ”€ 590 Β· πŸ“¦ 1.1K Β· πŸ“‹ 780 - 2% open Β· ⏱️ 11.07.2024): ``` - git clone https://github.com/pydata/patsy + git clone https://github.com/jmschrei/pomegranate ``` -- [PyPi](https://pypi.org/project/patsy) (πŸ“₯ 15M / month Β· πŸ“¦ 480 Β· ⏱️ 04.01.2024): +- [PyPi](https://pypi.org/project/pomegranate) (πŸ“₯ 13K / month Β· πŸ“¦ 59 Β· ⏱️ 11.07.2024): ``` - pip install patsy + pip install pomegranate ``` -- [Conda](https://anaconda.org/conda-forge/patsy) (πŸ“₯ 11M Β· ⏱️ 05.01.2024): +- [Conda](https://anaconda.org/conda-forge/pomegranate) (πŸ“₯ 170K Β· ⏱️ 10.12.2023): ``` - conda install -c conda-forge patsy + conda install -c conda-forge pomegranate ```
-
SALib (πŸ₯ˆ31 Β· ⭐ 840) - Sensitivity Analysis Library in Python. Contains Sobol, Morris, FAST, and.. MIT +
GPflow (πŸ₯ˆ30 Β· ⭐ 1.8K) - Gaussian processes in TensorFlow. Apache-2 -- [GitHub](https://github.com/SALib/SALib) (πŸ‘¨β€πŸ’» 46 Β· πŸ”€ 230 Β· πŸ“¦ 1.1K Β· πŸ“‹ 320 - 15% open Β· ⏱️ 22.04.2024): +- [GitHub](https://github.com/GPflow/GPflow) (πŸ‘¨β€πŸ’» 84 Β· πŸ”€ 440 Β· πŸ“¦ 680 Β· πŸ“‹ 840 - 18% open Β· ⏱️ 14.06.2024): ``` - git clone https://github.com/SALib/SALib + git clone https://github.com/GPflow/GPflow ``` -- [PyPi](https://pypi.org/project/salib) (πŸ“₯ 160K / month Β· πŸ“¦ 120 Β· ⏱️ 22.04.2024): +- [PyPi](https://pypi.org/project/gpflow) (πŸ“₯ 75K / month Β· πŸ“¦ 35 Β· ⏱️ 17.06.2024): ``` - pip install salib + pip install gpflow ``` -- [Conda](https://anaconda.org/conda-forge/salib) (πŸ“₯ 160K Β· ⏱️ 22.04.2024): +- [Conda](https://anaconda.org/conda-forge/gpflow) (πŸ“₯ 33K Β· ⏱️ 26.06.2024): ``` - conda install -c conda-forge salib + conda install -c conda-forge gpflow ```
-
pomegranate (πŸ₯‰30 Β· ⭐ 3.3K) - Fast, flexible and easy to use probabilistic modelling in Python. MIT +
emcee (πŸ₯ˆ30 Β· ⭐ 1.5K) - The Python ensemble sampling toolkit for affine-invariant MCMC. MIT -- [GitHub](https://github.com/jmschrei/pomegranate) (πŸ‘¨β€πŸ’» 73 Β· πŸ”€ 570 Β· πŸ“¦ 1.1K Β· πŸ“‹ 760 - 6% open Β· ⏱️ 11.03.2024): +- [GitHub](https://github.com/dfm/emcee) (πŸ‘¨β€πŸ’» 74 Β· πŸ”€ 430 Β· πŸ“¦ 2.6K Β· πŸ“‹ 300 - 19% open Β· ⏱️ 03.07.2024): ``` - git clone https://github.com/jmschrei/pomegranate + git clone https://github.com/dfm/emcee ``` -- [PyPi](https://pypi.org/project/pomegranate) (πŸ“₯ 28K / month Β· πŸ“¦ 54 Β· ⏱️ 11.03.2024): +- [PyPi](https://pypi.org/project/emcee) (πŸ“₯ 180K / month Β· πŸ“¦ 420 Β· ⏱️ 19.04.2024): ``` - pip install pomegranate + pip install emcee ``` -- [Conda](https://anaconda.org/conda-forge/pomegranate) (πŸ“₯ 150K Β· ⏱️ 10.12.2023): +- [Conda](https://anaconda.org/conda-forge/emcee) (πŸ“₯ 360K Β· ⏱️ 22.04.2024): ``` - conda install -c conda-forge pomegranate + conda install -c conda-forge emcee ```
-
hmmlearn (πŸ₯‰30 Β· ⭐ 3K) - Hidden Markov Models in Python, with scikit-learn like API. BSD-3 +
patsy (πŸ₯ˆ30 Β· ⭐ 940 Β· πŸ’€) - Describing statistical models in Python using symbolic formulas. BSD-2 -- [GitHub](https://github.com/hmmlearn/hmmlearn) (πŸ‘¨β€πŸ’» 48 Β· πŸ”€ 740 Β· πŸ“¦ 2.6K Β· πŸ“‹ 440 - 14% open Β· ⏱️ 05.04.2024): +- [GitHub](https://github.com/pydata/patsy) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 100 Β· πŸ“¦ 100K Β· πŸ“‹ 150 - 46% open Β· ⏱️ 04.01.2024): ``` - git clone https://github.com/hmmlearn/hmmlearn + git clone https://github.com/pydata/patsy ``` -- [PyPi](https://pypi.org/project/hmmlearn) (πŸ“₯ 210K / month Β· πŸ“¦ 79 Β· ⏱️ 02.03.2024): +- [PyPi](https://pypi.org/project/patsy) (πŸ“₯ 15M / month Β· πŸ“¦ 520 Β· ⏱️ 04.01.2024): ``` - pip install hmmlearn + pip install patsy ``` -- [Conda](https://anaconda.org/conda-forge/hmmlearn) (πŸ“₯ 230K Β· ⏱️ 22.05.2024): +- [Conda](https://anaconda.org/conda-forge/patsy) (πŸ“₯ 12M Β· ⏱️ 05.01.2024): ``` - conda install -c conda-forge hmmlearn + conda install -c conda-forge patsy ```
-
GPflow (πŸ₯‰30 Β· ⭐ 1.8K) - Gaussian processes in TensorFlow. Apache-2 +
SALib (πŸ₯ˆ30 Β· ⭐ 870) - Sensitivity Analysis Library in Python. Contains Sobol, Morris, FAST, and.. MIT -- [GitHub](https://github.com/GPflow/GPflow) (πŸ‘¨β€πŸ’» 84 Β· πŸ”€ 440 Β· πŸ“¦ 660 Β· πŸ“‹ 830 - 17% open Β· ⏱️ 06.05.2024): +- [GitHub](https://github.com/SALib/SALib) (πŸ‘¨β€πŸ’» 46 Β· πŸ”€ 230 Β· πŸ“¦ 1.2K Β· πŸ“‹ 340 - 15% open Β· ⏱️ 14.07.2024): ``` - git clone https://github.com/GPflow/GPflow + git clone https://github.com/SALib/SALib ``` -- [PyPi](https://pypi.org/project/gpflow) (πŸ“₯ 62K / month Β· πŸ“¦ 37 Β· ⏱️ 07.02.2024): +- [PyPi](https://pypi.org/project/salib) (πŸ“₯ 180K / month Β· πŸ“¦ 130 Β· ⏱️ 19.08.2024): ``` - pip install gpflow + pip install salib ``` -- [Conda](https://anaconda.org/conda-forge/gpflow) (πŸ“₯ 27K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/salib) (πŸ“₯ 180K Β· ⏱️ 19.08.2024): ``` - conda install -c conda-forge gpflow + conda install -c conda-forge salib ```
-
PyStan (πŸ₯‰29 Β· ⭐ 320) - PyStan, a Python interface to Stan, a platform for statistical modeling... ISC +
hmmlearn (πŸ₯‰29 Β· ⭐ 3K) - Hidden Markov Models in Python, with scikit-learn like API. BSD-3 -- [GitHub](https://github.com/stan-dev/pystan) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 58 Β· πŸ“¦ 9.8K Β· πŸ“‹ 200 - 6% open Β· ⏱️ 12.04.2024): +- [GitHub](https://github.com/hmmlearn/hmmlearn) (πŸ‘¨β€πŸ’» 49 Β· πŸ”€ 740 Β· πŸ“¦ 2.7K Β· πŸ“‹ 440 - 15% open Β· ⏱️ 05.04.2024): ``` - git clone https://github.com/stan-dev/pystan + git clone https://github.com/hmmlearn/hmmlearn ``` -- [PyPi](https://pypi.org/project/pystan) (πŸ“₯ 2M / month Β· πŸ“¦ 160 Β· ⏱️ 12.04.2024): +- [PyPi](https://pypi.org/project/hmmlearn) (πŸ“₯ 110K / month Β· πŸ“¦ 87 Β· ⏱️ 02.03.2024): ``` - pip install pystan + pip install hmmlearn ``` -- [Conda](https://anaconda.org/conda-forge/pystan) (πŸ“₯ 2.8M Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/hmmlearn) (πŸ“₯ 270K Β· ⏱️ 22.05.2024): ``` - conda install -c conda-forge pystan + conda install -c conda-forge hmmlearn ```
-
Orbit (πŸ₯‰26 Β· ⭐ 1.8K) - A Python package for Bayesian forecasting with object-oriented design.. Apache-2 +
PyStan (πŸ₯‰29 Β· ⭐ 340) - PyStan, a Python interface to Stan, a platform for statistical modeling... ISC -- [GitHub](https://github.com/uber/orbit) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 140 Β· πŸ“¦ 57 Β· πŸ“‹ 400 - 12% open Β· ⏱️ 31.03.2024): +- [GitHub](https://github.com/stan-dev/pystan) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 58 Β· πŸ“¦ 10K Β· πŸ“‹ 200 - 6% open Β· ⏱️ 03.07.2024): ``` - git clone https://github.com/uber/orbit + git clone https://github.com/stan-dev/pystan ``` -- [PyPi](https://pypi.org/project/orbit-ml) (πŸ“₯ 21K / month Β· πŸ“¦ 1 Β· ⏱️ 01.04.2024): +- [PyPi](https://pypi.org/project/pystan) (πŸ“₯ 790K / month Β· πŸ“¦ 160 Β· ⏱️ 03.07.2024): ``` - pip install orbit-ml + pip install pystan + ``` +- [Conda](https://anaconda.org/conda-forge/pystan) (πŸ“₯ 2.9M Β· ⏱️ 16.06.2023): + ``` + conda install -c conda-forge pystan ```
-
bambi (πŸ₯‰25 Β· ⭐ 1K) - BAyesian Model-Building Interface (Bambi) in Python. MIT +
bambi (πŸ₯‰27 Β· ⭐ 1.1K) - BAyesian Model-Building Interface (Bambi) in Python. MIT -- [GitHub](https://github.com/bambinos/bambi) (πŸ‘¨β€πŸ’» 37 Β· πŸ”€ 120 Β· πŸ“¦ 120 Β· πŸ“‹ 400 - 18% open Β· ⏱️ 02.06.2024): +- [GitHub](https://github.com/bambinos/bambi) (πŸ‘¨β€πŸ’» 39 Β· πŸ”€ 120 Β· πŸ“¦ 140 Β· πŸ“‹ 410 - 19% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/bambinos/bambi ``` -- [PyPi](https://pypi.org/project/bambi) (πŸ“₯ 21K / month Β· πŸ“¦ 10 Β· ⏱️ 25.10.2023): +- [PyPi](https://pypi.org/project/bambi) (πŸ“₯ 28K / month Β· πŸ“¦ 10 Β· ⏱️ 10.07.2024): ``` pip install bambi ``` -- [Conda](https://anaconda.org/conda-forge/bambi) (πŸ“₯ 32K Β· ⏱️ 27.10.2023): +- [Conda](https://anaconda.org/conda-forge/bambi) (πŸ“₯ 36K Β· ⏱️ 10.07.2024): ``` conda install -c conda-forge bambi ```
-
Baal (πŸ₯‰24 Β· ⭐ 840) - Bayesian active learning library for research and industrial usecases. Apache-2 +
Orbit (πŸ₯‰25 Β· ⭐ 1.9K) - A Python package for Bayesian forecasting with object-oriented design.. Apache-2 -- [GitHub](https://github.com/baal-org/baal) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 83 Β· πŸ“¦ 56 Β· πŸ“‹ 110 - 21% open Β· ⏱️ 28.05.2024): +- [GitHub](https://github.com/uber/orbit) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 140 Β· πŸ“¦ 61 Β· πŸ“‹ 400 - 12% open Β· ⏱️ 10.07.2024): ``` - git clone https://github.com/baal-org/baal - ``` -- [PyPi](https://pypi.org/project/baal) (πŸ“₯ 1.3K / month Β· πŸ“¦ 1 Β· ⏱️ 04.04.2024): - ``` - pip install baal + git clone https://github.com/uber/orbit ``` -- [Conda](https://anaconda.org/conda-forge/baal) (πŸ“₯ 8.5K Β· ⏱️ 12.06.2023): +- [PyPi](https://pypi.org/project/orbit-ml) (πŸ“₯ 19K / month Β· πŸ“¦ 1 Β· ⏱️ 01.04.2024): ``` - conda install -c conda-forge baal + pip install orbit-ml ```
-
scikit-posthocs (πŸ₯‰24 Β· ⭐ 320) - Multiple Pairwise Comparisons (Post Hoc) Tests in Python. MIT +
scikit-posthocs (πŸ₯‰24 Β· ⭐ 330) - Multiple Pairwise Comparisons (Post Hoc) Tests in Python. MIT -- [GitHub](https://github.com/maximtrp/scikit-posthocs) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 39 Β· πŸ“₯ 46 Β· πŸ“¦ 720 Β· πŸ“‹ 54 - 11% open Β· ⏱️ 18.02.2024): +- [GitHub](https://github.com/maximtrp/scikit-posthocs) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 40 Β· πŸ“₯ 57 Β· πŸ“¦ 800 Β· πŸ“‹ 58 - 12% open Β· ⏱️ 26.06.2024): ``` git clone https://github.com/maximtrp/scikit-posthocs ``` -- [PyPi](https://pypi.org/project/scikit-posthocs) (πŸ“₯ 98K / month Β· πŸ“¦ 46 Β· ⏱️ 18.02.2024): +- [PyPi](https://pypi.org/project/scikit-posthocs) (πŸ“₯ 100K / month Β· πŸ“¦ 48 Β· ⏱️ 18.02.2024): ``` pip install scikit-posthocs ``` -- [Conda](https://anaconda.org/conda-forge/scikit-posthocs) (πŸ“₯ 930K Β· ⏱️ 19.02.2024): +- [Conda](https://anaconda.org/conda-forge/scikit-posthocs) (πŸ“₯ 960K Β· ⏱️ 08.07.2024): ``` conda install -c conda-forge scikit-posthocs ```
-
Show 7 hidden projects... +
Baal (πŸ₯‰21 Β· ⭐ 860) - Bayesian active learning library for research and industrial usecases. Apache-2 + +- [GitHub](https://github.com/baal-org/baal) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 86 Β· πŸ“¦ 60 Β· πŸ“‹ 110 - 17% open Β· ⏱️ 27.06.2024): + + ``` + git clone https://github.com/baal-org/baal + ``` +- [PyPi](https://pypi.org/project/baal) (πŸ“₯ 1.6K / month Β· πŸ“¦ 2 Β· ⏱️ 11.06.2024): + ``` + pip install baal + ``` +- [Conda](https://anaconda.org/conda-forge/baal) (πŸ“₯ 9.7K Β· ⏱️ 12.06.2023): + ``` + conda install -c conda-forge baal + ``` +
+
Show 6 hidden projects... -- pandas-ta (πŸ₯ˆ31 Β· ⭐ 4.9K Β· πŸ’€) - Technical Analysis Indicators - Pandas TA is an easy to use.. MIT -- filterpy (πŸ₯ˆ31 Β· ⭐ 3.2K Β· πŸ’€) - Python Kalman filtering and optimal estimation library. Implements.. MIT -- pingouin (πŸ₯‰30 Β· ⭐ 1.6K) - Statistical package in Python based on Pandas. ❗️GPL-3.0 +- filterpy (πŸ₯ˆ31 Β· ⭐ 3.3K Β· πŸ’€) - Python Kalman filtering and optimal estimation library. Implements.. MIT +- pingouin (πŸ₯‰29 Β· ⭐ 1.6K) - Statistical package in Python based on Pandas. ❗️GPL-3.0 - Edward (πŸ₯‰27 Β· ⭐ 4.8K Β· πŸ’€) - A probabilistic programming language in TensorFlow. Deep.. Apache-2 -- pyhsmm (πŸ₯‰20 Β· ⭐ 540 Β· πŸ’€) - Bayesian inference in HSMMs and HMMs. MIT -- Funsor (πŸ₯‰19 Β· ⭐ 230 Β· πŸ’€) - Functional tensors for probabilistic programming. Apache-2 +- pyhsmm (πŸ₯‰21 Β· ⭐ 550 Β· πŸ’€) - Bayesian inference in HSMMs and HMMs. MIT +- Funsor (πŸ₯‰20 Β· ⭐ 230 Β· πŸ’€) - Functional tensors for probabilistic programming. Apache-2 - ZhuSuan (πŸ₯‰15 Β· ⭐ 2.2K Β· πŸ’€) - A probabilistic programming library for Bayesian deep learning,.. MIT

@@ -6917,60 +6838,60 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes _Libraries for testing the robustness of machine learning models against attacks with adversarial/malicious examples._ -
ART (πŸ₯‡34 Β· ⭐ 4.6K) - Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning.. MIT +
ART (πŸ₯‡34 Β· ⭐ 4.7K) - Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning.. MIT -- [GitHub](https://github.com/Trusted-AI/adversarial-robustness-toolbox) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 1.1K Β· πŸ“¦ 530 Β· πŸ“‹ 900 - 16% open Β· ⏱️ 06.05.2024): +- [GitHub](https://github.com/Trusted-AI/adversarial-robustness-toolbox) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 1.1K Β· πŸ“¦ 580 Β· πŸ“‹ 910 - 16% open Β· ⏱️ 29.08.2024): ``` git clone https://github.com/Trusted-AI/adversarial-robustness-toolbox ``` -- [PyPi](https://pypi.org/project/adversarial-robustness-toolbox) (πŸ“₯ 24K / month Β· πŸ“¦ 11 Β· ⏱️ 17.02.2024): +- [PyPi](https://pypi.org/project/adversarial-robustness-toolbox) (πŸ“₯ 27K / month Β· πŸ“¦ 20 Β· ⏱️ 03.07.2024): ``` pip install adversarial-robustness-toolbox ``` -- [Conda](https://anaconda.org/conda-forge/adversarial-robustness-toolbox) (πŸ“₯ 40K Β· ⏱️ 18.02.2024): +- [Conda](https://anaconda.org/conda-forge/adversarial-robustness-toolbox) (πŸ“₯ 47K Β· ⏱️ 03.07.2024): ``` conda install -c conda-forge adversarial-robustness-toolbox ```
-
TextAttack (πŸ₯ˆ29 Β· ⭐ 2.8K) - TextAttack is a Python framework for adversarial attacks, data.. MIT +
TextAttack (πŸ₯ˆ27 Β· ⭐ 2.9K) - TextAttack is a Python framework for adversarial attacks, data.. MIT -- [GitHub](https://github.com/QData/TextAttack) (πŸ‘¨β€πŸ’» 65 Β· πŸ”€ 370 Β· πŸ“¦ 260 Β· πŸ“‹ 270 - 19% open Β· ⏱️ 31.03.2024): +- [GitHub](https://github.com/QData/TextAttack) (πŸ‘¨β€πŸ’» 66 Β· πŸ”€ 380 Β· πŸ“¦ 290 Β· πŸ“‹ 280 - 21% open Β· ⏱️ 25.07.2024): ``` git clone https://github.com/QData/TextAttack ``` -- [PyPi](https://pypi.org/project/textattack) (πŸ“₯ 3.2K / month Β· πŸ“¦ 6 Β· ⏱️ 11.03.2024): +- [PyPi](https://pypi.org/project/textattack) (πŸ“₯ 3.7K / month Β· πŸ“¦ 11 Β· ⏱️ 11.03.2024): ``` pip install textattack ``` -- [Conda](https://anaconda.org/conda-forge/textattack) (πŸ“₯ 7.6K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/textattack) (πŸ“₯ 8.3K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge textattack ```
-
Foolbox (πŸ₯ˆ29 Β· ⭐ 2.7K) - A Python toolbox to create adversarial examples that fool neural networks.. MIT +
Foolbox (πŸ₯ˆ27 Β· ⭐ 2.7K) - A Python toolbox to create adversarial examples that fool neural networks.. MIT -- [GitHub](https://github.com/bethgelab/foolbox) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 420 Β· πŸ“¦ 580 Β· πŸ“‹ 370 - 5% open Β· ⏱️ 04.03.2024): +- [GitHub](https://github.com/bethgelab/foolbox) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 420 Β· πŸ“¦ 620 Β· πŸ“‹ 370 - 5% open Β· ⏱️ 04.03.2024): ``` git clone https://github.com/bethgelab/foolbox ``` -- [PyPi](https://pypi.org/project/foolbox) (πŸ“₯ 2.6K / month Β· πŸ“¦ 14 Β· ⏱️ 04.03.2024): +- [PyPi](https://pypi.org/project/foolbox) (πŸ“₯ 3.2K / month Β· πŸ“¦ 14 Β· ⏱️ 04.03.2024): ``` pip install foolbox ``` -- [Conda](https://anaconda.org/conda-forge/foolbox) (πŸ“₯ 13K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/foolbox) (πŸ“₯ 15K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge foolbox ```
Show 6 hidden projects... -- CleverHans (πŸ₯ˆ30 Β· ⭐ 6.1K Β· πŸ’€) - An adversarial example library for constructing attacks,.. MIT +- CleverHans (πŸ₯ˆ29 Β· ⭐ 6.2K Β· πŸ’€) - An adversarial example library for constructing attacks,.. MIT - advertorch (πŸ₯‰22 Β· ⭐ 1.3K Β· πŸ’€) - A Toolbox for Adversarial Robustness Research. ❗️GPL-3.0 -- AdvBox (πŸ₯‰18 Β· ⭐ 1.4K Β· πŸ’€) - Advbox is a toolbox to generate adversarial examples that fool.. Apache-2 -- robustness (πŸ₯‰18 Β· ⭐ 890 Β· πŸ’€) - A library for experimenting with, training and evaluating neural.. MIT +- AdvBox (πŸ₯‰19 Β· ⭐ 1.4K Β· πŸ’€) - Advbox is a toolbox to generate adversarial examples that fool.. Apache-2 +- robustness (πŸ₯‰18 Β· ⭐ 900 Β· πŸ’€) - A library for experimenting with, training and evaluating neural.. MIT - textflint (πŸ₯‰16 Β· ⭐ 630 Β· πŸ’€) - Unified Multilingual Robustness Evaluation Toolkit for.. ❗️GPL-3.0 - Adversary (πŸ₯‰15 Β· ⭐ 390 Β· πŸ’€) - Tool to generate adversarial text examples and test machine.. MIT
@@ -6982,102 +6903,102 @@ _Libraries for testing the robustness of machine learning models against attacks _Libraries that require and make use of CUDA/GPU or other accelerator hardware capabilities to optimize machine learning tasks._ -
CuPy (πŸ₯‡37 Β· ⭐ 7.9K) - NumPy & SciPy for GPU. MIT +
CuPy (πŸ₯‡39 Β· ⭐ 8.1K) - NumPy & SciPy for GPU. MIT -- [GitHub](https://github.com/cupy/cupy) (πŸ‘¨β€πŸ’» 370 Β· πŸ”€ 780 Β· πŸ“₯ 180K Β· πŸ“¦ 2.1K Β· πŸ“‹ 2.2K - 25% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/cupy/cupy) (πŸ‘¨β€πŸ’» 380 Β· πŸ”€ 800 Β· πŸ“₯ 180K Β· πŸ“¦ 2.2K Β· πŸ“‹ 2.3K - 27% open Β· ⏱️ 30.08.2024): ``` git clone https://github.com/cupy/cupy ``` -- [PyPi](https://pypi.org/project/cupy) (πŸ“₯ 23K / month Β· πŸ“¦ 220 Β· ⏱️ 19.04.2024): +- [PyPi](https://pypi.org/project/cupy) (πŸ“₯ 29K / month Β· πŸ“¦ 270 Β· ⏱️ 22.08.2024): ``` pip install cupy ``` -- [Conda](https://anaconda.org/conda-forge/cupy) (πŸ“₯ 3.7M Β· ⏱️ 29.04.2024): +- [Conda](https://anaconda.org/conda-forge/cupy) (πŸ“₯ 4.5M Β· ⏱️ 22.08.2024): ``` conda install -c conda-forge cupy ``` -- [Docker Hub](https://hub.docker.com/r/cupy/cupy) (πŸ“₯ 63K Β· ⭐ 13 Β· ⏱️ 19.04.2024): +- [Docker Hub](https://hub.docker.com/r/cupy/cupy) (πŸ“₯ 66K Β· ⭐ 13 Β· ⏱️ 22.08.2024): ``` docker pull cupy/cupy ```
-
optimum (πŸ₯‡34 Β· ⭐ 2.2K) - Accelerate training and inference of Transformers and Diffusers with.. Apache-2 +
cuDF (πŸ₯‡35 Β· ⭐ 8.2K) - cuDF - GPU DataFrame Library. Apache-2 -- [GitHub](https://github.com/huggingface/optimum) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 380 Β· πŸ“¦ 2.6K Β· πŸ“‹ 750 - 47% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/rapidsai/cudf) (πŸ‘¨β€πŸ’» 290 Β· πŸ”€ 880 Β· πŸ“¦ 56 Β· πŸ“‹ 6.5K - 15% open Β· ⏱️ 05.09.2024): ``` - git clone https://github.com/huggingface/optimum - ``` -- [PyPi](https://pypi.org/project/optimum) (πŸ“₯ 930K / month Β· πŸ“¦ 140 Β· ⏱️ 29.05.2024): - ``` - pip install optimum + git clone https://github.com/rapidsai/cudf ``` -- [Conda](https://anaconda.org/conda-forge/optimum) (πŸ“₯ 15K Β· ⏱️ 29.05.2024): +- [PyPi](https://pypi.org/project/cudf) (πŸ“₯ 2.8K / month Β· πŸ“¦ 22 Β· ⏱️ 01.06.2020): ``` - conda install -c conda-forge optimum + pip install cudf ```
-
cuDF (πŸ₯ˆ33 Β· ⭐ 7.8K) - cuDF - GPU DataFrame Library. Apache-2 +
optimum (πŸ₯ˆ34 Β· ⭐ 2.4K) - Accelerate training and inference of Transformers and Diffusers with.. Apache-2 -- [GitHub](https://github.com/rapidsai/cudf) (πŸ‘¨β€πŸ’» 290 Β· πŸ”€ 850 Β· πŸ“¦ 55 Β· πŸ“‹ 6.4K - 17% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/huggingface/optimum) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 420 Β· πŸ“¦ 3.3K Β· πŸ“‹ 820 - 49% open Β· ⏱️ 05.09.2024): ``` - git clone https://github.com/rapidsai/cudf + git clone https://github.com/huggingface/optimum ``` -- [PyPi](https://pypi.org/project/cudf) (πŸ“₯ 3.5K / month Β· πŸ“¦ 17 Β· ⏱️ 01.06.2020): +- [PyPi](https://pypi.org/project/optimum) (πŸ“₯ 890K / month Β· πŸ“¦ 160 Β· ⏱️ 16.08.2024): ``` - pip install cudf + pip install optimum + ``` +- [Conda](https://anaconda.org/conda-forge/optimum) (πŸ“₯ 22K Β· ⏱️ 29.05.2024): + ``` + conda install -c conda-forge optimum ```
-
cuML (πŸ₯ˆ31 Β· ⭐ 4K) - cuML - RAPIDS Machine Learning Library. Apache-2 +
PyCUDA (πŸ₯ˆ33 Β· ⭐ 1.8K) - CUDA integration for Python, plus shiny features. MIT -- [GitHub](https://github.com/rapidsai/cuml) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 510 Β· πŸ“‹ 2.5K - 35% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/inducer/pycuda) (πŸ‘¨β€πŸ’» 82 Β· πŸ”€ 280 Β· πŸ“¦ 3.1K Β· πŸ“‹ 270 - 30% open Β· ⏱️ 30.07.2024): ``` - git clone https://github.com/rapidsai/cuml + git clone https://github.com/inducer/pycuda ``` -- [PyPi](https://pypi.org/project/cuml) (πŸ“₯ 3.4K / month Β· πŸ“¦ 13 Β· ⏱️ 01.06.2020): +- [PyPi](https://pypi.org/project/pycuda) (πŸ“₯ 50K / month Β· πŸ“¦ 160 Β· ⏱️ 30.07.2024): ``` - pip install cuml + pip install pycuda + ``` +- [Conda](https://anaconda.org/conda-forge/pycuda) (πŸ“₯ 530K Β· ⏱️ 17.08.2024): + ``` + conda install -c conda-forge pycuda ```
-
PyCUDA (πŸ₯ˆ31 Β· ⭐ 1.8K) - CUDA integration for Python, plus shiny features. MIT +
Apex (πŸ₯ˆ31 Β· ⭐ 8.3K) - A PyTorch Extension: Tools for easy mixed precision and distributed.. BSD-3 -- [GitHub](https://github.com/inducer/pycuda) (πŸ‘¨β€πŸ’» 82 Β· πŸ”€ 280 Β· πŸ“¦ 2.9K Β· πŸ“‹ 260 - 30% open Β· ⏱️ 08.05.2024): +- [GitHub](https://github.com/NVIDIA/apex) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 1.4K Β· πŸ“¦ 2.7K Β· πŸ“‹ 1.2K - 57% open Β· ⏱️ 30.08.2024): ``` - git clone https://github.com/inducer/pycuda - ``` -- [PyPi](https://pypi.org/project/pycuda) (πŸ“₯ 53K / month Β· πŸ“¦ 140 Β· ⏱️ 03.01.2024): - ``` - pip install pycuda + git clone https://github.com/NVIDIA/apex ``` -- [Conda](https://anaconda.org/conda-forge/pycuda) (πŸ“₯ 350K Β· ⏱️ 06.01.2024): +- [Conda](https://anaconda.org/conda-forge/nvidia-apex) (πŸ“₯ 300K Β· ⏱️ 17.05.2024): ``` - conda install -c conda-forge pycuda + conda install -c conda-forge nvidia-apex ```
-
Apex (πŸ₯ˆ30 Β· ⭐ 8.1K) - A PyTorch Extension: Tools for easy mixed precision and distributed.. BSD-3 +
cuML (πŸ₯ˆ31 Β· ⭐ 4.1K) - cuML - RAPIDS Machine Learning Library. Apache-2 -- [GitHub](https://github.com/NVIDIA/apex) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 1.3K Β· πŸ“¦ 2.5K Β· πŸ“‹ 1.2K - 57% open Β· ⏱️ 26.04.2024): +- [GitHub](https://github.com/rapidsai/cuml) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 520 Β· πŸ“‹ 2.5K - 35% open Β· ⏱️ 04.09.2024): ``` - git clone https://github.com/NVIDIA/apex + git clone https://github.com/rapidsai/cuml ``` -- [Conda](https://anaconda.org/conda-forge/nvidia-apex) (πŸ“₯ 220K Β· ⏱️ 17.05.2024): +- [PyPi](https://pypi.org/project/cuml) (πŸ“₯ 2.8K / month Β· πŸ“¦ 14 Β· ⏱️ 01.06.2020): ``` - conda install -c conda-forge nvidia-apex + pip install cuml ```
-
gpustat (πŸ₯ˆ29 Β· ⭐ 3.9K) - A simple command-line utility for querying and monitoring GPU status. MIT +
gpustat (πŸ₯ˆ30 Β· ⭐ 4K Β· πŸ’€) - A simple command-line utility for querying and monitoring GPU status. MIT -- [GitHub](https://github.com/wookayin/gpustat) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 270 Β· πŸ“¦ 5.4K Β· πŸ“‹ 120 - 22% open Β· ⏱️ 12.01.2024): +- [GitHub](https://github.com/wookayin/gpustat) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 280 Β· πŸ“¦ 5.9K Β· πŸ“‹ 120 - 22% open Β· ⏱️ 12.01.2024): ``` git clone https://github.com/wookayin/gpustat ``` -- [PyPi](https://pypi.org/project/gpustat) (πŸ“₯ 780K / month Β· πŸ“¦ 140 Β· ⏱️ 22.08.2023): +- [PyPi](https://pypi.org/project/gpustat) (πŸ“₯ 570K / month Β· πŸ“¦ 150 Β· ⏱️ 22.08.2023): ``` pip install gpustat ``` @@ -7086,74 +7007,74 @@ _Libraries that require and make use of CUDA/GPU or other accelerator hardware c conda install -c conda-forge gpustat ```
-
ArrayFire (πŸ₯ˆ27 Β· ⭐ 4.4K) - ArrayFire: a general purpose GPU library. BSD-3 +
ArrayFire (πŸ₯ˆ28 Β· ⭐ 4.5K) - ArrayFire: a general purpose GPU library. BSD-3 -- [GitHub](https://github.com/arrayfire/arrayfire) (πŸ‘¨β€πŸ’» 90 Β· πŸ”€ 530 Β· πŸ“₯ 6.2K Β· πŸ“‹ 1.7K - 20% open Β· ⏱️ 04.04.2024): +- [GitHub](https://github.com/arrayfire/arrayfire) (πŸ‘¨β€πŸ’» 92 Β· πŸ”€ 530 Β· πŸ“₯ 6.8K Β· πŸ“‹ 1.7K - 19% open Β· ⏱️ 03.09.2024): ``` git clone https://github.com/arrayfire/arrayfire ``` -- [PyPi](https://pypi.org/project/arrayfire) (πŸ“₯ 1.8K / month Β· πŸ“¦ 10 Β· ⏱️ 22.02.2022): +- [PyPi](https://pypi.org/project/arrayfire) (πŸ“₯ 2.2K / month Β· πŸ“¦ 10 Β· ⏱️ 22.02.2022): ``` pip install arrayfire ```
-
cuGraph (πŸ₯ˆ27 Β· ⭐ 1.6K) - cuGraph - RAPIDS Graph Analytics Library. Apache-2 +
cuGraph (πŸ₯‰27 Β· ⭐ 1.7K) - cuGraph - RAPIDS Graph Analytics Library. Apache-2 -- [GitHub](https://github.com/rapidsai/cugraph) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 290 Β· πŸ“¦ 2 Β· πŸ“‹ 1.8K - 17% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/rapidsai/cugraph) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 300 Β· πŸ“‹ 1.7K - 10% open Β· ⏱️ 03.09.2024): ``` git clone https://github.com/rapidsai/cugraph ``` -- [PyPi](https://pypi.org/project/cugraph) (πŸ“₯ 270 / month Β· πŸ“¦ 4 Β· ⏱️ 01.06.2020): +- [PyPi](https://pypi.org/project/cugraph) (πŸ“₯ 210 / month Β· πŸ“¦ 4 Β· ⏱️ 01.06.2020): ``` pip install cugraph ``` -- [Conda](https://anaconda.org/conda-forge/libcugraph) (πŸ“₯ 20K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/libcugraph) (πŸ“₯ 23K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge libcugraph ```
-
DALI (πŸ₯‰25 Β· ⭐ 5K) - A GPU-accelerated library containing highly optimized building blocks and.. Apache-2 +
DALI (πŸ₯‰25 Β· ⭐ 5.1K) - A GPU-accelerated library containing highly optimized building blocks.. Apache-2 -- [GitHub](https://github.com/NVIDIA/DALI) (πŸ‘¨β€πŸ’» 92 Β· πŸ”€ 610 Β· πŸ“‹ 1.6K - 13% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/NVIDIA/DALI) (πŸ‘¨β€πŸ’» 93 Β· πŸ”€ 620 Β· πŸ“‹ 1.6K - 14% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/NVIDIA/DALI ```
-
scikit-cuda (πŸ₯‰24 Β· ⭐ 970 Β· πŸ’€) - Python interface to GPU-powered libraries. BSD-3 +
scikit-cuda (πŸ₯‰24 Β· ⭐ 980 Β· πŸ’€) - Python interface to GPU-powered libraries. BSD-3 -- [GitHub](https://github.com/lebedov/scikit-cuda) (πŸ‘¨β€πŸ’» 44 Β· πŸ”€ 170 Β· πŸ“¦ 300 Β· πŸ“‹ 220 - 23% open Β· ⏱️ 15.10.2023): +- [GitHub](https://github.com/lebedov/scikit-cuda) (πŸ‘¨β€πŸ’» 44 Β· πŸ”€ 180 Β· πŸ“¦ 300 Β· πŸ“‹ 220 - 23% open Β· ⏱️ 15.10.2023): ``` git clone https://github.com/lebedov/scikit-cuda ``` -- [PyPi](https://pypi.org/project/scikit-cuda) (πŸ“₯ 790 / month Β· πŸ“¦ 23 Β· ⏱️ 27.05.2019): +- [PyPi](https://pypi.org/project/scikit-cuda) (πŸ“₯ 800 / month Β· πŸ“¦ 23 Β· ⏱️ 27.05.2019): ``` pip install scikit-cuda ```
-
Vulkan Kompute (πŸ₯‰21 Β· ⭐ 1.5K) - General purpose GPU compute framework built on Vulkan to.. Apache-2 +
Vulkan Kompute (πŸ₯‰23 Β· ⭐ 1.9K) - General purpose GPU compute framework built on Vulkan to.. Apache-2 -- [GitHub](https://github.com/KomputeProject/kompute) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 120 Β· πŸ“₯ 500 Β· πŸ“‹ 210 - 33% open Β· ⏱️ 29.05.2024): +- [GitHub](https://github.com/KomputeProject/kompute) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 140 Β· πŸ“₯ 560 Β· πŸ“‹ 220 - 32% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/KomputeProject/kompute ``` -- [PyPi](https://pypi.org/project/kp) (πŸ“₯ 120 / month Β· ⏱️ 20.01.2024): +- [PyPi](https://pypi.org/project/kp) (πŸ“₯ 150 / month Β· ⏱️ 20.01.2024): ``` pip install kp ```
-
Merlin (πŸ₯‰20 Β· ⭐ 700) - NVIDIA Merlin is an open source library providing end-to-end GPU-.. Apache-2 +
Merlin (πŸ₯‰20 Β· ⭐ 740) - NVIDIA Merlin is an open source library providing end-to-end GPU-.. Apache-2 -- [GitHub](https://github.com/NVIDIA-Merlin/Merlin) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 110 Β· πŸ“‹ 450 - 45% open Β· ⏱️ 25.04.2024): +- [GitHub](https://github.com/NVIDIA-Merlin/Merlin) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 110 Β· πŸ“‹ 460 - 46% open Β· ⏱️ 22.07.2024): ``` git clone https://github.com/NVIDIA-Merlin/Merlin ``` -- [PyPi](https://pypi.org/project/merlin-core) (πŸ“₯ 7.4K / month Β· πŸ“¦ 1 Β· ⏱️ 29.08.2023): +- [PyPi](https://pypi.org/project/merlin-core) (πŸ“₯ 8.1K / month Β· πŸ“¦ 1 Β· ⏱️ 29.08.2023): ``` pip install merlin-core ``` @@ -7168,11 +7089,11 @@ _Libraries that require and make use of CUDA/GPU or other accelerator hardware c
Show 6 hidden projects... -- GPUtil (πŸ₯‰24 Β· ⭐ 1.1K Β· πŸ’€) - A Python module for getting the GPU status from NVIDA GPUs using.. MIT -- py3nvml (πŸ₯‰22 Β· ⭐ 230 Β· πŸ’€) - Python 3 Bindings for NVML library. Get NVIDIA GPU status inside.. BSD-3 +- GPUtil (πŸ₯‰25 Β· ⭐ 1.1K Β· πŸ’€) - A Python module for getting the GPU status from NVIDA GPUs using.. MIT +- py3nvml (πŸ₯‰22 Β· ⭐ 240 Β· πŸ’€) - Python 3 Bindings for NVML library. Get NVIDIA GPU status inside.. BSD-3 - BlazingSQL (πŸ₯‰20 Β· ⭐ 1.9K Β· πŸ’€) - BlazingSQL is a lightweight, GPU accelerated, SQL engine for.. Apache-2 -- nvidia-ml-py3 (πŸ₯‰18 Β· ⭐ 130 Β· πŸ’€) - Python 3 Bindings for the NVIDIA Management Library. BSD-3 -- ipyexperiments (πŸ₯‰16 Β· ⭐ 200) - Automatic GPU+CPU memory profiling, re-use and memory.. Apache-2 +- nvidia-ml-py3 (πŸ₯‰17 Β· ⭐ 130) - Python 3 Bindings for the NVIDIA Management Library. BSD-3 +- ipyexperiments (πŸ₯‰16 Β· ⭐ 200 Β· πŸ’€) - Automatic GPU+CPU memory profiling, re-use and memory.. Apache-2 - SpeedTorch (πŸ₯‰15 Β· ⭐ 680 Β· πŸ’€) - Library for faster pinned CPU - GPU transfer in Pytorch. MIT

@@ -7183,153 +7104,153 @@ _Libraries that require and make use of CUDA/GPU or other accelerator hardware c _Libraries that extend TensorFlow with additional capabilities._ -
TensorFlow Datasets (πŸ₯‡40 Β· ⭐ 4.2K) - TFDS is a collection of datasets ready to use with.. Apache-2 +
TensorFlow Datasets (πŸ₯‡39 Β· ⭐ 4.3K) - TFDS is a collection of datasets ready to use with.. Apache-2 -- [GitHub](https://github.com/tensorflow/datasets) (πŸ‘¨β€πŸ’» 310 Β· πŸ”€ 1.5K Β· πŸ“¦ 18K Β· πŸ“‹ 1.4K - 48% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/tensorflow/datasets) (πŸ‘¨β€πŸ’» 310 Β· πŸ”€ 1.5K Β· πŸ“¦ 19K Β· πŸ“‹ 1.4K - 47% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/tensorflow/datasets ``` -- [PyPi](https://pypi.org/project/tensorflow-datasets) (πŸ“₯ 3.6M / month Β· πŸ“¦ 310 Β· ⏱️ 05.06.2024): +- [PyPi](https://pypi.org/project/tensorflow-datasets) (πŸ“₯ 1.6M / month Β· πŸ“¦ 330 Β· ⏱️ 05.06.2024): ``` pip install tensorflow-datasets ``` -- [Conda](https://anaconda.org/conda-forge/tensorflow-datasets) (πŸ“₯ 30K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/tensorflow-datasets) (πŸ“₯ 34K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge tensorflow-datasets ```
-
tensorflow-hub (πŸ₯‡35 Β· ⭐ 3.4K) - A library for transfer learning by reusing parts of.. Apache-2 +
TFX (πŸ₯‡34 Β· ⭐ 2.1K) - TFX is an end-to-end platform for deploying production ML pipelines. Apache-2 -- [GitHub](https://github.com/tensorflow/hub) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 1.7K Β· πŸ“‹ 700 - 1% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/tensorflow/tfx) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 700 Β· πŸ“¦ 1.5K Β· πŸ“‹ 1.1K - 22% open Β· ⏱️ 04.09.2024): ``` - git clone https://github.com/tensorflow/hub - ``` -- [PyPi](https://pypi.org/project/tensorflow-hub) (πŸ“₯ 4.8M / month Β· πŸ“¦ 290 Β· ⏱️ 30.01.2024): - ``` - pip install tensorflow-hub + git clone https://github.com/tensorflow/tfx ``` -- [Conda](https://anaconda.org/conda-forge/tensorflow-hub) (πŸ“₯ 98K Β· ⏱️ 07.05.2024): +- [PyPi](https://pypi.org/project/tfx) (πŸ“₯ 39K / month Β· πŸ“¦ 17 Β· ⏱️ 13.05.2024): ``` - conda install -c conda-forge tensorflow-hub + pip install tfx ```
-
TF Addons (πŸ₯ˆ33 Β· ⭐ 1.7K) - Useful extra functionality for TensorFlow 2.x maintained by.. Apache-2 +
tensorflow-hub (πŸ₯ˆ32 Β· ⭐ 3.5K Β· πŸ“‰) - A library for transfer learning by reusing parts of.. Apache-2 -- [GitHub](https://github.com/tensorflow/addons) (πŸ‘¨β€πŸ’» 210 Β· πŸ”€ 610 Β· πŸ“¦ 15K Β· πŸ“‹ 990 - 8% open Β· ⏱️ 15.04.2024): +- [GitHub](https://github.com/tensorflow/hub) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 1.7K Β· πŸ“‹ 700 - 1% open Β· ⏱️ 06.06.2024): ``` - git clone https://github.com/tensorflow/addons + git clone https://github.com/tensorflow/hub ``` -- [PyPi](https://pypi.org/project/tensorflow-addons) (πŸ“₯ 1M / month Β· πŸ“¦ 220 Β· ⏱️ 28.11.2023): +- [PyPi](https://pypi.org/project/tensorflow-hub) (πŸ“₯ 1.9M / month Β· πŸ“¦ 300 Β· ⏱️ 30.01.2024): ``` - pip install tensorflow-addons + pip install tensorflow-hub + ``` +- [Conda](https://anaconda.org/conda-forge/tensorflow-hub) (πŸ“₯ 100K Β· ⏱️ 07.05.2024): + ``` + conda install -c conda-forge tensorflow-hub ```
-
TF Model Optimization (πŸ₯ˆ33 Β· ⭐ 1.5K) - A toolkit to optimize ML models for deployment for.. Apache-2 +
TF Addons (πŸ₯ˆ32 Β· ⭐ 1.7K) - Useful extra functionality for TensorFlow 2.x maintained by.. Apache-2 -- [GitHub](https://github.com/tensorflow/model-optimization) (πŸ‘¨β€πŸ’» 85 Β· πŸ”€ 320 Β· πŸ“¦ 3.8K Β· πŸ“‹ 380 - 56% open Β· ⏱️ 02.05.2024): +- [GitHub](https://github.com/tensorflow/addons) (πŸ‘¨β€πŸ’» 210 Β· πŸ”€ 610 Β· πŸ“‹ 990 - 9% open Β· ⏱️ 15.04.2024): ``` - git clone https://github.com/tensorflow/model-optimization + git clone https://github.com/tensorflow/addons ``` -- [PyPi](https://pypi.org/project/tensorflow-model-optimization) (πŸ“₯ 840K / month Β· πŸ“¦ 43 Β· ⏱️ 08.02.2024): +- [PyPi](https://pypi.org/project/tensorflow-addons) (πŸ“₯ 930K / month Β· πŸ“¦ 360 Β· ⏱️ 28.11.2023): ``` - pip install tensorflow-model-optimization + pip install tensorflow-addons ```
-
TFX (πŸ₯ˆ32 Β· ⭐ 2.1K) - TFX is an end-to-end platform for deploying production ML pipelines. Apache-2 +
TensorFlow I/O (πŸ₯ˆ30 Β· ⭐ 700) - Dataset, streaming, and file system extensions.. Apache-2 -- [GitHub](https://github.com/tensorflow/tfx) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 690 Β· πŸ“‹ 1.1K - 21% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/tensorflow/io) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 280 Β· πŸ“‹ 660 - 43% open Β· ⏱️ 01.07.2024): ``` - git clone https://github.com/tensorflow/tfx + git clone https://github.com/tensorflow/io ``` -- [PyPi](https://pypi.org/project/tfx) (πŸ“₯ 69K / month Β· πŸ“¦ 17 Β· ⏱️ 13.05.2024): +- [PyPi](https://pypi.org/project/tensorflow-io) (πŸ“₯ 1.4M / month Β· πŸ“¦ 61 Β· ⏱️ 01.07.2024): ``` - pip install tfx + pip install tensorflow-io ```
-
TensorFlow I/O (πŸ₯ˆ32 Β· ⭐ 690) - Dataset, streaming, and file system extensions.. Apache-2 +
TF Model Optimization (πŸ₯ˆ28 Β· ⭐ 1.5K Β· πŸ“‰) - A toolkit to optimize ML models for deployment for.. Apache-2 -- [GitHub](https://github.com/tensorflow/io) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 280 Β· πŸ“‹ 650 - 44% open Β· ⏱️ 24.05.2024): +- [GitHub](https://github.com/tensorflow/model-optimization) (πŸ‘¨β€πŸ’» 86 Β· πŸ”€ 320 Β· πŸ“‹ 390 - 57% open Β· ⏱️ 08.07.2024): ``` - git clone https://github.com/tensorflow/io + git clone https://github.com/tensorflow/model-optimization ``` -- [PyPi](https://pypi.org/project/tensorflow-io) (πŸ“₯ 3.3M / month Β· πŸ“¦ 60 Β· ⏱️ 01.05.2024): +- [PyPi](https://pypi.org/project/tensorflow-model-optimization) (πŸ“₯ 830K / month Β· πŸ“¦ 45 Β· ⏱️ 08.02.2024): ``` - pip install tensorflow-io + pip install tensorflow-model-optimization ```
-
TensorFlow Transform (πŸ₯‰31 Β· ⭐ 980) - Input pipeline framework. Apache-2 +
TensorFlow Transform (πŸ₯ˆ28 Β· ⭐ 980) - Input pipeline framework. Apache-2 -- [GitHub](https://github.com/tensorflow/transform) (πŸ‘¨β€πŸ’» 28 Β· πŸ”€ 210 Β· πŸ“¦ 1.8K Β· πŸ“‹ 220 - 20% open Β· ⏱️ 30.04.2024): +- [GitHub](https://github.com/tensorflow/transform) (πŸ‘¨β€πŸ’» 28 Β· πŸ”€ 210 Β· πŸ“‹ 220 - 20% open Β· ⏱️ 30.04.2024): ``` git clone https://github.com/tensorflow/transform ``` -- [PyPi](https://pypi.org/project/tensorflow-transform) (πŸ“₯ 880K / month Β· πŸ“¦ 17 Β· ⏱️ 24.04.2024): +- [PyPi](https://pypi.org/project/tensorflow-transform) (πŸ“₯ 540K / month Β· πŸ“¦ 18 Β· ⏱️ 24.04.2024): ``` pip install tensorflow-transform ```
-
Neural Structured Learning (πŸ₯‰25 Β· ⭐ 980 Β· πŸ’€) - Training neural models with structured signals. Apache-2 +
Neural Structured Learning (πŸ₯‰24 Β· ⭐ 980) - Training neural models with structured signals. Apache-2 -- [GitHub](https://github.com/tensorflow/neural-structured-learning) (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 190 Β· πŸ“¦ 450 Β· πŸ“‹ 69 - 1% open Β· ⏱️ 20.09.2023): +- [GitHub](https://github.com/tensorflow/neural-structured-learning) (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 190 Β· πŸ“¦ 480 Β· πŸ“‹ 69 - 1% open Β· ⏱️ 18.06.2024): ``` git clone https://github.com/tensorflow/neural-structured-learning ``` -- [PyPi](https://pypi.org/project/neural-structured-learning) (πŸ“₯ 17K / month Β· πŸ“¦ 3 Β· ⏱️ 29.07.2022): +- [PyPi](https://pypi.org/project/neural-structured-learning) (πŸ“₯ 8.5K / month Β· πŸ“¦ 3 Β· ⏱️ 29.07.2022): ``` pip install neural-structured-learning ```
-
TensorFlow Cloud (πŸ₯‰24 Β· ⭐ 370) - The TensorFlow Cloud repository provides APIs that.. Apache-2 +
Saliency (πŸ₯‰22 Β· ⭐ 950) - Framework-agnostic implementation for state-of-the-art saliency.. Apache-2 -- [GitHub](https://github.com/tensorflow/cloud) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 84 Β· πŸ“¦ 400 Β· πŸ“‹ 100 - 73% open Β· ⏱️ 25.02.2024): +- [GitHub](https://github.com/PAIR-code/saliency) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 190 Β· πŸ“¦ 100 Β· πŸ“‹ 39 - 30% open Β· ⏱️ 20.03.2024): ``` - git clone https://github.com/tensorflow/cloud + git clone https://github.com/PAIR-code/saliency ``` -- [PyPi](https://pypi.org/project/tensorflow-cloud) (πŸ“₯ 44K / month Β· πŸ“¦ 7 Β· ⏱️ 17.06.2021): +- [PyPi](https://pypi.org/project/saliency) (πŸ“₯ 42K / month Β· πŸ“¦ 8 Β· ⏱️ 20.03.2024): ``` - pip install tensorflow-cloud + pip install saliency ```
-
TF Compression (πŸ₯‰22 Β· ⭐ 830) - Data compression in TensorFlow. Apache-2 +
TF Compression (πŸ₯‰21 Β· ⭐ 850) - Data compression in TensorFlow. Apache-2 -- [GitHub](https://github.com/tensorflow/compression) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 250 Β· πŸ“‹ 100 - 9% open Β· ⏱️ 20.05.2024): +- [GitHub](https://github.com/tensorflow/compression) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 250 Β· πŸ“‹ 100 - 10% open Β· ⏱️ 07.08.2024): ``` git clone https://github.com/tensorflow/compression ``` -- [PyPi](https://pypi.org/project/tensorflow-compression) (πŸ“₯ 4.2K / month Β· πŸ“¦ 2 Β· ⏱️ 02.02.2024): +- [PyPi](https://pypi.org/project/tensorflow-compression) (πŸ“₯ 2.1K / month Β· πŸ“¦ 2 Β· ⏱️ 02.02.2024): ``` pip install tensorflow-compression ```
-
Saliency (πŸ₯‰21 Β· ⭐ 930) - Framework-agnostic implementation for state-of-the-art saliency.. Apache-2 +
TensorFlow Cloud (πŸ₯‰21 Β· ⭐ 370 Β· πŸ’€) - The TensorFlow Cloud repository provides APIs that.. Apache-2 -- [GitHub](https://github.com/PAIR-code/saliency) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 190 Β· πŸ“¦ 85 Β· πŸ“‹ 39 - 30% open Β· ⏱️ 20.03.2024): +- [GitHub](https://github.com/tensorflow/cloud) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 85 Β· πŸ“‹ 100 - 73% open Β· ⏱️ 25.02.2024): ``` - git clone https://github.com/PAIR-code/saliency + git clone https://github.com/tensorflow/cloud ``` -- [PyPi](https://pypi.org/project/saliency) (πŸ“₯ 5.6K / month Β· πŸ“¦ 8 Β· ⏱️ 20.03.2024): +- [PyPi](https://pypi.org/project/tensorflow-cloud) (πŸ“₯ 33K / month Β· πŸ“¦ 7 Β· ⏱️ 17.06.2021): ``` - pip install saliency + pip install tensorflow-cloud ```
Show 5 hidden projects... - tensor2tensor (πŸ₯ˆ32 Β· ⭐ 15K Β· πŸ’€) - Library of deep learning models and datasets designed.. Apache-2 -- Keras-Preprocessing (πŸ₯‰28 Β· ⭐ 1K Β· πŸ’€) - Utilities for working with image data, text data, and.. MIT -- efficientnet (πŸ₯‰27 Β· ⭐ 2.1K Β· πŸ’€) - Implementation of EfficientNet model. Keras and.. Apache-2 +- Keras-Preprocessing (πŸ₯ˆ28 Β· ⭐ 1K Β· πŸ’€) - Utilities for working with image data, text data, and.. MIT +- efficientnet (πŸ₯‰26 Β· ⭐ 2.1K Β· πŸ’€) - Implementation of EfficientNet model. Keras and.. Apache-2 - TensorNets (πŸ₯‰20 Β· ⭐ 1K Β· πŸ’€) - High level network definitions with pre-trained weights in.. MIT -- tffm (πŸ₯‰18 Β· ⭐ 780 Β· πŸ’€) - TensorFlow implementation of an arbitrary order Factorization Machine. MIT +- tffm (πŸ₯‰19 Β· ⭐ 780 Β· πŸ’€) - TensorFlow implementation of an arbitrary order Factorization Machine. MIT

@@ -7339,37 +7260,37 @@ _Libraries that extend TensorFlow with additional capabilities._ _Libraries that extend Jax with additional capabilities._ -
equinox (πŸ₯‡30 Β· ⭐ 1.9K) - Elegant easy-to-use neural networks + scientific computing in.. Apache-2 +
equinox (πŸ₯‡30 Β· ⭐ 2K) - Elegant easy-to-use neural networks + scientific computing in.. Apache-2 -- [GitHub](https://github.com/patrick-kidger/equinox) (πŸ‘¨β€πŸ’» 52 Β· πŸ”€ 130 Β· πŸ“¦ 580 Β· πŸ“‹ 360 - 33% open Β· ⏱️ 29.05.2024): +- [GitHub](https://github.com/patrick-kidger/equinox) (πŸ‘¨β€πŸ’» 55 Β· πŸ”€ 130 Β· πŸ“¦ 690 Β· πŸ“‹ 420 - 34% open Β· ⏱️ 03.09.2024): ``` git clone https://github.com/patrick-kidger/equinox ``` -- [PyPi](https://pypi.org/project/equinox) (πŸ“₯ 240K / month Β· πŸ“¦ 130 Β· ⏱️ 14.04.2024): +- [PyPi](https://pypi.org/project/equinox) (πŸ“₯ 92K / month Β· πŸ“¦ 150 Β· ⏱️ 18.08.2024): ``` pip install equinox ```
-
evojax (πŸ₯‰19 Β· ⭐ 790 Β· πŸ’€) - EvoJAX: Hardware-accelerated Neuroevolution. Apache-2 +
evojax (πŸ₯‰20 Β· ⭐ 830) - EvoJAX: Hardware-accelerated Neuroevolution. Apache-2 -- [GitHub](https://github.com/google/evojax) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 71 Β· πŸ“¦ 21 Β· πŸ“‹ 33 - 48% open Β· ⏱️ 29.08.2023): +- [GitHub](https://github.com/google/evojax) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 77 Β· πŸ“¦ 25 Β· πŸ“‹ 33 - 48% open Β· ⏱️ 27.06.2024): ``` git clone https://github.com/google/evojax ``` -- [PyPi](https://pypi.org/project/evojax) (πŸ“₯ 820 / month Β· πŸ“¦ 5 Β· ⏱️ 29.08.2023): +- [PyPi](https://pypi.org/project/evojax) (πŸ“₯ 1K / month Β· πŸ“¦ 6 Β· ⏱️ 18.06.2024): ``` pip install evojax ``` -- [Conda](https://anaconda.org/conda-forge/evojax) (πŸ“₯ 25K Β· ⏱️ 29.08.2023): +- [Conda](https://anaconda.org/conda-forge/evojax) (πŸ“₯ 29K Β· ⏱️ 18.06.2024): ``` conda install -c conda-forge evojax ```
Show 1 hidden projects... -- jaxdf (πŸ₯‰11 Β· ⭐ 110 Β· πŸ’€) - A JAX-based research framework for writing differentiable.. ❗️LGPL-3.0 +- jaxdf (πŸ₯‰11 Β· ⭐ 120 Β· πŸ’€) - A JAX-based research framework for writing differentiable.. ❗️LGPL-3.0

@@ -7379,135 +7300,146 @@ _Libraries that extend Jax with additional capabilities._ _Libraries that extend scikit-learn with additional capabilities._ -
imbalanced-learn (πŸ₯‡37 Β· ⭐ 6.7K) - A Python Package to Tackle the Curse of Imbalanced.. MIT +
imbalanced-learn (πŸ₯‡35 Β· ⭐ 6.8K) - A Python Package to Tackle the Curse of Imbalanced.. MIT -- [GitHub](https://github.com/scikit-learn-contrib/imbalanced-learn) (πŸ‘¨β€πŸ’» 84 Β· πŸ”€ 1.3K Β· πŸ“¦ 28K Β· πŸ“‹ 600 - 6% open Β· ⏱️ 28.05.2024): +- [GitHub](https://github.com/scikit-learn-contrib/imbalanced-learn) (πŸ‘¨β€πŸ’» 84 Β· πŸ”€ 1.3K Β· πŸ“¦ 31K Β· πŸ“‹ 600 - 7% open Β· ⏱️ 28.05.2024): ``` git clone https://github.com/scikit-learn-contrib/imbalanced-learn ``` -- [PyPi](https://pypi.org/project/imbalanced-learn) (πŸ“₯ 12M / month Β· πŸ“¦ 400 Β· ⏱️ 28.05.2024): +- [PyPi](https://pypi.org/project/imbalanced-learn) (πŸ“₯ 12M / month Β· πŸ“¦ 430 Β· ⏱️ 28.05.2024): ``` pip install imbalanced-learn ``` -- [Conda](https://anaconda.org/conda-forge/imbalanced-learn) (πŸ“₯ 570K Β· ⏱️ 28.05.2024): +- [Conda](https://anaconda.org/conda-forge/imbalanced-learn) (πŸ“₯ 610K Β· ⏱️ 28.05.2024): ``` conda install -c conda-forge imbalanced-learn ```
scikit-learn-intelex (πŸ₯‡35 Β· ⭐ 1.2K) - Intel(R) Extension for Scikit-learn is a seamless way.. Apache-2 -- [GitHub](https://github.com/intel/scikit-learn-intelex) (πŸ‘¨β€πŸ’» 79 Β· πŸ”€ 170 Β· πŸ“¦ 11K Β· πŸ“‹ 250 - 28% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/intel/scikit-learn-intelex) (πŸ‘¨β€πŸ’» 81 Β· πŸ”€ 170 Β· πŸ“¦ 12K Β· πŸ“‹ 280 - 32% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/intel/scikit-learn-intelex ``` -- [PyPi](https://pypi.org/project/scikit-learn-intelex) (πŸ“₯ 100K / month Β· πŸ“¦ 42 Β· ⏱️ 13.05.2024): +- [PyPi](https://pypi.org/project/scikit-learn-intelex) (πŸ“₯ 110K / month Β· πŸ“¦ 49 Β· ⏱️ 07.08.2024): ``` pip install scikit-learn-intelex ``` -- [Conda](https://anaconda.org/conda-forge/scikit-learn-intelex) (πŸ“₯ 270K Β· ⏱️ 19.04.2024): +- [Conda](https://anaconda.org/conda-forge/scikit-learn-intelex) (πŸ“₯ 330K Β· ⏱️ 20.08.2024): ``` conda install -c conda-forge scikit-learn-intelex ```
-
MLxtend (πŸ₯ˆ33 Β· ⭐ 4.8K) - A library of extension and helper modules for Pythons data.. BSD-3 +
MLxtend (πŸ₯ˆ32 Β· ⭐ 4.9K) - A library of extension and helper modules for Pythons data.. BSD-3 -- [GitHub](https://github.com/rasbt/mlxtend) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 840 Β· πŸ“¦ 14K Β· πŸ“‹ 480 - 29% open Β· ⏱️ 31.03.2024): +- [GitHub](https://github.com/rasbt/mlxtend) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 860 Β· πŸ“¦ 15K Β· πŸ“‹ 490 - 29% open Β· ⏱️ 02.07.2024): ``` git clone https://github.com/rasbt/mlxtend ``` -- [PyPi](https://pypi.org/project/mlxtend) (πŸ“₯ 630K / month Β· πŸ“¦ 160 Β· ⏱️ 05.01.2024): +- [PyPi](https://pypi.org/project/mlxtend) (πŸ“₯ 600K / month Β· πŸ“¦ 170 Β· ⏱️ 05.01.2024): ``` pip install mlxtend ``` -- [Conda](https://anaconda.org/conda-forge/mlxtend) (πŸ“₯ 310K Β· ⏱️ 05.01.2024): +- [Conda](https://anaconda.org/conda-forge/mlxtend) (πŸ“₯ 320K Β· ⏱️ 05.01.2024): ``` conda install -c conda-forge mlxtend ```
-
category_encoders (πŸ₯ˆ31 Β· ⭐ 2.4K) - A library of sklearn compatible categorical variable.. BSD-3 +
category_encoders (πŸ₯ˆ30 Β· ⭐ 2.4K) - A library of sklearn compatible categorical variable.. BSD-3 -- [GitHub](https://github.com/scikit-learn-contrib/category_encoders) (πŸ‘¨β€πŸ’» 70 Β· πŸ”€ 390 Β· πŸ“¦ 1.8K Β· πŸ“‹ 290 - 15% open Β· ⏱️ 09.04.2024): +- [GitHub](https://github.com/scikit-learn-contrib/category_encoders) (πŸ‘¨β€πŸ’» 70 Β· πŸ”€ 390 Β· πŸ“¦ 2.1K Β· πŸ“‹ 290 - 15% open Β· ⏱️ 09.04.2024): ``` git clone https://github.com/scikit-learn-contrib/category_encoders ``` -- [PyPi](https://pypi.org/project/category_encoders) (πŸ“₯ 1.6M / month Β· πŸ“¦ 240 Β· ⏱️ 29.10.2023): +- [PyPi](https://pypi.org/project/category_encoders) (πŸ“₯ 1.3M / month Β· πŸ“¦ 260 Β· ⏱️ 29.10.2023): ``` pip install category_encoders ``` -- [Conda](https://anaconda.org/conda-forge/category_encoders) (πŸ“₯ 260K Β· ⏱️ 30.10.2023): +- [Conda](https://anaconda.org/conda-forge/category_encoders) (πŸ“₯ 280K Β· ⏱️ 30.10.2023): ``` conda install -c conda-forge category_encoders ```
scikit-lego (πŸ₯ˆ28 Β· ⭐ 1.2K) - Extra blocks for scikit-learn pipelines. MIT -- [GitHub](https://github.com/koaning/scikit-lego) (πŸ‘¨β€πŸ’» 67 Β· πŸ”€ 110 Β· πŸ“¦ 150 Β· πŸ“‹ 310 - 11% open Β· ⏱️ 26.05.2024): +- [GitHub](https://github.com/koaning/scikit-lego) (πŸ‘¨β€πŸ’» 67 Β· πŸ”€ 120 Β· πŸ“¦ 160 Β· πŸ“‹ 320 - 9% open Β· ⏱️ 21.08.2024): ``` git clone https://github.com/koaning/scikit-lego ``` -- [PyPi](https://pypi.org/project/scikit-lego) (πŸ“₯ 22K / month Β· πŸ“¦ 11 Β· ⏱️ 25.05.2024): +- [PyPi](https://pypi.org/project/scikit-lego) (πŸ“₯ 27K / month Β· πŸ“¦ 11 Β· ⏱️ 10.07.2024): ``` pip install scikit-lego ``` -- [Conda](https://anaconda.org/conda-forge/scikit-lego) (πŸ“₯ 49K Β· ⏱️ 04.06.2024): +- [Conda](https://anaconda.org/conda-forge/scikit-lego) (πŸ“₯ 54K Β· ⏱️ 10.07.2024): ``` conda install -c conda-forge scikit-lego ```
-
scikit-opt (πŸ₯‰25 Β· ⭐ 5K Β· πŸ’€) - Genetic Algorithm, Particle Swarm Optimization, Simulated.. MIT +
scikit-opt (πŸ₯‰25 Β· ⭐ 5.2K) - Genetic Algorithm, Particle Swarm Optimization, Simulated.. MIT -- [GitHub](https://github.com/guofei9987/scikit-opt) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 960 Β· πŸ“¦ 200 Β· πŸ“‹ 180 - 36% open Β· ⏱️ 19.11.2023): +- [GitHub](https://github.com/guofei9987/scikit-opt) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 970 Β· πŸ“¦ 220 Β· πŸ“‹ 180 - 36% open Β· ⏱️ 23.06.2024): ``` git clone https://github.com/guofei9987/scikit-opt ``` -- [PyPi](https://pypi.org/project/scikit-opt) (πŸ“₯ 3.9K / month Β· πŸ“¦ 9 Β· ⏱️ 14.01.2022): +- [PyPi](https://pypi.org/project/scikit-opt) (πŸ“₯ 4.3K / month Β· πŸ“¦ 15 Β· ⏱️ 14.01.2022): ``` pip install scikit-opt ```
-
DESlib (πŸ₯‰21 Β· ⭐ 470) - A Python library for dynamic classifier and ensemble selection. BSD-3 +
dabl (πŸ₯‰20 Β· ⭐ 720 Β· πŸ’€) - Data Analysis Baseline Library. BSD-3 -- [GitHub](https://github.com/scikit-learn-contrib/DESlib) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 100 Β· πŸ“¦ 47 Β· πŸ“‹ 160 - 11% open Β· ⏱️ 15.04.2024): +- [GitHub](https://github.com/amueller/dabl) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 110 Β· ⏱️ 09.01.2024): ``` - git clone https://github.com/scikit-learn-contrib/DESlib + git clone https://github.com/amueller/dabl ``` -- [PyPi](https://pypi.org/project/deslib) (πŸ“₯ 990 / month Β· πŸ“¦ 3 Β· ⏱️ 12.04.2024): +- [PyPi](https://pypi.org/project/dabl) (πŸ“₯ 4.7K / month Β· πŸ“¦ 3 Β· ⏱️ 07.08.2024): ``` - pip install deslib + pip install dabl ```
-
scikit-tda (πŸ₯‰18 Β· ⭐ 500) - Topological Data Analysis for Python. MIT +
scikit-tda (πŸ₯‰19 Β· ⭐ 520) - Topological Data Analysis for Python. MIT -- [GitHub](https://github.com/scikit-tda/scikit-tda) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 51 Β· πŸ“¦ 56 Β· πŸ“‹ 22 - 54% open Β· ⏱️ 30.03.2024): +- [GitHub](https://github.com/scikit-tda/scikit-tda) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 54 Β· πŸ“¦ 60 Β· πŸ“‹ 22 - 18% open Β· ⏱️ 19.07.2024): ``` git clone https://github.com/scikit-tda/scikit-tda ``` -- [PyPi](https://pypi.org/project/scikit-tda) (πŸ“₯ 2.8K / month Β· ⏱️ 03.08.2021): +- [PyPi](https://pypi.org/project/scikit-tda) (πŸ“₯ 1.1K / month Β· ⏱️ 19.07.2024): ``` pip install scikit-tda ```
-
Show 11 hidden projects... +
DESlib (πŸ₯‰18 Β· ⭐ 480) - A Python library for dynamic classifier and ensemble selection. BSD-3 + +- [GitHub](https://github.com/scikit-learn-contrib/DESlib) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 100 Β· πŸ“‹ 160 - 11% open Β· ⏱️ 15.04.2024): + + ``` + git clone https://github.com/scikit-learn-contrib/DESlib + ``` +- [PyPi](https://pypi.org/project/deslib) (πŸ“₯ 740 / month Β· πŸ“¦ 3 Β· ⏱️ 12.04.2024): + ``` + pip install deslib + ``` +
+
Show 10 hidden projects... -- scikit-survival (πŸ₯ˆ29 Β· ⭐ 1.1K) - Survival analysis built on top of scikit-learn. ❗️GPL-3.0 -- scikit-multilearn (πŸ₯ˆ27 Β· ⭐ 910 Β· πŸ’€) - A scikit-learn based module for multi-label et. al... BSD-2 -- fancyimpute (πŸ₯ˆ26 Β· ⭐ 1.2K Β· πŸ’€) - Multivariate imputation and matrix completion.. Apache-2 -- sklearn-crfsuite (πŸ₯ˆ26 Β· ⭐ 420 Β· πŸ’€) - scikit-learn inspired API for CRFsuite. MIT +- scikit-survival (πŸ₯ˆ31 Β· ⭐ 1.1K) - Survival analysis built on top of scikit-learn. ❗️GPL-3.0 +- fancyimpute (πŸ₯ˆ27 Β· ⭐ 1.2K Β· πŸ’€) - Multivariate imputation and matrix completion.. Apache-2 +- sklearn-crfsuite (πŸ₯ˆ27 Β· ⭐ 430 Β· πŸ’€) - scikit-learn inspired API for CRFsuite. MIT +- scikit-multilearn (πŸ₯‰26 Β· ⭐ 920 Β· πŸ’€) - A scikit-learn based module for multi-label et. al... BSD-2 - sklearn-contrib-lightning (πŸ₯‰22 Β· ⭐ 1.7K Β· πŸ’€) - Large-scale linear classification, regression and.. BSD-3 -- iterative-stratification (πŸ₯‰21 Β· ⭐ 830 Β· πŸ’€) - scikit-learn cross validators for iterative.. BSD-3 +- iterative-stratification (πŸ₯‰21 Β· ⭐ 840 Β· πŸ’€) - scikit-learn cross validators for iterative.. BSD-3 - combo (πŸ₯‰21 Β· ⭐ 640 Β· πŸ’€) - (AAAI 20) A Python Toolbox for Machine Learning Model.. BSD-2 xgboost -- skope-rules (πŸ₯‰21 Β· ⭐ 600 Β· πŸ’€) - machine learning with logical rules in Python. ❗️BSD-1-Clause -- celer (πŸ₯‰18 Β· ⭐ 200) - Fast solver for L1-type problems: Lasso, sparse Logisitic regression,.. BSD-3 -- skggm (πŸ₯‰17 Β· ⭐ 240 Β· πŸ’€) - Scikit-learn compatible estimation of general graphical models. MIT -- dabl (πŸ₯‰15 Β· ⭐ 130) - Data Analysis Baseline Library. BSD-3 +- skope-rules (πŸ₯‰21 Β· ⭐ 610 Β· πŸ’€) - machine learning with logical rules in Python. ❗️BSD-1-Clause +- celer (πŸ₯‰19 Β· ⭐ 200) - Fast solver for L1-type problems: Lasso, sparse Logisitic regression,.. BSD-3 +- skggm (πŸ₯‰17 Β· ⭐ 240 Β· πŸ’€) - Scikit-learn compatible estimation of general graphical models. MIT

@@ -7517,201 +7449,171 @@ _Libraries that extend scikit-learn with additional capabilities._ _Libraries that extend Pytorch with additional capabilities._ -
accelerate (πŸ₯‡40 Β· ⭐ 7.2K) - A simple way to launch, train, and use PyTorch models on.. Apache-2 +
accelerate (πŸ₯‡40 Β· ⭐ 7.6K) - A simple way to launch, train, and use PyTorch models on.. Apache-2 -- [GitHub](https://github.com/huggingface/accelerate) (πŸ‘¨β€πŸ’» 250 Β· πŸ”€ 820 Β· πŸ“¦ 39K Β· πŸ“‹ 1.4K - 9% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/huggingface/accelerate) (πŸ‘¨β€πŸ’» 290 Β· πŸ”€ 920 Β· πŸ“¦ 49K Β· πŸ“‹ 1.6K - 9% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/huggingface/accelerate ``` -- [PyPi](https://pypi.org/project/accelerate) (πŸ“₯ 7.7M / month Β· πŸ“¦ 1.1K Β· ⏱️ 10.05.2024): +- [PyPi](https://pypi.org/project/accelerate) (πŸ“₯ 6.5M / month Β· πŸ“¦ 1.4K Β· ⏱️ 05.09.2024): ``` pip install accelerate ``` -- [Conda](https://anaconda.org/conda-forge/accelerate) (πŸ“₯ 140K Β· ⏱️ 11.05.2024): +- [Conda](https://anaconda.org/conda-forge/accelerate) (πŸ“₯ 200K Β· ⏱️ 03.09.2024): ``` conda install -c conda-forge accelerate ```
-
tinygrad (πŸ₯‡33 Β· ⭐ 25K) - You like pytorch? You like micrograd? You love tinygrad!. MIT - -- [GitHub](https://github.com/tinygrad/tinygrad) (πŸ‘¨β€πŸ’» 310 Β· πŸ”€ 2.7K Β· πŸ“¦ 69 Β· πŸ“‹ 620 - 14% open Β· ⏱️ 06.06.2024): - - ``` - git clone https://github.com/geohot/tinygrad - ``` -
-
PML (πŸ₯‡33 Β· ⭐ 5.8K) - The easiest way to use deep metric learning in your application. Modular,.. MIT +
PML (πŸ₯‡34 Β· ⭐ 5.9K) - The easiest way to use deep metric learning in your application. Modular,.. MIT -- [GitHub](https://github.com/KevinMusgrave/pytorch-metric-learning) (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 650 Β· πŸ“¦ 1.5K Β· πŸ“‹ 500 - 11% open Β· ⏱️ 01.04.2024): +- [GitHub](https://github.com/KevinMusgrave/pytorch-metric-learning) (πŸ‘¨β€πŸ’» 42 Β· πŸ”€ 660 Β· πŸ“¦ 1.8K Β· πŸ“‹ 500 - 12% open Β· ⏱️ 24.07.2024): ``` git clone https://github.com/KevinMusgrave/pytorch-metric-learning ``` -- [PyPi](https://pypi.org/project/pytorch-metric-learning) (πŸ“₯ 460K / month Β· πŸ“¦ 33 Β· ⏱️ 01.04.2024): +- [PyPi](https://pypi.org/project/pytorch-metric-learning) (πŸ“₯ 840K / month Β· πŸ“¦ 50 Β· ⏱️ 25.07.2024): ``` pip install pytorch-metric-learning ``` -- [Conda](https://anaconda.org/metric-learning/pytorch-metric-learning) (πŸ“₯ 11K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/metric-learning/pytorch-metric-learning) (πŸ“₯ 12K Β· ⏱️ 16.06.2023): ``` conda install -c metric-learning pytorch-metric-learning ```
-
torchdiffeq (πŸ₯‡31 Β· ⭐ 5.3K Β· πŸ’€) - Differentiable ODE solvers with full GPU support and.. MIT +
tinygrad (πŸ₯‡33 Β· ⭐ 26K) - You like pytorch? You like micrograd? You love tinygrad!. MIT + +- [GitHub](https://github.com/tinygrad/tinygrad) (πŸ‘¨β€πŸ’» 330 Β· πŸ”€ 2.8K Β· πŸ“¦ 93 Β· πŸ“‹ 710 - 14% open Β· ⏱️ 05.09.2024): + + ``` + git clone https://github.com/geohot/tinygrad + ``` +
+
torchdiffeq (πŸ₯‡31 Β· ⭐ 5.5K Β· πŸ’€) - Differentiable ODE solvers with full GPU support and.. MIT -- [GitHub](https://github.com/rtqichen/torchdiffeq) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 900 Β· πŸ“¦ 3.4K Β· πŸ“‹ 220 - 32% open Β· ⏱️ 19.10.2023): +- [GitHub](https://github.com/rtqichen/torchdiffeq) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 910 Β· πŸ“¦ 3.8K Β· πŸ“‹ 220 - 33% open Β· ⏱️ 19.10.2023): ``` git clone https://github.com/rtqichen/torchdiffeq ``` -- [PyPi](https://pypi.org/project/torchdiffeq) (πŸ“₯ 690K / month Β· πŸ“¦ 89 Β· ⏱️ 29.05.2024): +- [PyPi](https://pypi.org/project/torchdiffeq) (πŸ“₯ 820K / month Β· πŸ“¦ 100 Β· ⏱️ 29.05.2024): ``` pip install torchdiffeq ``` -- [Conda](https://anaconda.org/conda-forge/torchdiffeq) (πŸ“₯ 16K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/torchdiffeq) (πŸ“₯ 17K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge torchdiffeq ```
-
torchsde (πŸ₯ˆ29 Β· ⭐ 1.5K Β· πŸ’€) - Differentiable SDE solvers with GPU support and efficient.. Apache-2 +
torchsde (πŸ₯ˆ28 Β· ⭐ 1.5K Β· πŸ’€) - Differentiable SDE solvers with GPU support and efficient.. Apache-2 -- [GitHub](https://github.com/google-research/torchsde) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 190 Β· πŸ“¦ 3.1K Β· πŸ“‹ 76 - 31% open Β· ⏱️ 26.09.2023): +- [GitHub](https://github.com/google-research/torchsde) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 200 Β· πŸ“¦ 3.6K Β· πŸ“‹ 79 - 34% open Β· ⏱️ 26.09.2023): ``` git clone https://github.com/google-research/torchsde ``` -- [PyPi](https://pypi.org/project/torchsde) (πŸ“₯ 1.3M / month Β· πŸ“¦ 30 Β· ⏱️ 26.09.2023): +- [PyPi](https://pypi.org/project/torchsde) (πŸ“₯ 1.9M / month Β· πŸ“¦ 37 Β· ⏱️ 26.09.2023): ``` pip install torchsde ``` -- [Conda](https://anaconda.org/conda-forge/torchsde) (πŸ“₯ 22K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/torchsde) (πŸ“₯ 27K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge torchsde ```
-
pytorch-optimizer (πŸ₯ˆ28 Β· ⭐ 3K Β· πŸ’€) - torch-optimizer -- collection of optimizers for.. Apache-2 - -- [GitHub](https://github.com/jettify/pytorch-optimizer) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 290 Β· πŸ“¦ 1.2K Β· πŸ“‹ 83 - 63% open Β· ⏱️ 20.06.2023): - - ``` - git clone https://github.com/jettify/pytorch-optimizer - ``` -- [PyPi](https://pypi.org/project/torch_optimizer) (πŸ“₯ 120K / month Β· πŸ“¦ 84 Β· ⏱️ 31.10.2021): - ``` - pip install torch_optimizer - ``` -- [Conda](https://anaconda.org/conda-forge/torch-optimizer) (πŸ“₯ 10K Β· ⏱️ 16.06.2023): - ``` - conda install -c conda-forge torch-optimizer - ``` -
lightning-flash (πŸ₯ˆ27 Β· ⭐ 1.7K Β· πŸ’€) - Your PyTorch AI Factory - Flash enables you to easily.. Apache-2 -- [GitHub](https://github.com/Lightning-Universe/lightning-flash) (πŸ‘¨β€πŸ’» 87 Β· πŸ”€ 210 Β· πŸ“¦ 280 Β· πŸ“‹ 520 - 4% open Β· ⏱️ 08.10.2023): +- [GitHub](https://github.com/Lightning-Universe/lightning-flash) (πŸ‘¨β€πŸ’» 87 Β· πŸ”€ 210 Β· πŸ“¦ 290 Β· πŸ“‹ 520 - 4% open Β· ⏱️ 08.10.2023): ``` git clone https://github.com/Lightning-AI/lightning-flash ``` -- [PyPi](https://pypi.org/project/lightning-flash) (πŸ“₯ 2K / month Β· πŸ“¦ 5 Β· ⏱️ 11.05.2022): +- [PyPi](https://pypi.org/project/lightning-flash) (πŸ“₯ 1.4K / month Β· πŸ“¦ 5 Β· ⏱️ 11.05.2022): ``` pip install lightning-flash ``` -- [Conda](https://anaconda.org/conda-forge/lightning-flash) (πŸ“₯ 19K Β· ⏱️ 04.07.2023): +- [Conda](https://anaconda.org/conda-forge/lightning-flash) (πŸ“₯ 22K Β· ⏱️ 04.07.2023): ``` conda install -c conda-forge lightning-flash ```
-
TabNet (πŸ₯ˆ26 Β· ⭐ 2.5K Β· πŸ’€) - PyTorch implementation of TabNet paper :.. MIT - -- [GitHub](https://github.com/dreamquark-ai/tabnet) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 470 Β· πŸ“‹ 330 - 15% open Β· ⏱️ 23.07.2023): - - ``` - git clone https://github.com/dreamquark-ai/tabnet - ``` -- [PyPi](https://pypi.org/project/pytorch-tabnet) (πŸ“₯ 39K / month Β· πŸ“¦ 11 Β· ⏱️ 23.07.2023): - ``` - pip install pytorch-tabnet - ``` -- [Conda](https://anaconda.org/conda-forge/pytorch-tabnet) (πŸ“₯ 6.8K Β· ⏱️ 20.12.2023): - ``` - conda install -c conda-forge pytorch-tabnet - ``` -
-
torch-scatter (πŸ₯ˆ26 Β· ⭐ 1.5K) - PyTorch Extension Library of Optimized Scatter Operations. MIT +
torch-scatter (πŸ₯ˆ25 Β· ⭐ 1.5K) - PyTorch Extension Library of Optimized Scatter Operations. MIT -- [GitHub](https://github.com/rusty1s/pytorch_scatter) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 180 Β· πŸ“‹ 370 - 7% open Β· ⏱️ 27.05.2024): +- [GitHub](https://github.com/rusty1s/pytorch_scatter) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 180 Β· πŸ“‹ 390 - 7% open Β· ⏱️ 15.08.2024): ``` git clone https://github.com/rusty1s/pytorch_scatter ``` -- [PyPi](https://pypi.org/project/torch-scatter) (πŸ“₯ 37K / month Β· πŸ“¦ 130 Β· ⏱️ 06.10.2023): +- [PyPi](https://pypi.org/project/torch-scatter) (πŸ“₯ 34K / month Β· πŸ“¦ 150 Β· ⏱️ 06.10.2023): ``` pip install torch-scatter ``` -- [Conda](https://anaconda.org/conda-forge/pytorch_scatter) (πŸ“₯ 300K Β· ⏱️ 19.05.2024): +- [Conda](https://anaconda.org/conda-forge/pytorch_scatter) (πŸ“₯ 450K Β· ⏱️ 24.08.2024): ``` conda install -c conda-forge pytorch_scatter ```
-
PyTorch Sparse (πŸ₯‰23 Β· ⭐ 960) - PyTorch Extension Library of Optimized Autograd Sparse.. MIT +
EfficientNets (πŸ₯ˆ24 Β· ⭐ 1.6K) - Pretrained EfficientNet, EfficientNet-Lite, MixNet,.. Apache-2 -- [GitHub](https://github.com/rusty1s/pytorch_sparse) (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 140 Β· πŸ“‹ 270 - 11% open Β· ⏱️ 29.04.2024): +- [GitHub](https://github.com/rwightman/gen-efficientnet-pytorch) (πŸ‘¨β€πŸ’» 5 Β· πŸ”€ 210 Β· πŸ“¦ 250 Β· πŸ“‹ 55 - 7% open Β· ⏱️ 13.06.2024): ``` - git clone https://github.com/rusty1s/pytorch_sparse - ``` -- [PyPi](https://pypi.org/project/torch-sparse) (πŸ“₯ 25K / month Β· πŸ“¦ 100 Β· ⏱️ 06.10.2023): - ``` - pip install torch-sparse + git clone https://github.com/rwightman/gen-efficientnet-pytorch ``` -- [Conda](https://anaconda.org/conda-forge/pytorch_sparse) (πŸ“₯ 300K Β· ⏱️ 19.05.2024): +- [PyPi](https://pypi.org/project/geffnet) (πŸ“₯ 180K / month Β· πŸ“¦ 4 Β· ⏱️ 08.07.2021): ``` - conda install -c conda-forge pytorch_sparse + pip install geffnet ```
-
Pytorch Toolbelt (πŸ₯‰22 Β· ⭐ 1.5K) - PyTorch extensions for fast R&D prototyping and Kaggle.. MIT +
Pytorch Toolbelt (πŸ₯‰23 Β· ⭐ 1.5K) - PyTorch extensions for fast R&D prototyping and Kaggle.. MIT -- [GitHub](https://github.com/BloodAxe/pytorch-toolbelt) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 120 Β· πŸ“₯ 17 Β· πŸ“‹ 33 - 12% open Β· ⏱️ 18.04.2024): +- [GitHub](https://github.com/BloodAxe/pytorch-toolbelt) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 120 Β· πŸ“₯ 28 Β· πŸ“‹ 33 - 12% open Β· ⏱️ 01.09.2024): ``` git clone https://github.com/BloodAxe/pytorch-toolbelt ``` -- [PyPi](https://pypi.org/project/pytorch_toolbelt) (πŸ“₯ 6.1K / month Β· πŸ“¦ 7 Β· ⏱️ 27.06.2022): +- [PyPi](https://pypi.org/project/pytorch_toolbelt) (πŸ“₯ 7.3K / month Β· πŸ“¦ 7 Β· ⏱️ 27.06.2022): ``` pip install pytorch_toolbelt ```
-
reformer-pytorch (πŸ₯‰21 Β· ⭐ 2.1K Β· πŸ’€) - Reformer, the efficient Transformer, in Pytorch. MIT +
PyTorch Sparse (πŸ₯‰23 Β· ⭐ 990) - PyTorch Extension Library of Optimized Autograd Sparse.. MIT -- [GitHub](https://github.com/lucidrains/reformer-pytorch) (πŸ‘¨β€πŸ’» 11 Β· πŸ”€ 250 Β· πŸ“‹ 120 - 13% open Β· ⏱️ 21.06.2023): +- [GitHub](https://github.com/rusty1s/pytorch_sparse) (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 140 Β· πŸ“‹ 280 - 10% open Β· ⏱️ 15.08.2024): ``` - git clone https://github.com/lucidrains/reformer-pytorch + git clone https://github.com/rusty1s/pytorch_sparse + ``` +- [PyPi](https://pypi.org/project/torch-sparse) (πŸ“₯ 23K / month Β· πŸ“¦ 120 Β· ⏱️ 06.10.2023): ``` -- [PyPi](https://pypi.org/project/reformer-pytorch) (πŸ“₯ 11K / month Β· ⏱️ 06.11.2021): + pip install torch-sparse + ``` +- [Conda](https://anaconda.org/conda-forge/pytorch_sparse) (πŸ“₯ 420K Β· ⏱️ 19.05.2024): ``` - pip install reformer-pytorch + conda install -c conda-forge pytorch_sparse ```
-
Show 20 hidden projects... +
Show 22 hidden projects... - pretrainedmodels (πŸ₯ˆ29 Β· ⭐ 9K Β· πŸ’€) - Pretrained ConvNets for pytorch: NASNet, ResNeXt,.. BSD-3 - EfficientNet-PyTorch (πŸ₯ˆ27 Β· ⭐ 7.8K Β· πŸ’€) - A PyTorch implementation of EfficientNet. Apache-2 - pytorch-summary (πŸ₯ˆ27 Β· ⭐ 4K Β· πŸ’€) - Model summary in PyTorch similar to `model.summary()` in.. MIT -- EfficientNets (πŸ₯ˆ25 Β· ⭐ 1.6K Β· πŸ’€) - Pretrained EfficientNet, EfficientNet-Lite, MixNet,.. Apache-2 -- Higher (πŸ₯‰24 Β· ⭐ 1.6K Β· πŸ’€) - higher is a pytorch library allowing users to obtain higher.. Apache-2 +- pytorch-optimizer (πŸ₯ˆ26 Β· ⭐ 3K Β· πŸ’€) - torch-optimizer -- collection of optimizers for.. Apache-2 +- TabNet (πŸ₯ˆ26 Β· ⭐ 2.6K Β· πŸ’€) - PyTorch implementation of TabNet paper :.. MIT +- Higher (πŸ₯ˆ24 Β· ⭐ 1.6K Β· πŸ’€) - higher is a pytorch library allowing users to obtain higher.. Apache-2 - SRU (πŸ₯‰23 Β· ⭐ 2.1K Β· πŸ’€) - Training RNNs as Fast as CNNs (https://arxiv.org/abs/1709.02755). MIT -- Torchmeta (πŸ₯‰23 Β· ⭐ 1.9K Β· πŸ’€) - A collection of extensions and data-loaders for few-shot.. MIT -- Antialiased CNNs (πŸ₯‰22 Β· ⭐ 1.6K Β· πŸ’€) - pip install antialiased-cnns to improve stability and.. ❗️CC BY-NC-SA 4.0 -- micrograd (πŸ₯‰21 Β· ⭐ 8.6K Β· πŸ’€) - A tiny scalar-valued autograd engine and a neural net library.. MIT +- Torchmeta (πŸ₯‰23 Β· ⭐ 2K Β· πŸ’€) - A collection of extensions and data-loaders for few-shot.. MIT +- micrograd (πŸ₯‰22 Β· ⭐ 9.9K Β· πŸ’€) - A tiny scalar-valued autograd engine and a neural net library.. MIT +- Poutyne (πŸ₯‰22 Β· ⭐ 570) - A simplified framework and utilities for PyTorch. ❗️LGPL-3.0 - AdaBound (πŸ₯‰21 Β· ⭐ 2.9K Β· πŸ’€) - An optimizer that trains as fast as Adam and as good as SGD. Apache-2 -- pytorchviz (πŸ₯‰20 Β· ⭐ 3.1K Β· πŸ’€) - A small package to create visualizations of PyTorch execution.. MIT +- reformer-pytorch (πŸ₯‰21 Β· ⭐ 2.1K Β· πŸ’€) - Reformer, the efficient Transformer, in Pytorch. MIT +- Antialiased CNNs (πŸ₯‰21 Β· ⭐ 1.7K Β· πŸ’€) - pip install antialiased-cnns to improve stability and.. ❗️CC BY-NC-SA 4.0 - Lambda Networks (πŸ₯‰20 Β· ⭐ 1.5K Β· πŸ’€) - Implementation of LambdaNetworks, a new approach to.. MIT +- pytorchviz (πŸ₯‰19 Β· ⭐ 3.2K Β· πŸ’€) - A small package to create visualizations of PyTorch execution.. MIT +- Torch-Struct (πŸ₯‰19 Β· ⭐ 1.1K Β· πŸ’€) - Fast, general, and tested differentiable structured.. MIT - Performer Pytorch (πŸ₯‰19 Β· ⭐ 1.1K Β· πŸ’€) - An implementation of Performer, a linear attention-.. MIT -- Poutyne (πŸ₯‰19 Β· ⭐ 570 Β· πŸ’€) - A simplified framework and utilities for PyTorch. ❗️LGPL-3.0 -- Torch-Struct (πŸ₯‰18 Β· ⭐ 1.1K Β· πŸ’€) - Fast, general, and tested differentiable structured.. MIT +- Tensor Sensor (πŸ₯‰18 Β· ⭐ 770 Β· πŸ’€) - The goal of this library is to generate more helpful.. MIT - Tez (πŸ₯‰17 Β· ⭐ 1.2K Β· πŸ’€) - Tez is a super-simple and lightweight Trainer for PyTorch. It.. Apache-2 -- Tensor Sensor (πŸ₯‰17 Β· ⭐ 760 Β· πŸ’€) - The goal of this library is to generate more helpful.. MIT - madgrad (πŸ₯‰16 Β· ⭐ 800 Β· πŸ’€) - MADGRAD Optimization Method. MIT - Pywick (πŸ₯‰16 Β· ⭐ 400 Β· πŸ’€) - High-level batteries-included neural network training library for.. MIT - TorchDrift (πŸ₯‰15 Β· ⭐ 310 Β· πŸ’€) - Drift Detection for your PyTorch Models. Apache-2 @@ -7724,7 +7626,7 @@ _Libraries that extend Pytorch with additional capabilities._ _Libraries for connecting to, operating, and querying databases._ -πŸ”— best-of-python - DB Clients ( ⭐ 3.5K) - Collection of database clients for python. +πŸ”— best-of-python - DB Clients ( ⭐ 3.6K) - Collection of database clients for python.
@@ -7732,484 +7634,488 @@ _Libraries for connecting to, operating, and querying databases._ Back to top -
scipy (πŸ₯‡51 Β· ⭐ 13K) - Ecosystem of open-source software for mathematics, science, and engineering. BSD-3 +
scipy (πŸ₯‡50 Β· ⭐ 13K) - Ecosystem of open-source software for mathematics, science, and engineering. BSD-3 -- [GitHub](https://github.com/scipy/scipy) (πŸ‘¨β€πŸ’» 1.6K Β· πŸ”€ 5K Β· πŸ“₯ 400K Β· πŸ“¦ 1M Β· πŸ“‹ 10K - 17% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/scipy/scipy) (πŸ‘¨β€πŸ’» 1.7K Β· πŸ”€ 5.1K Β· πŸ“₯ 410K Β· πŸ“¦ 1.1M Β· πŸ“‹ 11K - 17% open Β· ⏱️ 04.09.2024): ``` git clone https://github.com/scipy/scipy ``` -- [PyPi](https://pypi.org/project/scipy) (πŸ“₯ 110M / month Β· πŸ“¦ 42K Β· ⏱️ 30.05.2024): +- [PyPi](https://pypi.org/project/scipy) (πŸ“₯ 120M / month Β· πŸ“¦ 45K Β· ⏱️ 21.08.2024): ``` pip install scipy ``` -- [Conda](https://anaconda.org/conda-forge/scipy) (πŸ“₯ 49M Β· ⏱️ 23.05.2024): +- [Conda](https://anaconda.org/conda-forge/scipy) (πŸ“₯ 52M Β· ⏱️ 22.08.2024): ``` conda install -c conda-forge scipy ```
-
SymPy (πŸ₯‡47 Β· ⭐ 12K Β· πŸ“‰) - A computer algebra system written in pure Python. BSD-3 +
SymPy (πŸ₯‡49 Β· ⭐ 13K) - A computer algebra system written in pure Python. BSD-3 -- [GitHub](https://github.com/sympy/sympy) (πŸ‘¨β€πŸ’» 1.3K Β· πŸ”€ 4.3K Β· πŸ“₯ 540K Β· πŸ“¦ 140K Β· πŸ“‹ 14K - 36% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/sympy/sympy) (πŸ‘¨β€πŸ’» 1.3K Β· πŸ”€ 4.4K Β· πŸ“₯ 550K Β· πŸ“¦ 170K Β· πŸ“‹ 14K - 36% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/sympy/sympy ``` -- [PyPi](https://pypi.org/project/sympy) (πŸ“₯ 23M / month Β· πŸ“¦ 3.1K Β· ⏱️ 06.06.2024): +- [PyPi](https://pypi.org/project/sympy) (πŸ“₯ 30M / month Β· πŸ“¦ 3.4K Β· ⏱️ 11.08.2024): ``` pip install sympy ``` -- [Conda](https://anaconda.org/conda-forge/sympy) (πŸ“₯ 5.7M Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/sympy) (πŸ“₯ 6.5M Β· ⏱️ 12.08.2024): ``` conda install -c conda-forge sympy ```
-
Streamlit (πŸ₯‡46 Β· ⭐ 33K) - Streamlit A faster way to build and share data apps. Apache-2 +
Streamlit (πŸ₯‡46 Β· ⭐ 34K) - Streamlit A faster way to build and share data apps. Apache-2 -- [GitHub](https://github.com/streamlit/streamlit) (πŸ‘¨β€πŸ’» 230 Β· πŸ”€ 2.8K Β· πŸ“¦ 400K Β· πŸ“‹ 4.2K - 19% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/streamlit/streamlit) (πŸ‘¨β€πŸ’» 240 Β· πŸ”€ 3K Β· πŸ“¦ 500K Β· πŸ“‹ 4.5K - 20% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/streamlit/streamlit ``` -- [PyPi](https://pypi.org/project/streamlit) (πŸ“₯ 4.9M / month Β· πŸ“¦ 2.3K Β· ⏱️ 23.05.2024): +- [PyPi](https://pypi.org/project/streamlit) (πŸ“₯ 5.6M / month Β· πŸ“¦ 2.7K Β· ⏱️ 27.08.2024): ``` pip install streamlit ```
-
Gradio (πŸ₯‡44 Β· ⭐ 30K) - Wrap UIs around any model, share with anyone. Apache-2 +
Gradio (πŸ₯‡43 Β· ⭐ 32K) - Wrap UIs around any model, share with anyone. Apache-2 -- [GitHub](https://github.com/gradio-app/gradio) (πŸ‘¨β€πŸ’» 330 Β· πŸ”€ 2.2K Β· πŸ“¦ 32K Β· πŸ“‹ 4.3K - 11% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/gradio-app/gradio) (πŸ‘¨β€πŸ’» 370 Β· πŸ”€ 2.4K Β· πŸ“¦ 40K Β· πŸ“‹ 4.7K - 11% open Β· ⏱️ 02.09.2024): ``` git clone https://github.com/gradio-app/gradio ``` -- [PyPi](https://pypi.org/project/gradio) (πŸ“₯ 7.5M / month Β· πŸ“¦ 580 Β· ⏱️ 05.06.2024): +- [PyPi](https://pypi.org/project/gradio) (πŸ“₯ 6.3M / month Β· πŸ“¦ 740 Β· ⏱️ 04.09.2024): ``` pip install gradio ```
carla (πŸ₯‡36 Β· ⭐ 11K) - Open-source simulator for autonomous driving research. MIT -- [GitHub](https://github.com/carla-simulator/carla) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 3.4K Β· πŸ“¦ 720 Β· πŸ“‹ 5.3K - 20% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/carla-simulator/carla) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 3.6K Β· πŸ“¦ 790 Β· πŸ“‹ 5.5K - 19% open Β· ⏱️ 29.08.2024): ``` git clone https://github.com/carla-simulator/carla ``` -- [PyPi](https://pypi.org/project/carla) (πŸ“₯ 13K / month Β· πŸ“¦ 7 Β· ⏱️ 14.11.2023): +- [PyPi](https://pypi.org/project/carla) (πŸ“₯ 10K / month Β· πŸ“¦ 11 Β· ⏱️ 14.11.2023): ``` pip install carla ```
-
DeepChem (πŸ₯‡36 Β· ⭐ 5.2K) - Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry,.. MIT +
Datasette (πŸ₯‡36 Β· ⭐ 9.2K Β· πŸ“ˆ) - An open source multi-tool for exploring and publishing data. Apache-2 -- [GitHub](https://github.com/deepchem/deepchem) (πŸ‘¨β€πŸ’» 240 Β· πŸ”€ 1.6K Β· πŸ“¦ 380 Β· πŸ“‹ 1.8K - 32% open Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/simonw/datasette) (πŸ‘¨β€πŸ’» 80 Β· πŸ”€ 660 Β· πŸ“₯ 67 Β· πŸ“¦ 1.3K Β· πŸ“‹ 1.9K - 31% open Β· ⏱️ 03.09.2024): ``` - git clone https://github.com/deepchem/deepchem + git clone https://github.com/simonw/datasette ``` -- [PyPi](https://pypi.org/project/deepchem) (πŸ“₯ 24K / month Β· πŸ“¦ 13 Β· ⏱️ 05.06.2024): +- [PyPi](https://pypi.org/project/datasette) (πŸ“₯ 60K / month Β· πŸ“¦ 410 Β· ⏱️ 16.08.2024): ``` - pip install deepchem + pip install datasette ``` -- [Conda](https://anaconda.org/conda-forge/deepchem) (πŸ“₯ 110K Β· ⏱️ 05.04.2024): +- [Conda](https://anaconda.org/conda-forge/datasette) (πŸ“₯ 42K Β· ⏱️ 24.06.2024): ``` - conda install -c conda-forge deepchem + conda install -c conda-forge datasette ```
-
PyOD (πŸ₯‡35 Β· ⭐ 8.1K) - A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly.. BSD-2 +
PyOD (πŸ₯‡36 Β· ⭐ 8.4K) - A Python Library for Outlier and Anomaly Detection, Integrating Classical.. BSD-2 -- [GitHub](https://github.com/yzhao062/pyod) (πŸ‘¨β€πŸ’» 53 Β· πŸ”€ 1.3K Β· πŸ“¦ 3.8K Β· πŸ“‹ 370 - 60% open Β· ⏱️ 01.06.2024): +- [GitHub](https://github.com/yzhao062/pyod) (πŸ‘¨β€πŸ’» 59 Β· πŸ”€ 1.4K Β· πŸ“¦ 4.1K Β· πŸ“‹ 370 - 60% open Β· ⏱️ 22.06.2024): ``` git clone https://github.com/yzhao062/pyod ``` -- [PyPi](https://pypi.org/project/pyod) (πŸ“₯ 680K / month Β· πŸ“¦ 110 Β· ⏱️ 01.06.2024): +- [PyPi](https://pypi.org/project/pyod) (πŸ“₯ 640K / month Β· πŸ“¦ 110 Β· ⏱️ 22.06.2024): ``` pip install pyod ``` -- [Conda](https://anaconda.org/conda-forge/pyod) (πŸ“₯ 100K Β· ⏱️ 01.06.2024): +- [Conda](https://anaconda.org/conda-forge/pyod) (πŸ“₯ 120K Β· ⏱️ 22.06.2024): ``` conda install -c conda-forge pyod ```
-
PennyLane (πŸ₯‡35 Β· ⭐ 2.2K) - PennyLane is a cross-platform Python library for quantum.. Apache-2 +
Autograd (πŸ₯‡36 Β· ⭐ 6.9K Β· πŸ“ˆ) - Efficiently computes derivatives of NumPy code. MIT -- [GitHub](https://github.com/PennyLaneAI/pennylane) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 550 Β· πŸ“₯ 78 Β· πŸ“¦ 920 Β· πŸ“‹ 1.3K - 23% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/HIPS/autograd) (πŸ‘¨β€πŸ’» 59 Β· πŸ”€ 900 Β· πŸ“¦ 9.3K Β· πŸ“‹ 420 - 42% open Β· ⏱️ 02.09.2024): ``` - git clone https://github.com/PennyLaneAI/PennyLane + git clone https://github.com/HIPS/autograd ``` -- [PyPi](https://pypi.org/project/pennylane) (πŸ“₯ 51K / month Β· πŸ“¦ 100 Β· ⏱️ 06.05.2024): +- [PyPi](https://pypi.org/project/autograd) (πŸ“₯ 1.8M / month Β· πŸ“¦ 280 Β· ⏱️ 22.08.2024): ``` - pip install pennylane + pip install autograd ``` -- [Conda](https://anaconda.org/conda-forge/pennylane) (πŸ“₯ 55K Β· ⏱️ 07.05.2024): +- [Conda](https://anaconda.org/conda-forge/autograd) (πŸ“₯ 470K Β· ⏱️ 26.08.2024): ``` - conda install -c conda-forge pennylane + conda install -c conda-forge autograd ```
-
agate (πŸ₯‡35 Β· ⭐ 1.2K) - A Python data analysis library that is optimized for humans instead of.. MIT +
DeepChem (πŸ₯‡36 Β· ⭐ 5.4K) - Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry,.. MIT -- [GitHub](https://github.com/wireservice/agate) (πŸ‘¨β€πŸ’» 53 Β· πŸ”€ 150 Β· πŸ“¦ 3.3K Β· πŸ“‹ 650 - 0% open Β· ⏱️ 27.05.2024): +- [GitHub](https://github.com/deepchem/deepchem) (πŸ‘¨β€πŸ’» 250 Β· πŸ”€ 1.6K Β· πŸ“¦ 420 Β· πŸ“‹ 1.9K - 33% open Β· ⏱️ 23.08.2024): ``` - git clone https://github.com/wireservice/agate + git clone https://github.com/deepchem/deepchem ``` -- [PyPi](https://pypi.org/project/agate) (πŸ“₯ 7.5M / month Β· πŸ“¦ 47 Β· ⏱️ 27.05.2024): +- [PyPi](https://pypi.org/project/deepchem) (πŸ“₯ 37K / month Β· πŸ“¦ 13 Β· ⏱️ 23.08.2024): ``` - pip install agate + pip install deepchem ``` -- [Conda](https://anaconda.org/conda-forge/agate) (πŸ“₯ 180K Β· ⏱️ 31.05.2024): +- [Conda](https://anaconda.org/conda-forge/deepchem) (πŸ“₯ 110K Β· ⏱️ 05.04.2024): ``` - conda install -c conda-forge agate + conda install -c conda-forge deepchem ```
-
Datasette (πŸ₯ˆ33 Β· ⭐ 9K) - An open source multi-tool for exploring and publishing data. Apache-2 +
PennyLane (πŸ₯ˆ34 Β· ⭐ 2.3K) - PennyLane is a cross-platform Python library for quantum.. Apache-2 -- [GitHub](https://github.com/simonw/datasette) (πŸ‘¨β€πŸ’» 78 Β· πŸ”€ 640 Β· πŸ“₯ 64 Β· πŸ“¦ 1.3K Β· πŸ“‹ 1.8K - 32% open Β· ⏱️ 22.04.2024): +- [GitHub](https://github.com/PennyLaneAI/pennylane) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 580 Β· πŸ“₯ 88 Β· πŸ“‹ 1.4K - 22% open Β· ⏱️ 05.09.2024): ``` - git clone https://github.com/simonw/datasette + git clone https://github.com/PennyLaneAI/PennyLane ``` -- [PyPi](https://pypi.org/project/datasette) (πŸ“₯ 38K / month Β· πŸ“¦ 390 Β· ⏱️ 13.03.2024): +- [PyPi](https://pypi.org/project/pennylane) (πŸ“₯ 66K / month Β· πŸ“¦ 110 Β· ⏱️ 03.09.2024): ``` - pip install datasette + pip install pennylane ``` -- [Conda](https://anaconda.org/conda-forge/datasette) (πŸ“₯ 35K Β· ⏱️ 03.01.2024): +- [Conda](https://anaconda.org/conda-forge/pennylane) (πŸ“₯ 130K Β· ⏱️ 09.07.2024): ``` - conda install -c conda-forge datasette + conda install -c conda-forge pennylane ```
-
Autograd (πŸ₯ˆ33 Β· ⭐ 6.8K) - Efficiently computes derivatives of numpy code. MIT +
hdbscan (πŸ₯ˆ33 Β· ⭐ 2.8K) - A high performance implementation of HDBSCAN clustering. BSD-3 -- [GitHub](https://github.com/HIPS/autograd) (πŸ‘¨β€πŸ’» 56 Β· πŸ”€ 870 Β· πŸ“¦ 8.3K Β· πŸ“‹ 410 - 42% open Β· ⏱️ 25.05.2024): +- [GitHub](https://github.com/scikit-learn-contrib/hdbscan) (πŸ‘¨β€πŸ’» 92 Β· πŸ”€ 490 Β· πŸ“¦ 4K Β· πŸ“‹ 530 - 67% open Β· ⏱️ 15.08.2024): ``` - git clone https://github.com/HIPS/autograd + git clone https://github.com/scikit-learn-contrib/hdbscan ``` -- [PyPi](https://pypi.org/project/autograd) (πŸ“₯ 1.3M / month Β· πŸ“¦ 270 Β· ⏱️ 23.06.2023): +- [PyPi](https://pypi.org/project/hdbscan) (πŸ“₯ 580K / month Β· πŸ“¦ 330 Β· ⏱️ 05.08.2024): ``` - pip install autograd + pip install hdbscan ``` -- [Conda](https://anaconda.org/conda-forge/autograd) (πŸ“₯ 430K Β· ⏱️ 26.06.2023): +- [Conda](https://anaconda.org/conda-forge/hdbscan) (πŸ“₯ 2.1M Β· ⏱️ 14.08.2024): ``` - conda install -c conda-forge autograd + conda install -c conda-forge hdbscan ```
-
hdbscan (πŸ₯ˆ33 Β· ⭐ 2.7K) - A high performance implementation of HDBSCAN clustering. BSD-3 +
Pythran (πŸ₯ˆ33 Β· ⭐ 2K) - Ahead of Time compiler for numeric kernels. BSD-3 -- [GitHub](https://github.com/scikit-learn-contrib/hdbscan) (πŸ‘¨β€πŸ’» 89 Β· πŸ”€ 490 Β· πŸ“¦ 3.6K Β· πŸ“‹ 520 - 67% open Β· ⏱️ 24.05.2024): +- [GitHub](https://github.com/serge-sans-paille/pythran) (πŸ‘¨β€πŸ’» 72 Β· πŸ”€ 190 Β· πŸ“¦ 2.6K Β· πŸ“‹ 860 - 15% open Β· ⏱️ 02.09.2024): ``` - git clone https://github.com/scikit-learn-contrib/hdbscan + git clone https://github.com/serge-sans-paille/pythran ``` -- [PyPi](https://pypi.org/project/hdbscan) (πŸ“₯ 740K / month Β· πŸ“¦ 300 Β· ⏱️ 24.05.2024): +- [PyPi](https://pypi.org/project/pythran) (πŸ“₯ 200K / month Β· πŸ“¦ 19 Β· ⏱️ 28.05.2024): ``` - pip install hdbscan + pip install pythran ``` -- [Conda](https://anaconda.org/conda-forge/hdbscan) (πŸ“₯ 1.9M Β· ⏱️ 24.05.2024): +- [Conda](https://anaconda.org/conda-forge/pythran) (πŸ“₯ 670K Β· ⏱️ 03.09.2024): ``` - conda install -c conda-forge hdbscan + conda install -c conda-forge pythran ```
-
Pythran (πŸ₯ˆ33 Β· ⭐ 2K) - Ahead of Time compiler for numeric kernels. BSD-3 +
tensorly (πŸ₯ˆ33 Β· ⭐ 1.5K) - TensorLy: Tensor Learning in Python. BSD-2 -- [GitHub](https://github.com/serge-sans-paille/pythran) (πŸ‘¨β€πŸ’» 72 Β· πŸ”€ 190 Β· πŸ“¦ 2.2K Β· πŸ“‹ 860 - 15% open Β· ⏱️ 28.05.2024): +- [GitHub](https://github.com/tensorly/tensorly) (πŸ‘¨β€πŸ’» 68 Β· πŸ”€ 290 Β· πŸ“¦ 730 Β· πŸ“‹ 270 - 21% open Β· ⏱️ 15.08.2024): ``` - git clone https://github.com/serge-sans-paille/pythran + git clone https://github.com/tensorly/tensorly ``` -- [PyPi](https://pypi.org/project/pythran) (πŸ“₯ 230K / month Β· πŸ“¦ 19 Β· ⏱️ 28.05.2024): +- [PyPi](https://pypi.org/project/tensorly) (πŸ“₯ 71K / month Β· πŸ“¦ 92 Β· ⏱️ 08.03.2023): ``` - pip install pythran + pip install tensorly ``` -- [Conda](https://anaconda.org/conda-forge/pythran) (πŸ“₯ 500K Β· ⏱️ 28.05.2024): +- [Conda](https://anaconda.org/conda-forge/tensorly) (πŸ“₯ 370K Β· ⏱️ 10.06.2024): ``` - conda install -c conda-forge pythran + conda install -c conda-forge tensorly + ``` +
+
agate (πŸ₯ˆ33 Β· ⭐ 1.2K) - A Python data analysis library that is optimized for humans instead of.. MIT + +- [GitHub](https://github.com/wireservice/agate) (πŸ‘¨β€πŸ’» 53 Β· πŸ”€ 160 Β· πŸ“¦ 3.7K Β· πŸ“‹ 650 - 0% open Β· ⏱️ 30.07.2024): + + ``` + git clone https://github.com/wireservice/agate + ``` +- [PyPi](https://pypi.org/project/agate) (πŸ“₯ 9.9M / month Β· πŸ“¦ 49 Β· ⏱️ 30.07.2024): + ``` + pip install agate + ``` +- [Conda](https://anaconda.org/conda-forge/agate) (πŸ“₯ 230K Β· ⏱️ 30.07.2024): + ``` + conda install -c conda-forge agate ```
-
pyopencl (πŸ₯ˆ33 Β· ⭐ 1K) - OpenCL integration for Python, plus shiny features. MIT +
pyopencl (πŸ₯ˆ32 Β· ⭐ 1.1K) - OpenCL integration for Python, plus shiny features. MIT -- [GitHub](https://github.com/inducer/pyopencl) (πŸ‘¨β€πŸ’» 96 Β· πŸ”€ 240 Β· πŸ“¦ 1.9K Β· πŸ“‹ 340 - 20% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/inducer/pyopencl) (πŸ‘¨β€πŸ’» 96 Β· πŸ”€ 240 Β· πŸ“¦ 2K Β· πŸ“‹ 350 - 21% open Β· ⏱️ 30.08.2024): ``` git clone https://github.com/inducer/pyopencl ``` -- [PyPi](https://pypi.org/project/pyopencl) (πŸ“₯ 54K / month Β· πŸ“¦ 160 Β· ⏱️ 05.06.2024): +- [PyPi](https://pypi.org/project/pyopencl) (πŸ“₯ 58K / month Β· πŸ“¦ 170 Β· ⏱️ 25.06.2024): ``` pip install pyopencl ``` -- [Conda](https://anaconda.org/conda-forge/pyopencl) (πŸ“₯ 1.1M Β· ⏱️ 09.05.2024): +- [Conda](https://anaconda.org/conda-forge/pyopencl) (πŸ“₯ 1.2M Β· ⏱️ 26.06.2024): ``` conda install -c conda-forge pyopencl ```
-
datalad (πŸ₯ˆ32 Β· ⭐ 500) - Keep code, data, containers under control with git and git-annex. MIT +
datalad (πŸ₯ˆ32 Β· ⭐ 520) - Keep code, data, containers under control with git and git-annex. MIT -- [GitHub](https://github.com/datalad/datalad) (πŸ‘¨β€πŸ’» 56 Β· πŸ”€ 110 Β· πŸ“¦ 400 Β· πŸ“‹ 3.9K - 13% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/datalad/datalad) (πŸ‘¨β€πŸ’» 57 Β· πŸ”€ 110 Β· πŸ“¦ 420 Β· πŸ“‹ 3.9K - 13% open Β· ⏱️ 31.08.2024): ``` git clone https://github.com/datalad/datalad ``` -- [PyPi](https://pypi.org/project/datalad) (πŸ“₯ 21K / month Β· πŸ“¦ 93 Β· ⏱️ 19.04.2024): +- [PyPi](https://pypi.org/project/datalad) (πŸ“₯ 22K / month Β· πŸ“¦ 95 Β· ⏱️ 08.08.2024): ``` pip install datalad ``` -- [Conda](https://anaconda.org/conda-forge/datalad) (πŸ“₯ 470K Β· ⏱️ 29.05.2024): +- [Conda](https://anaconda.org/conda-forge/datalad) (πŸ“₯ 590K Β· ⏱️ 08.08.2024): ``` conda install -c conda-forge datalad ```
-
River (πŸ₯ˆ31 Β· ⭐ 4.8K) - Online machine learning in Python. BSD-3 +
PaddleHub (πŸ₯ˆ31 Β· ⭐ 13K) - Awesome pre-trained models toolkit based on PaddlePaddle... Apache-2 + +- [GitHub](https://github.com/PaddlePaddle/PaddleHub) (πŸ‘¨β€πŸ’» 70 Β· πŸ”€ 2.1K Β· πŸ“₯ 750 Β· πŸ“¦ 1.7K Β· πŸ“‹ 1.3K - 44% open Β· ⏱️ 07.08.2024): + + ``` + git clone https://github.com/PaddlePaddle/PaddleHub + ``` +- [PyPi](https://pypi.org/project/paddlehub) (πŸ“₯ 5.7K / month Β· πŸ“¦ 7 Β· ⏱️ 20.09.2023): + ``` + pip install paddlehub + ``` +
+
River (πŸ₯ˆ31 Β· ⭐ 5K) - Online machine learning in Python. BSD-3 -- [GitHub](https://github.com/online-ml/river) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 530 Β· πŸ“¦ 490 Β· πŸ“‹ 590 - 18% open Β· ⏱️ 20.05.2024): +- [GitHub](https://github.com/online-ml/river) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 540 Β· πŸ“¦ 550 Β· πŸ“‹ 610 - 18% open Β· ⏱️ 04.09.2024): ``` git clone https://github.com/online-ml/river ``` -- [PyPi](https://pypi.org/project/river) (πŸ“₯ 40K / month Β· πŸ“¦ 51 Β· ⏱️ 23.04.2024): +- [PyPi](https://pypi.org/project/river) (πŸ“₯ 40K / month Β· πŸ“¦ 53 Β· ⏱️ 09.07.2024): ``` pip install river ``` -- [Conda](https://anaconda.org/conda-forge/river) (πŸ“₯ 60K Β· ⏱️ 06.10.2023): +- [Conda](https://anaconda.org/conda-forge/river) (πŸ“₯ 76K Β· ⏱️ 06.10.2023): ``` conda install -c conda-forge river ```
pyjanitor (πŸ₯ˆ31 Β· ⭐ 1.3K) - Clean APIs for data cleaning. Python implementation of R package.. MIT -- [GitHub](https://github.com/pyjanitor-devs/pyjanitor) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 160 Β· πŸ“¦ 620 Β· πŸ“‹ 560 - 20% open Β· ⏱️ 04.06.2024): +- [GitHub](https://github.com/pyjanitor-devs/pyjanitor) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 160 Β· πŸ“¦ 670 Β· πŸ“‹ 560 - 19% open Β· ⏱️ 20.08.2024): ``` git clone https://github.com/pyjanitor-devs/pyjanitor ``` -- [PyPi](https://pypi.org/project/pyjanitor) (πŸ“₯ 76K / month Β· πŸ“¦ 28 Β· ⏱️ 21.03.2024): +- [PyPi](https://pypi.org/project/pyjanitor) (πŸ“₯ 83K / month Β· πŸ“¦ 29 Β· ⏱️ 09.08.2024): ``` pip install pyjanitor ``` -- [Conda](https://anaconda.org/conda-forge/pyjanitor) (πŸ“₯ 200K Β· ⏱️ 21.03.2024): +- [Conda](https://anaconda.org/conda-forge/pyjanitor) (πŸ“₯ 210K Β· ⏱️ 09.08.2024): ``` conda install -c conda-forge pyjanitor ```
-
causalml (πŸ₯ˆ30 Β· ⭐ 4.8K) - Uplift modeling and causal inference with machine learning.. Apache-2 +
causalml (πŸ₯ˆ29 Β· ⭐ 5K) - Uplift modeling and causal inference with machine learning algorithms. Apache-2 -- [GitHub](https://github.com/uber/causalml) (πŸ‘¨β€πŸ’» 62 Β· πŸ”€ 740 Β· πŸ“¦ 200 Β· πŸ“‹ 390 - 14% open Β· ⏱️ 09.05.2024): +- [GitHub](https://github.com/uber/causalml) (πŸ‘¨β€πŸ’» 63 Β· πŸ”€ 760 Β· πŸ“¦ 220 Β· πŸ“‹ 390 - 13% open Β· ⏱️ 01.08.2024): ``` git clone https://github.com/uber/causalml ``` -- [PyPi](https://pypi.org/project/causalml) (πŸ“₯ 45K / month Β· πŸ“¦ 1 Β· ⏱️ 19.04.2024): +- [PyPi](https://pypi.org/project/causalml) (πŸ“₯ 47K / month Β· πŸ“¦ 1 Β· ⏱️ 19.04.2024): ``` pip install causalml ```
-
anomalib (πŸ₯ˆ30 Β· ⭐ 3.3K) - An anomaly detection library comprising state-of-the-art algorithms.. Apache-2 +
anomalib (πŸ₯ˆ29 Β· ⭐ 3.6K) - An anomaly detection library comprising state-of-the-art algorithms.. Apache-2 -- [GitHub](https://github.com/openvinotoolkit/anomalib) (πŸ‘¨β€πŸ’» 79 Β· πŸ”€ 590 Β· πŸ“₯ 11K Β· πŸ“¦ 73 Β· πŸ“‹ 840 - 14% open Β· ⏱️ 06.06.2024): +- [GitHub](https://github.com/openvinotoolkit/anomalib) (πŸ‘¨β€πŸ’» 80 Β· πŸ”€ 640 Β· πŸ“₯ 13K Β· πŸ“¦ 87 Β· πŸ“‹ 880 - 13% open Β· ⏱️ 03.09.2024): ``` git clone https://github.com/openvinotoolkit/anomalib ``` -- [PyPi](https://pypi.org/project/anomalib) (πŸ“₯ 17K / month Β· πŸ“¦ 5 Β· ⏱️ 31.05.2024): +- [PyPi](https://pypi.org/project/anomalib) (πŸ“₯ 27K / month Β· πŸ“¦ 5 Β· ⏱️ 12.08.2024): ``` pip install anomalib ```
-
tensorly (πŸ₯ˆ30 Β· ⭐ 1.5K) - TensorLy: Tensor Learning in Python. BSD-2 - -- [GitHub](https://github.com/tensorly/tensorly) (πŸ‘¨β€πŸ’» 67 Β· πŸ”€ 270 Β· πŸ“¦ 660 Β· πŸ“‹ 260 - 23% open Β· ⏱️ 11.04.2024): - - ``` - git clone https://github.com/tensorly/tensorly - ``` -- [PyPi](https://pypi.org/project/tensorly) (πŸ“₯ 30K / month Β· πŸ“¦ 80 Β· ⏱️ 08.03.2023): - ``` - pip install tensorly - ``` -- [Conda](https://anaconda.org/conda-forge/tensorly) (πŸ“₯ 360K Β· ⏱️ 16.06.2023): - ``` - conda install -c conda-forge tensorly - ``` -
-
kmodes (πŸ₯ˆ29 Β· ⭐ 1.2K) - Python implementations of the k-modes and k-prototypes clustering.. MIT +
TabPy (πŸ₯ˆ29 Β· ⭐ 1.5K) - Execute Python code on the fly and display results in Tableau visualizations:. MIT -- [GitHub](https://github.com/nicodv/kmodes) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 410 Β· πŸ“¦ 2.6K Β· πŸ“‹ 160 - 10% open Β· ⏱️ 17.01.2024): +- [GitHub](https://github.com/tableau/TabPy) (πŸ‘¨β€πŸ’» 51 Β· πŸ”€ 590 Β· πŸ“¦ 170 Β· πŸ“‹ 320 - 6% open Β· ⏱️ 05.09.2024): ``` - git clone https://github.com/nicodv/kmodes + git clone https://github.com/tableau/TabPy ``` -- [PyPi](https://pypi.org/project/kmodes) (πŸ“₯ 320K / month Β· πŸ“¦ 38 Β· ⏱️ 06.09.2022): +- [PyPi](https://pypi.org/project/tabpy) (πŸ“₯ 6.9K / month Β· πŸ“¦ 2 Β· ⏱️ 05.09.2024): ``` - pip install kmodes + pip install tabpy ``` -- [Conda](https://anaconda.org/conda-forge/kmodes) (πŸ“₯ 43K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/anaconda/tabpy-client) (πŸ“₯ 4.6K Β· ⏱️ 16.06.2023): ``` - conda install -c conda-forge kmodes + conda install -c anaconda tabpy-client ```
-
adapter-transformers (πŸ₯ˆ28 Β· ⭐ 2.4K) - A Unified Library for Parameter-Efficient and Modular.. Apache-2 huggingface +
dstack (πŸ₯ˆ28 Β· ⭐ 1.3K) - A lightweight alternative to Kubernetes for AI, simplifying container.. MPL-2.0 -- [GitHub](https://github.com/adapter-hub/adapters) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 320 Β· πŸ“¦ 61 Β· πŸ“‹ 370 - 10% open Β· ⏱️ 21.05.2024): +- [GitHub](https://github.com/dstackai/dstack) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 98 Β· πŸ“¦ 15 Β· πŸ“‹ 880 - 10% open Β· ⏱️ 05.09.2024): ``` - git clone https://github.com/Adapter-Hub/adapter-transformers + git clone https://github.com/dstackai/dstack ``` -- [PyPi](https://pypi.org/project/adapter-transformers) (πŸ“₯ 92K / month Β· πŸ“¦ 7 Β· ⏱️ 16.12.2023): +- [PyPi](https://pypi.org/project/dstack) (πŸ“₯ 3.6K / month Β· ⏱️ 04.09.2024): ``` - pip install adapter-transformers + pip install dstack ```
-
avalanche (πŸ₯ˆ28 Β· ⭐ 1.7K) - Avalanche: an End-to-End Library for Continual Learning based on.. MIT +
kmodes (πŸ₯ˆ28 Β· ⭐ 1.2K Β· πŸ’€) - Python implementations of the k-modes and k-prototypes clustering.. MIT -- [GitHub](https://github.com/ContinualAI/avalanche) (πŸ‘¨β€πŸ’» 78 Β· πŸ”€ 280 Β· πŸ“₯ 21 Β· πŸ“¦ 83 Β· πŸ“‹ 800 - 11% open Β· ⏱️ 03.06.2024): +- [GitHub](https://github.com/nicodv/kmodes) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 420 Β· πŸ“¦ 2.8K Β· πŸ“‹ 160 - 10% open Β· ⏱️ 17.01.2024): ``` - git clone https://github.com/ContinualAI/avalanche - ``` -- [PyPi](https://pypi.org/project/avalanche-lib) (πŸ“₯ 970 / month Β· πŸ“¦ 3 Β· ⏱️ 27.02.2024): - ``` - pip install avalanche-lib + git clone https://github.com/nicodv/kmodes ``` -
-
dstack (πŸ₯ˆ28 Β· ⭐ 1.1K) - An open-source container orchestration engine for running AI workloads.. MPL-2.0 - -- [GitHub](https://github.com/dstackai/dstack) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 80 Β· πŸ“¦ 14 Β· πŸ“‹ 710 - 5% open Β· ⏱️ 06.06.2024): - +- [PyPi](https://pypi.org/project/kmodes) (πŸ“₯ 240K / month Β· πŸ“¦ 38 Β· ⏱️ 06.09.2022): ``` - git clone https://github.com/dstackai/dstack + pip install kmodes ``` -- [PyPi](https://pypi.org/project/dstack) (πŸ“₯ 2K / month Β· ⏱️ 06.06.2024): +- [Conda](https://anaconda.org/conda-forge/kmodes) (πŸ“₯ 48K Β· ⏱️ 16.06.2023): ``` - pip install dstack + conda install -c conda-forge kmodes ```
-
PySwarms (πŸ₯‰27 Β· ⭐ 1.2K Β· πŸ’€) - A research toolkit for particle swarm optimization in Python. MIT +
adapter-transformers (πŸ₯‰27 Β· ⭐ 2.5K) - A Unified Library for Parameter-Efficient and Modular.. Apache-2 huggingface -- [GitHub](https://github.com/ljvmiranda921/pyswarms) (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 330 Β· πŸ“¦ 390 Β· πŸ“‹ 230 - 12% open Β· ⏱️ 06.06.2023): +- [GitHub](https://github.com/adapter-hub/adapters) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 340 Β· πŸ“¦ 96 Β· πŸ“‹ 380 - 10% open Β· ⏱️ 22.08.2024): ``` - git clone https://github.com/ljvmiranda921/pyswarms + git clone https://github.com/Adapter-Hub/adapter-transformers ``` -- [PyPi](https://pypi.org/project/pyswarms) (πŸ“₯ 22K / month Β· πŸ“¦ 22 Β· ⏱️ 03.01.2021): +- [PyPi](https://pypi.org/project/adapter-transformers) (πŸ“₯ 21K / month Β· πŸ“¦ 12 Β· ⏱️ 07.07.2024): ``` - pip install pyswarms + pip install adapter-transformers ```
-
pyclustering (πŸ₯‰27 Β· ⭐ 1.1K) - pyclustering is a Python, C++ data mining library. BSD-3 +
pyclustering (πŸ₯‰27 Β· ⭐ 1.2K Β· πŸ’€) - pyclustering is a Python, C++ data mining library. BSD-3 -- [GitHub](https://github.com/annoviko/pyclustering) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 250 Β· πŸ“₯ 540 Β· πŸ“¦ 680 Β· πŸ“‹ 660 - 10% open Β· ⏱️ 08.02.2024): +- [GitHub](https://github.com/annoviko/pyclustering) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 250 Β· πŸ“₯ 580 Β· πŸ“¦ 720 Β· πŸ“‹ 670 - 11% open Β· ⏱️ 08.02.2024): ``` git clone https://github.com/annoviko/pyclustering ``` -- [PyPi](https://pypi.org/project/pyclustering) (πŸ“₯ 43K / month Β· πŸ“¦ 29 Β· ⏱️ 25.11.2020): +- [PyPi](https://pypi.org/project/pyclustering) (πŸ“₯ 24K / month Β· πŸ“¦ 32 Β· ⏱️ 25.11.2020): ``` pip install pyclustering ``` -- [Conda](https://anaconda.org/conda-forge/pyclustering) (πŸ“₯ 67K Β· ⏱️ 16.11.2023): +- [Conda](https://anaconda.org/conda-forge/pyclustering) (πŸ“₯ 84K Β· ⏱️ 16.11.2023): ``` conda install -c conda-forge pyclustering ```
-
modAL (πŸ₯‰26 Β· ⭐ 2.2K Β· πŸ’€) - A modular active learning framework for Python. MIT +
Trax (πŸ₯‰26 Β· ⭐ 8K) - Trax Deep Learning with Clear Code and Speed. Apache-2 -- [GitHub](https://github.com/modAL-python/modAL) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 320 Β· πŸ“₯ 35 Β· πŸ“‹ 160 - 63% open Β· ⏱️ 01.06.2023): +- [GitHub](https://github.com/google/trax) (πŸ‘¨β€πŸ’» 80 Β· πŸ”€ 810 Β· πŸ“¦ 170 Β· πŸ“‹ 250 - 49% open Β· ⏱️ 21.08.2024): ``` - git clone https://github.com/modAL-python/modAL + git clone https://github.com/google/trax ``` -- [PyPi](https://pypi.org/project/modAL) (πŸ“₯ 280K / month Β· πŸ“¦ 41 Β· ⏱️ 06.06.2024): +- [PyPi](https://pypi.org/project/trax) (πŸ“₯ 4.1K / month Β· πŸ“¦ 1 Β· ⏱️ 26.10.2021): ``` - pip install modAL + pip install trax ```
-
TabPy (πŸ₯‰26 Β· ⭐ 1.5K) - Execute Python code on the fly and display results in Tableau visualizations:. MIT +
Feature Engine (πŸ₯‰26 Β· ⭐ 1.8K) - Feature engineering package with sklearn like functionality. BSD-3 -- [GitHub](https://github.com/tableau/TabPy) (πŸ‘¨β€πŸ’» 50 Β· πŸ”€ 580 Β· πŸ“¦ 160 Β· πŸ“‹ 320 - 5% open Β· ⏱️ 04.01.2024): +- [GitHub](https://github.com/solegalli/feature_engine) (πŸ‘¨β€πŸ’» 49 Β· πŸ”€ 310 Β· ⏱️ 31.08.2024): ``` - git clone https://github.com/tableau/TabPy + git clone https://github.com/solegalli/feature_engine ``` -- [PyPi](https://pypi.org/project/tabpy) (πŸ“₯ 8.5K / month Β· πŸ“¦ 2 Β· ⏱️ 30.01.2023): +- [PyPi](https://pypi.org/project/feature_engine) (πŸ“₯ 150K / month Β· πŸ“¦ 160 Β· ⏱️ 31.08.2024): ``` - pip install tabpy + pip install feature_engine ``` -- [Conda](https://anaconda.org/anaconda/tabpy-client) (πŸ“₯ 4.5K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/feature_engine) (πŸ“₯ 56K Β· ⏱️ 01.09.2024): ``` - conda install -c anaconda tabpy-client + conda install -c conda-forge feature_engine ```
-
pycm (πŸ₯‰26 Β· ⭐ 1.4K Β· πŸ’€) - Multi-class confusion matrix library in Python. MIT +
avalanche (πŸ₯‰26 Β· ⭐ 1.7K) - Avalanche: an End-to-End Library for Continual Learning based on.. MIT -- [GitHub](https://github.com/sepandhaghighi/pycm) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 120 Β· πŸ“¦ 300 Β· πŸ“‹ 200 - 5% open Β· ⏱️ 07.06.2023): +- [GitHub](https://github.com/ContinualAI/avalanche) (πŸ‘¨β€πŸ’» 78 Β· πŸ”€ 280 Β· πŸ“₯ 27 Β· πŸ“¦ 100 Β· πŸ“‹ 810 - 11% open Β· ⏱️ 03.06.2024): ``` - git clone https://github.com/sepandhaghighi/pycm + git clone https://github.com/ContinualAI/avalanche ``` -- [PyPi](https://pypi.org/project/pycm) (πŸ“₯ 40K / month Β· πŸ“¦ 22 Β· ⏱️ 07.06.2023): +- [PyPi](https://pypi.org/project/avalanche-lib) (πŸ“₯ 1.6K / month Β· πŸ“¦ 3 Β· ⏱️ 27.02.2024): ``` - pip install pycm + pip install avalanche-lib ```
-
metric-learn (πŸ₯‰26 Β· ⭐ 1.4K Β· πŸ’€) - Metric learning algorithms in Python. MIT +
metric-learn (πŸ₯‰25 Β· ⭐ 1.4K) - Metric learning algorithms in Python. MIT -- [GitHub](https://github.com/scikit-learn-contrib/metric-learn) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 230 Β· πŸ“¦ 380 Β· πŸ“‹ 170 - 30% open Β· ⏱️ 29.09.2023): +- [GitHub](https://github.com/scikit-learn-contrib/metric-learn) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 230 Β· πŸ“¦ 400 Β· πŸ“‹ 170 - 30% open Β· ⏱️ 03.08.2024): ``` git clone https://github.com/scikit-learn-contrib/metric-learn ``` -- [PyPi](https://pypi.org/project/metric-learn) (πŸ“₯ 16K / month Β· πŸ“¦ 7 Β· ⏱️ 09.10.2023): +- [PyPi](https://pypi.org/project/metric-learn) (πŸ“₯ 6.4K / month Β· πŸ“¦ 7 Β· ⏱️ 09.10.2023): ``` pip install metric-learn ``` -- [Conda](https://anaconda.org/conda-forge/metric-learn) (πŸ“₯ 12K Β· ⏱️ 09.10.2023): +- [Conda](https://anaconda.org/conda-forge/metric-learn) (πŸ“₯ 13K Β· ⏱️ 09.10.2023): ``` conda install -c conda-forge metric-learn ```
-
Prince (πŸ₯‰26 Β· ⭐ 1.2K) - Multivariate exploratory data analysis in Python PCA, CA, MCA, MFA,.. MIT +
Prince (πŸ₯‰25 Β· ⭐ 1.2K) - Multivariate exploratory data analysis in Python PCA, CA, MCA, MFA,.. MIT -- [GitHub](https://github.com/MaxHalford/prince) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 180 Β· πŸ“¦ 540 Β· πŸ“‹ 130 - 3% open Β· ⏱️ 16.04.2024): +- [GitHub](https://github.com/MaxHalford/prince) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 180 Β· πŸ“¦ 600 Β· πŸ“‹ 130 - 3% open Β· ⏱️ 10.06.2024): ``` git clone https://github.com/MaxHalford/prince ``` -- [PyPi](https://pypi.org/project/prince) (πŸ“₯ 140K / month Β· πŸ“¦ 16 Β· ⏱️ 11.10.2023): +- [PyPi](https://pypi.org/project/prince) (πŸ“₯ 150K / month Β· πŸ“¦ 18 Β· ⏱️ 11.10.2023): ``` pip install prince ``` -- [Conda](https://anaconda.org/conda-forge/prince-factor-analysis) (πŸ“₯ 19K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/prince-factor-analysis) (πŸ“₯ 20K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge prince-factor-analysis ```
-
Trax (πŸ₯‰25 Β· ⭐ 8K) - Trax Deep Learning with Clear Code and Speed. Apache-2 +
BioPandas (πŸ₯‰25 Β· ⭐ 710) - Working with molecular structures in pandas DataFrames. BSD-3 -- [GitHub](https://github.com/google/trax) (πŸ‘¨β€πŸ’» 79 Β· πŸ”€ 810 Β· πŸ“¦ 160 Β· πŸ“‹ 240 - 47% open Β· ⏱️ 16.05.2024): +- [GitHub](https://github.com/BioPandas/biopandas) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 120 Β· πŸ“¦ 280 Β· πŸ“‹ 59 - 35% open Β· ⏱️ 01.08.2024): ``` - git clone https://github.com/google/trax + git clone https://github.com/rasbt/biopandas ``` -- [PyPi](https://pypi.org/project/trax) (πŸ“₯ 3.3K / month Β· πŸ“¦ 1 Β· ⏱️ 26.10.2021): +- [PyPi](https://pypi.org/project/biopandas) (πŸ“₯ 66K / month Β· πŸ“¦ 38 Β· ⏱️ 01.08.2024): ``` - pip install trax + pip install biopandas + ``` +- [Conda](https://anaconda.org/conda-forge/biopandas) (πŸ“₯ 160K Β· ⏱️ 02.08.2024): + ``` + conda install -c conda-forge biopandas ```
-
gplearn (πŸ₯‰25 Β· ⭐ 1.6K Β· πŸ’€) - Genetic Programming in Python, with a scikit-learn inspired API. BSD-3 +
AugLy (πŸ₯‰24 Β· ⭐ 4.9K) - A data augmentations library for audio, image, text, and video. MIT -- [GitHub](https://github.com/trevorstephens/gplearn) (πŸ‘¨β€πŸ’» 11 Β· πŸ”€ 270 Β· πŸ“¦ 580 Β· πŸ“‹ 210 - 10% open Β· ⏱️ 12.08.2023): +- [GitHub](https://github.com/facebookresearch/AugLy) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 300 Β· πŸ“¦ 140 Β· πŸ“‹ 78 - 30% open Β· ⏱️ 23.08.2024): ``` - git clone https://github.com/trevorstephens/gplearn - ``` -- [PyPi](https://pypi.org/project/gplearn) (πŸ“₯ 7.2K / month Β· πŸ“¦ 17 Β· ⏱️ 03.05.2022): - ``` - pip install gplearn + git clone https://github.com/facebookresearch/AugLy ``` -- [Conda](https://anaconda.org/conda-forge/gplearn) (πŸ“₯ 7K Β· ⏱️ 16.06.2023): +- [PyPi](https://pypi.org/project/augly) (πŸ“₯ 2.9K / month Β· πŸ“¦ 4 Β· ⏱️ 05.12.2023): ``` - conda install -c conda-forge gplearn + pip install augly ```
Mars (πŸ₯‰24 Β· ⭐ 2.7K Β· πŸ’€) - Mars is a tensor-based unified framework for large-scale data.. Apache-2 @@ -8219,162 +8125,125 @@ _Libraries for connecting to, operating, and querying databases._ ``` git clone https://github.com/mars-project/mars ``` -- [PyPi](https://pypi.org/project/pymars) (πŸ“₯ 15K / month Β· πŸ“¦ 1 Β· ⏱️ 12.06.2022): +- [PyPi](https://pypi.org/project/pymars) (πŸ“₯ 14K / month Β· πŸ“¦ 2 Β· ⏱️ 12.06.2022): ``` pip install pymars ```
-
AugLy (πŸ₯‰23 Β· ⭐ 4.9K Β· πŸ“‰) - A data augmentations library for audio, image, text, and video. MIT +
MONAILabel (πŸ₯‰23 Β· ⭐ 590) - MONAI Label is an intelligent open source image labeling and.. Apache-2 -- [GitHub](https://github.com/facebookresearch/AugLy) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 300 Β· πŸ“¦ 120 Β· πŸ“‹ 78 - 30% open Β· ⏱️ 22.03.2024): +- [GitHub](https://github.com/Project-MONAI/MONAILabel) (πŸ‘¨β€πŸ’» 61 Β· πŸ”€ 190 Β· πŸ“₯ 92K Β· πŸ“‹ 520 - 24% open Β· ⏱️ 05.09.2024): ``` - git clone https://github.com/facebookresearch/AugLy + git clone https://github.com/Project-MONAI/MONAILabel ``` -- [PyPi](https://pypi.org/project/augly) (πŸ“₯ 2.7K / month Β· πŸ“¦ 4 Β· ⏱️ 05.12.2023): +- [PyPi](https://pypi.org/project/monailabel-weekly) (πŸ“₯ 520 / month Β· ⏱️ 01.10.2023): ``` - pip install augly + pip install monailabel-weekly ```
-
AstroML (πŸ₯‰23 Β· ⭐ 1K) - Machine learning, statistics, and data mining for astronomy and.. BSD-2 +
AstroML (πŸ₯‰22 Β· ⭐ 1K Β· πŸ’€) - Machine learning, statistics, and data mining for astronomy and.. BSD-2 -- [GitHub](https://github.com/astroML/astroML) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 300 Β· πŸ“‹ 160 - 38% open Β· ⏱️ 04.01.2024): +- [GitHub](https://github.com/astroML/astroML) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 290 Β· πŸ“‹ 160 - 38% open Β· ⏱️ 04.01.2024): ``` git clone https://github.com/astroML/astroML ``` -- [PyPi](https://pypi.org/project/astroML) (πŸ“₯ 1.6K / month Β· πŸ“¦ 14 Β· ⏱️ 01.03.2022): +- [PyPi](https://pypi.org/project/astroML) (πŸ“₯ 1.6K / month Β· πŸ“¦ 16 Β· ⏱️ 01.03.2022): ``` pip install astroML ``` -- [Conda](https://anaconda.org/conda-forge/astroml) (πŸ“₯ 44K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/astroml) (πŸ“₯ 47K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge astroml ```
-
BioPandas (πŸ₯‰23 Β· ⭐ 690 Β· πŸ’€) - Working with molecular structures in pandas DataFrames. BSD-3 - -- [GitHub](https://github.com/BioPandas/biopandas) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 120 Β· πŸ“¦ 250 Β· πŸ“‹ 58 - 41% open Β· ⏱️ 19.09.2023): - - ``` - git clone https://github.com/rasbt/biopandas - ``` -- [PyPi](https://pypi.org/project/biopandas) (πŸ“₯ 62K / month Β· πŸ“¦ 23 Β· ⏱️ 28.08.2023): - ``` - pip install biopandas - ``` -- [Conda](https://anaconda.org/conda-forge/biopandas) (πŸ“₯ 150K Β· ⏱️ 16.06.2023): - ``` - conda install -c conda-forge biopandas - ``` -
-
MONAILabel (πŸ₯‰23 Β· ⭐ 560) - MONAI Label is an intelligent open source image labeling and.. Apache-2 +
benchmark_VAE (πŸ₯‰21 Β· ⭐ 1.8K) - Unifying Variational Autoencoder (VAE) implementations.. Apache-2 -- [GitHub](https://github.com/Project-MONAI/MONAILabel) (πŸ‘¨β€πŸ’» 59 Β· πŸ”€ 180 Β· πŸ“₯ 85K Β· πŸ“‹ 510 - 23% open Β· ⏱️ 24.05.2024): +- [GitHub](https://github.com/clementchadebec/benchmark_VAE) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 160 Β· πŸ“¦ 31 Β· πŸ“‹ 64 - 35% open Β· ⏱️ 17.07.2024): ``` - git clone https://github.com/Project-MONAI/MONAILabel + git clone https://github.com/clementchadebec/benchmark_VAE ``` -- [PyPi](https://pypi.org/project/monailabel-weekly) (πŸ“₯ 440 / month Β· ⏱️ 01.10.2023): +- [PyPi](https://pypi.org/project/pythae) (πŸ“₯ 1.7K / month Β· ⏱️ 06.09.2023): ``` - pip install monailabel-weekly + pip install pythae ```
-
SUOD (πŸ₯‰22 Β· ⭐ 370) - (MLSys 21) An Acceleration System for Large-scare Unsupervised Heterogeneous.. BSD-2 +
SUOD (πŸ₯‰21 Β· ⭐ 380 Β· πŸ’€) - (MLSys 21) An Acceleration System for Large-scare Unsupervised.. BSD-2 -- [GitHub](https://github.com/yzhao062/SUOD) (πŸ‘¨β€πŸ’» 3 Β· πŸ”€ 48 Β· πŸ“¦ 520 Β· πŸ“‹ 14 - 78% open Β· ⏱️ 08.02.2024): +- [GitHub](https://github.com/yzhao062/SUOD) (πŸ‘¨β€πŸ’» 3 Β· πŸ”€ 49 Β· πŸ“¦ 530 Β· πŸ“‹ 15 - 80% open Β· ⏱️ 08.02.2024): ``` git clone https://github.com/yzhao062/SUOD ``` -- [PyPi](https://pypi.org/project/suod) (πŸ“₯ 13K / month Β· πŸ“¦ 8 Β· ⏱️ 08.02.2024): +- [PyPi](https://pypi.org/project/suod) (πŸ“₯ 19K / month Β· πŸ“¦ 8 Β· ⏱️ 08.02.2024): ``` pip install suod ```
-
benchmark_VAE (πŸ₯‰21 Β· ⭐ 1.7K) - Unifying Variational Autoencoder (VAE) implementations.. Apache-2 - -- [GitHub](https://github.com/clementchadebec/benchmark_VAE) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 150 Β· πŸ“¦ 23 Β· πŸ“‹ 58 - 32% open Β· ⏱️ 09.04.2024): - - ``` - git clone https://github.com/clementchadebec/benchmark_VAE - ``` -- [PyPi](https://pypi.org/project/pythae) (πŸ“₯ 1.1K / month Β· ⏱️ 06.09.2023): - ``` - pip install pythae - ``` -
-
rrcf (πŸ₯‰20 Β· ⭐ 480 Β· πŸ’€) - Implementation of the Robust Random Cut Forest algorithm for anomaly.. MIT +
pymdp (πŸ₯‰20 Β· ⭐ 430) - A Python implementation of active inference for Markov Decision Processes. MIT -- [GitHub](https://github.com/kLabUM/rrcf) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 110 Β· πŸ“¦ 63 Β· πŸ“‹ 47 - 55% open Β· ⏱️ 12.08.2023): +- [GitHub](https://github.com/infer-actively/pymdp) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 80 Β· πŸ“¦ 12 Β· πŸ“‹ 42 - 35% open Β· ⏱️ 16.07.2024): ``` - git clone https://github.com/kLabUM/rrcf + git clone https://github.com/infer-actively/pymdp ``` -- [PyPi](https://pypi.org/project/rrcf) (πŸ“₯ 2.7K / month Β· πŸ“¦ 8 Β· ⏱️ 30.04.2023): +- [PyPi](https://pypi.org/project/inferactively-pymdp) (πŸ“₯ 240 / month Β· ⏱️ 08.12.2022): ``` - pip install rrcf + pip install inferactively-pymdp ```
-
pykale (πŸ₯‰20 Β· ⭐ 430) - Knowledge-Aware machine LEarning (KALE): accessible machine learning.. MIT +
pykale (πŸ₯‰19 Β· ⭐ 440) - Knowledge-Aware machine LEarning (KALE): accessible machine learning.. MIT -- [GitHub](https://github.com/pykale/pykale) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 63 Β· πŸ“¦ 1 Β· πŸ“‹ 120 - 7% open Β· ⏱️ 29.05.2024): +- [GitHub](https://github.com/pykale/pykale) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 63 Β· πŸ“¦ 3 Β· πŸ“‹ 120 - 9% open Β· ⏱️ 27.07.2024): ``` git clone https://github.com/pykale/pykale ``` -- [PyPi](https://pypi.org/project/pykale) (πŸ“₯ 42 / month Β· ⏱️ 12.04.2022): +- [PyPi](https://pypi.org/project/pykale) (πŸ“₯ 130 / month Β· ⏱️ 12.04.2022): ``` pip install pykale ```
-
pymdp (πŸ₯‰19 Β· ⭐ 400 Β· πŸ“ˆ) - A Python implementation of active inference for Markov Decision Processes. MIT - -- [GitHub](https://github.com/infer-actively/pymdp) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 71 Β· πŸ“¦ 9 Β· πŸ“‹ 42 - 35% open Β· ⏱️ 06.06.2024): - - ``` - git clone https://github.com/infer-actively/pymdp - ``` -- [PyPi](https://pypi.org/project/inferactively-pymdp) (πŸ“₯ 290 / month Β· ⏱️ 08.12.2022): - ``` - pip install inferactively-pymdp - ``` -
-
NeuralCompression (πŸ₯‰14 Β· ⭐ 480 Β· πŸ“‰) - A collection of tools for neural compression enthusiasts. MIT +
NeuralCompression (πŸ₯‰15 Β· ⭐ 500) - A collection of tools for neural compression enthusiasts. MIT -- [GitHub](https://github.com/facebookresearch/NeuralCompression) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 42 Β· πŸ“‹ 69 - 7% open Β· ⏱️ 18.03.2024): +- [GitHub](https://github.com/facebookresearch/NeuralCompression) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 42 Β· πŸ“‹ 71 - 8% open Β· ⏱️ 18.03.2024): ``` git clone https://github.com/facebookresearch/NeuralCompression ``` -- [PyPi](https://pypi.org/project/neuralcompression) (πŸ“₯ 86 / month Β· ⏱️ 03.10.2023): +- [PyPi](https://pypi.org/project/neuralcompression) (πŸ“₯ 110 / month Β· ⏱️ 03.10.2023): ``` pip install neuralcompression ```
-
Show 22 hidden projects... +
Show 25 hidden projects... -- cleanlab (πŸ₯ˆ32 Β· ⭐ 8.9K) - The standard data-centric AI package for data quality and machine.. ❗️AGPL-3.0 -- PaddleHub (πŸ₯ˆ31 Β· ⭐ 13K Β· πŸ’€) - Awesome pre-trained models toolkit based on PaddlePaddle... Apache-2 -- pysc2 (πŸ₯ˆ28 Β· ⭐ 7.9K Β· πŸ’€) - StarCraft II Learning Environment. Apache-2 -- alibi-detect (πŸ₯ˆ28 Β· ⭐ 2.1K) - Algorithms for outlier, adversarial and drift detection. ❗️Intel +- cleanlab (πŸ₯ˆ32 Β· ⭐ 9.4K) - The standard data-centric AI package for data quality and machine.. ❗️AGPL-3.0 +- Cython BLIS (πŸ₯ˆ31 Β· ⭐ 220) - Fast matrix-multiplication as a self-contained Python library no.. BSD-3 +- alibi-detect (πŸ₯ˆ29 Β· ⭐ 2.2K) - Algorithms for outlier, adversarial and drift detection. ❗️Intel +- pysc2 (πŸ₯ˆ28 Β· ⭐ 8K Β· πŸ’€) - StarCraft II Learning Environment. Apache-2 - minisom (πŸ₯ˆ28 Β· ⭐ 1.4K) - MiniSom is a minimalistic implementation of the Self Organizing.. ❗️CC-BY-3.0 -- Cython BLIS (πŸ₯ˆ28 Β· ⭐ 210) - Fast matrix-multiplication as a self-contained Python library no.. BSD-3 -- pandas-ai (πŸ₯‰27 Β· ⭐ 11K) - Chat with your database (SQL, CSV, pandas, polars, mongodb,.. ❗Unlicensed +- PySwarms (πŸ₯ˆ28 Β· ⭐ 1.3K Β· πŸ’€) - A research toolkit for particle swarm optimization in Python. MIT +- modAL (πŸ₯‰27 Β· ⭐ 2.2K Β· πŸ’€) - A modular active learning framework for Python. MIT +- gplearn (πŸ₯‰26 Β· ⭐ 1.6K Β· πŸ’€) - Genetic Programming in Python, with a scikit-learn inspired API. BSD-3 +- pycm (πŸ₯‰26 Β· ⭐ 1.4K Β· πŸ’€) - Multi-class confusion matrix library in Python. MIT - metricflow (πŸ₯‰26 Β· ⭐ 1.1K) - MetricFlow allows you to define, build, and maintain metrics.. ❗Unlicensed -- Feature Engine (πŸ₯‰25 Β· ⭐ 1.8K Β· πŸ’€) - Feature engineering package with sklearn like functionality. BSD-3 - findspark (πŸ₯‰24 Β· ⭐ 510 Β· πŸ’€) - Find pyspark to make it importable. BSD-3 -- opyrator (πŸ₯‰22 Β· ⭐ 3K Β· πŸ’€) - Turns your machine learning code into microservices with web API,.. MIT -- mlens (πŸ₯‰22 Β· ⭐ 830 Β· πŸ’€) - ML-Ensemble high performance ensemble learning. MIT -- vecstack (πŸ₯‰22 Β· ⭐ 680 Β· πŸ’€) - Python package for stacking (machine learning technique). MIT +- pandas-ai (πŸ₯‰23 Β· ⭐ 13K Β· πŸ“‰) - Chat with your database (SQL, CSV, pandas, polars,.. ❗Unlicensed +- vecstack (πŸ₯‰23 Β· ⭐ 680 Β· πŸ’€) - Python package for stacking (machine learning technique). MIT +- opyrator (πŸ₯‰22 Β· ⭐ 3.1K Β· πŸ’€) - Turns your machine learning code into microservices with web API,.. MIT +- mlens (πŸ₯‰22 Β· ⭐ 840 Β· πŸ’€) - ML-Ensemble high performance ensemble learning. MIT +- apricot (πŸ₯‰21 Β· ⭐ 500 Β· πŸ’€) - apricot implements submodular optimization for the purpose of.. MIT - impyute (πŸ₯‰21 Β· ⭐ 350 Β· πŸ’€) - Data imputations library to preprocess datasets with missing data. MIT -- StreamAlert (πŸ₯‰20 Β· ⭐ 2.8K Β· πŸ’€) - StreamAlert is a serverless, realtime data analysis.. Apache-2 -- apricot (πŸ₯‰20 Β· ⭐ 490 Β· πŸ’€) - apricot implements submodular optimization for the purpose of.. MIT +- StreamAlert (πŸ₯‰20 Β· ⭐ 2.9K Β· πŸ’€) - StreamAlert is a serverless, realtime data analysis.. Apache-2 +- rrcf (πŸ₯‰20 Β· ⭐ 490 Β· πŸ’€) - Implementation of the Robust Random Cut Forest algorithm for anomaly.. MIT - scikit-rebate (πŸ₯‰19 Β· ⭐ 400 Β· πŸ’€) - A scikit-learn-compatible Python implementation of.. MIT - baikal (πŸ₯‰18 Β· ⭐ 590 Β· πŸ’€) - A graph-based functional API for building complex scikit-learn.. BSD-3 -- pandas-ml (πŸ₯‰18 Β· ⭐ 310 Β· πŸ’€) - pandas, scikit-learn, xgboost and seaborn integration. BSD-3 -- KD-Lib (πŸ₯‰15 Β· ⭐ 580 Β· πŸ’€) - A Pytorch Knowledge Distillation library for benchmarking and.. MIT -- traingenerator (πŸ₯‰13 Β· ⭐ 1.3K Β· πŸ’€) - A web app to generate template code for machine learning. MIT +- pandas-ml (πŸ₯‰16 Β· ⭐ 320 Β· πŸ’€) - pandas, scikit-learn, xgboost and seaborn integration. BSD-3 +- KD-Lib (πŸ₯‰15 Β· ⭐ 590 Β· πŸ’€) - A Pytorch Knowledge Distillation library for benchmarking and.. MIT +- traingenerator (πŸ₯‰13 Β· ⭐ 1.4K Β· πŸ’€) - A web app to generate template code for machine learning. MIT - nylon (πŸ₯‰12 Β· ⭐ 84 Β· πŸ’€) - An intelligent, flexible grammar of machine learning. MIT
diff --git a/history/2024-09-05_changes.md b/history/2024-09-05_changes.md new file mode 100644 index 0000000..1009383 --- /dev/null +++ b/history/2024-09-05_changes.md @@ -0,0 +1,36 @@ +## πŸ“ˆ Trending Up + +_Projects that have a higher project-quality score compared to the last update. There might be a variety of reasons, such as increased downloads or code activity._ + +- nltk (πŸ₯‡45 Β· ⭐ 13K Β· πŸ“ˆ) - Suite of libraries and programs for symbolic and statistical natural.. Apache-2 +- Optuna (πŸ₯‡43 Β· ⭐ 10K Β· πŸ“ˆ) - A hyperparameter optimization framework. MIT +- Netron (πŸ₯‡37 Β· ⭐ 27K Β· πŸ“ˆ) - Visualizer for neural network, deep learning and machine.. MIT +- Datasette (πŸ₯‡36 Β· ⭐ 9.2K Β· πŸ“ˆ) - An open source multi-tool for exploring and publishing data. Apache-2 +- Autograd (πŸ₯‡36 Β· ⭐ 6.9K Β· πŸ“ˆ) - Efficiently computes derivatives of NumPy code. MIT +- bt (πŸ₯‡31 Β· ⭐ 2.2K Β· πŸ“ˆ) - bt - flexible backtesting for Python. MIT +- python-soundfile (πŸ₯‰29 Β· ⭐ 700 Β· πŸ“ˆ) - SoundFile is an audio library based on libsndfile, CFFI,.. BSD-3 +- miceforest (πŸ₯‡26 Β· ⭐ 330 Β· πŸ“ˆ) - Multiple Imputation with LightGBM in Python. MIT +- dabl (πŸ₯‰20 Β· ⭐ 720 Β· πŸ’€) - Data Analysis Baseline Library. BSD-3 +- MXBoard (πŸ₯‰20 Β· ⭐ 320 Β· πŸ’€) - Logging MXNet data for visualization in TensorBoard. Apache-2 + +## πŸ“‰ Trending Down + +_Projects that have a lower project-quality score compared to the last update. There might be a variety of reasons such as decreased downloads or code activity._ + +- tensorflow-probability (πŸ₯‡35 Β· ⭐ 4.2K Β· πŸ“‰) - Probabilistic reasoning and statistical analysis in.. Apache-2 +- Graphviz (πŸ₯ˆ34 Β· ⭐ 1.6K Β· πŸ“‰) - Simple Python interface for Graphviz. MIT +- SpeechRecognition (πŸ₯ˆ33 Β· ⭐ 8.3K Β· πŸ“‰) - Speech recognition module for Python, supporting.. BSD-3 +- OpenNMT (πŸ₯ˆ32 Β· ⭐ 6.7K Β· πŸ“‰) - Open Source Neural Machine Translation and (Large) Language.. MIT +- tensorflow-hub (πŸ₯ˆ32 Β· ⭐ 3.5K Β· πŸ“‰) - A library for transfer learning by reusing parts of.. Apache-2 +- TF Model Optimization (πŸ₯ˆ28 Β· ⭐ 1.5K Β· πŸ“‰) - A toolkit to optimize ML models for deployment for.. Apache-2 +- data-validation (πŸ₯‰26 Β· ⭐ 760 Β· πŸ“‰) - Library for exploring and validating machine learning.. Apache-2 +- TF Recommenders (πŸ₯‰24 Β· ⭐ 1.8K Β· πŸ“‰) - TensorFlow Recommenders is a library for building.. Apache-2 +- pandas-ai (πŸ₯‰23 Β· ⭐ 13K Β· πŸ“‰) - Chat with your database (SQL, CSV, pandas, polars,.. ❗Unlicensed +- TensorFrames (πŸ₯‰16 Β· ⭐ 720 Β· πŸ’€) - Tensorflow wrapper for DataFrames on Apache Spark. Apache-2 + +## βž• Added Projects + +_Projects that were recently added to this best-of list._ + +- Runhouse (πŸ₯‰24 Β· ⭐ 960 Β· βž•) - Orchestrate heterogeneous ML workloads in Python, like PyTorch.. Apache-2 + diff --git a/history/2024-09-05_projects.csv b/history/2024-09-05_projects.csv new file mode 100644 index 0000000..f996204 --- /dev/null +++ b/history/2024-09-05_projects.csv @@ -0,0 +1,919 @@ +,name,github_id,category,resource,github_url,homepage,license,created_at,updated_at,last_commit_pushed_at,commit_count,recent_commit_count,fork_count,watchers_count,pr_count,open_issue_count,closed_issue_count,star_count,description,contributor_count,projectrank,show,latest_stable_release_published_at,latest_stable_release_number,release_count,pypi_id,conda_id,docs_url,labels,github_release_downloads,monthly_downloads,dependent_project_count,github_dependent_project_count,pypi_url,pypi_latest_release_published_at,pypi_dependent_project_count,pypi_monthly_downloads,conda_url,conda_latest_release_published_at,conda_total_downloads,projectrank_placing,dockerhub_id,dockerhub_url,dockerhub_latest_release_published_at,dockerhub_stars,dockerhub_pulls,trending,helm_id,updated_github_id,npm_id,npm_url,npm_latest_release_published_at,npm_dependent_project_count,npm_monthly_downloads,brew_id,apt_id,yum_id,conda_dependent_project_count,dnf_id,yay_id,maven_id,maven_url,maven_latest_release_published_at,maven_dependent_project_count,snap_id,new_addition +0,ANN Benchmarks,erikbern/ann-benchmarks,nn-search,True,https://github.com/erikbern/ann-benchmarks,https://github.com/erikbern/ann-benchmarks,MIT,2015-05-28 13:21:43.000,2024-09-02 06:22:28.000000,2024-09-02 06:22:28,1567.0,8.0,693.0,117.0,338.0,62.0,145.0,4842.0,Benchmarks of approximate nearest neighbor libraries in Python.,108.0,0,True,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, +1,best-of-web-python - Web Scraping,ml-tooling/best-of-web-python,web-scraping,True,https://github.com/ml-tooling/best-of-web-python,https://github.com/ml-tooling/best-of-web-python#web-scraping--crawling,CC-BY-SA-4.0,2021-01-05 13:09:27.000,2024-06-07 15:14:35.000000,2024-06-06 19:06:33,346.0,,166.0,57.0,205.0,,3.0,2279.0,Collection of web-scraping and crawling libraries.,16.0,0,True,2024-06-06 19:06:38.000,2024.06.06,100.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, +2,best-of-python - Data Extraction,ml-tooling/best-of-python,data-loading,True,https://github.com/ml-tooling/best-of-python,https://github.com/ml-tooling/best-of-python#data-loading--extraction,CC-BY-SA-4.0,2021-01-11 19:11:32.000,2024-08-14 02:31:07.000000,2024-08-14 02:31:07,360.0,1.0,244.0,93.0,199.0,6.0,5.0,3596.0,Collection of data-loading and -extraction libraries.,12.0,0,True,2024-06-06 14:07:12.000,2024.06.06,100.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, +3,best-of-python - DB Clients,ml-tooling/best-of-python,db-clients,True,https://github.com/ml-tooling/best-of-python,https://github.com/ml-tooling/best-of-python#database-clients,CC-BY-SA-4.0,2021-01-11 19:11:32.000,2024-08-14 02:31:07.000000,2024-08-14 02:31:07,360.0,1.0,244.0,93.0,199.0,6.0,5.0,3596.0,Collection of database clients for python.,12.0,0,True,2024-06-06 14:07:12.000,2024.06.06,100.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, +4,best-of-python - Data Containers,ml-tooling/best-of-python,data-containers,True,https://github.com/ml-tooling/best-of-python,https://github.com/ml-tooling/best-of-python#data-containers--dataframes,CC-BY-SA-4.0,2021-01-11 19:11:32.000,2024-08-14 02:31:07.000000,2024-08-14 02:31:07,360.0,1.0,244.0,93.0,199.0,6.0,5.0,3596.0,"Collection of data-container, dataframe, and pandas-utility libraries.",12.0,0,True,2024-06-06 14:07:12.000,2024.06.06,100.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, +5,best-of-python - Data Pipelines,ml-tooling/best-of-python,data-pipelines,True,https://github.com/ml-tooling/best-of-python,https://github.com/ml-tooling/best-of-python#data-pipelines--streaming,CC-BY-SA-4.0,2021-01-11 19:11:32.000,2024-08-14 02:31:07.000000,2024-08-14 02:31:07,360.0,1.0,244.0,93.0,199.0,6.0,5.0,3596.0,"Libraries for data batch- and stream-processing, workflow automation, job scheduling, and other data pipeline tasks.",12.0,0,True,2024-06-06 14:07:12.000,2024.06.06,100.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, +6,PyTorch,pytorch/pytorch,ml-frameworks,,https://github.com/pytorch/pytorch,https://github.com/pytorch/pytorch,BSD-3-Clause,2016-08-13 05:26:41.000,2024-09-05 14:13:12.000000,2024-09-05 12:52:43,78064.0,4008.0,21955.0,1744.0,90205.0,14808.0,30877.0,81851.0,Tensors and Dynamic neural networks in Python with strong GPU acceleration.,5097.0,56,True,2024-09-04 19:59:29.000,2.4.1,55.0,torch,pytorch/pytorch,https://pytorch.org/docs/stable/index.html,['pytorch'],55050.0,35132513.0,536836.0,518370.0,https://pypi.org/project/torch,2024-09-04 19:10:42.000,18466.0,34482200.0,https://anaconda.org/pytorch/pytorch,2024-09-03 16:47:49.313,23390644.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +7,Tensorflow,tensorflow/tensorflow,ml-frameworks,,https://github.com/tensorflow/tensorflow,https://github.com/tensorflow/tensorflow,Apache-2.0,2015-11-07 01:19:20.000,2024-09-05 14:08:30.000000,2024-09-05 13:45:19,169190.0,3689.0,74162.0,7603.0,34823.0,4553.0,38022.0,187888.0,An Open Source Machine Learning Framework for Everyone.,4668.0,55,True,2024-07-11 16:45:52.000,2.17.0,197.0,tensorflow,conda-forge/tensorflow,https://www.tensorflow.org/overview,['tensorflow'],,19035138.0,413414.0,405612.0,https://pypi.org/project/tensorflow,2024-07-11 16:45:52.000,7802.0,18200590.0,https://anaconda.org/conda-forge/tensorflow,2024-08-31 23:00:17.783,4914489.0,1.0,tensorflow/tensorflow,https://hub.docker.com/r/tensorflow/tensorflow,2024-09-04 12:48:51.219515,2540.0,78043486.0,,,,,,,,,,,,,,,,,,,, +8,transformers,huggingface/transformers,nlp,,https://github.com/huggingface/transformers,https://github.com/huggingface/transformers,Apache-2.0,2018-10-29 13:56:00.000,2024-09-05 14:24:31.000000,2024-09-05 14:17:34,16759.0,648.0,26184.0,1118.0,17258.0,1400.0,14593.0,131616.0,"Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.",2790.0,52,True,2024-08-22 16:56:32.000,4.44.2,157.0,transformers,conda-forge/transformers,,"['pytorch', 'tensorflow']",,35821691.0,217088.0,211035.0,https://pypi.org/project/transformers,2024-08-22 16:56:29.000,6053.0,35781688.0,https://anaconda.org/conda-forge/transformers,2024-08-23 08:59:54.225,2000152.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +9,scikit-learn,scikit-learn/scikit-learn,ml-frameworks,,https://github.com/scikit-learn/scikit-learn,https://github.com/scikit-learn/scikit-learn,BSD-3-Clause,2010-08-17 09:43:38.000,2024-09-05 12:14:52.000000,2024-09-05 12:14:52,31652.0,263.0,25230.0,2141.0,17665.0,2098.0,9550.0,59339.0,scikit-learn: machine learning in Python.,3173.0,52,True,2024-07-03 09:17:35.000,1.5.1,80.0,scikit-learn,conda-forge/scikit-learn,,['sklearn'],1019.0,72877506.0,901554.0,877595.0,https://pypi.org/project/scikit-learn,2024-07-03 09:11:11.000,23959.0,72287515.0,https://anaconda.org/conda-forge/scikit-learn,2024-07-03 09:49:53.256,30679039.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +10,scipy,scipy/scipy,others,,https://github.com/scipy/scipy,https://github.com/scipy/scipy,BSD-3-Clause,2011-03-09 18:52:03.000,2024-09-04 22:29:36.000000,2024-09-04 22:29:36,33268.0,565.0,5121.0,347.0,11234.0,1808.0,8756.0,12886.0,"Ecosystem of open-source software for mathematics, science, and engineering.",1678.0,50,True,2024-08-21 00:10:50.000,1.14.1,108.0,scipy,conda-forge/scipy,,,411363.0,120625329.0,1128458.0,1083640.0,https://pypi.org/project/scipy,2024-08-21 00:03:32.000,44818.0,119493193.0,https://anaconda.org/conda-forge/scipy,2024-08-22 15:46:59.754,51906302.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +11,SymPy,sympy/sympy,others,,https://github.com/sympy/sympy,https://github.com/sympy/sympy,BSD-3-Clause,2010-04-30 20:37:14.000,2024-09-05 12:15:40.000000,2024-09-05 12:15:40,58816.0,785.0,4370.0,292.0,13365.0,5124.0,8847.0,12752.0,A computer algebra system written in pure Python.,1322.0,49,True,2024-08-11 16:59:00.000,1.13.2,63.0,sympy,conda-forge/sympy,,,547056.0,29664701.0,169884.0,166484.0,https://pypi.org/project/sympy,2024-08-11 16:58:39.000,3400.0,29535996.0,https://anaconda.org/conda-forge/sympy,2024-08-12 22:08:15.340,6480408.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +12,Keras,keras-team/keras,ml-frameworks,,https://github.com/keras-team/keras,https://github.com/keras-team/keras,Apache-2.0,2015-03-28 00:35:42.000,2024-09-05 03:42:28.000000,2024-09-05 03:42:28,10920.0,201.0,19416.0,1913.0,7419.0,240.0,11863.0,61555.0,Deep Learning for humans.,1325.0,48,True,2024-08-12 20:42:48.000,3.5.0,102.0,keras,conda-forge/keras,https://keras.io,['tensorflow'],,14026758.0,1528.0,,https://pypi.org/project/keras,2024-08-12 20:42:48.000,1528.0,13954555.0,https://anaconda.org/conda-forge/keras,2024-08-17 19:28:53.337,3682388.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +13,Matplotlib,matplotlib/matplotlib,data-viz,,https://github.com/matplotlib/matplotlib,https://github.com/matplotlib/matplotlib,,2011-02-19 03:17:12.000,2024-09-03 22:00:24.000000,2024-09-03 22:00:24,50973.0,494.0,7554.0,595.0,18303.0,1600.0,9240.0,19922.0,matplotlib: plotting with Python.,1717.0,48,True,2024-08-13 01:44:21.000,3.9.2,127.0,matplotlib,conda-forge/matplotlib,,,,72120676.0,1368264.0,1319685.0,https://pypi.org/project/matplotlib,2024-08-13 01:44:21.000,48579.0,71617361.0,https://anaconda.org/conda-forge/matplotlib,2024-08-22 20:32:53.714,25669070.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +14,Pillow,python-pillow/Pillow,image,,https://github.com/python-pillow/Pillow,https://github.com/python-pillow/Pillow,PIL,2012-07-24 21:38:39.000,2024-09-05 12:54:21.000000,2024-09-05 12:53:48,18389.0,456.0,2210.0,220.0,5027.0,134.0,3065.0,12076.0,Python Imaging Library (Fork).,475.0,48,True,2024-07-01 09:51:39.000,10.4.0,98.0,Pillow,conda-forge/pillow,,,,113732231.0,1818069.0,1810387.0,https://pypi.org/project/Pillow,2024-07-01 09:45:22.000,7682.0,112857636.0,https://anaconda.org/conda-forge/pillow,2024-07-02 08:21:06.154,43729768.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +15,Streamlit,streamlit/streamlit,others,,https://github.com/streamlit/streamlit,https://github.com/streamlit/streamlit,Apache-2.0,2019-08-24 00:14:52.000,2024-09-05 14:10:56.000000,2024-09-05 12:11:28,6607.0,218.0,2976.0,319.0,4823.0,937.0,3573.0,34405.0,Streamlit A faster way to build and share data apps.,240.0,46,True,2024-08-27 18:46:56.000,1.38.0,226.0,streamlit,,,,,5631298.0,498767.0,496110.0,https://pypi.org/project/streamlit,2024-08-27 18:46:49.000,2657.0,5631298.0,,,,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +16,jax,google/jax,ml-frameworks,,https://github.com/google/jax,https://github.com/google/jax,Apache-2.0,2018-10-25 21:25:02.000,2024-09-05 13:36:36.000000,2024-09-05 11:57:52,22800.0,1609.0,2713.0,323.0,15182.0,1703.0,4160.0,29742.0,"Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more.",742.0,46,True,2024-07-30 00:25:44.000,0.4.31,165.0,jax,conda-forge/jaxlib,,,,3410536.0,31375.0,29587.0,https://pypi.org/project/jax,2024-07-30 00:25:44.000,1788.0,3378882.0,https://anaconda.org/conda-forge/jaxlib,2024-08-31 00:56:55.014,1614396.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +17,PaddlePaddle,PaddlePaddle/Paddle,ml-frameworks,,https://github.com/PaddlePaddle/Paddle,https://github.com/PaddlePaddle/Paddle,Apache-2.0,2016-08-15 06:59:08.000,2024-09-05 12:19:34.000000,2024-09-05 12:19:34,50806.0,2002.0,5535.0,717.0,49544.0,1822.0,17311.0,22049.0,PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice &.,1267.0,46,True,2024-06-27 10:00:34.000,3.0.0-beta0,69.0,paddlepaddle,,,['paddle'],15389.0,513774.0,5982.0,5822.0,https://pypi.org/project/paddlepaddle,2024-07-08 06:22:25.000,160.0,513616.0,,,,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +18,Ray,ray-project/ray,distributed-ml,,https://github.com/ray-project/ray,https://github.com/ray-project/ray,Apache-2.0,2016-10-25 19:38:30.000,2024-09-05 14:56:39.000000,2024-09-05 14:56:37,22555.0,728.0,5571.0,475.0,28864.0,3963.0,14866.0,32918.0,Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a..,1066.0,45,True,2024-08-28 00:11:51.000,ray-2.35.0,114.0,ray,conda-forge/ray-tune,,,235.0,4187177.0,18328.0,17572.0,https://pypi.org/project/ray,2024-08-27 22:09:04.000,756.0,4178743.0,https://anaconda.org/conda-forge/ray-tune,2024-08-29 18:04:13.302,379447.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +19,XGBoost,dmlc/xgboost,ml-frameworks,,https://github.com/dmlc/xgboost,https://github.com/dmlc/xgboost,Apache-2.0,2014-02-06 17:28:03.000,2024-09-02 20:06:23.000000,2024-09-02 11:44:12,7077.0,178.0,8699.0,911.0,5527.0,463.0,4886.0,26063.0,"Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and..",649.0,45,True,2024-07-31 08:14:26.000,2.1.1,83.0,xgboost,conda-forge/xgboost,https://xgboost.readthedocs.io/en/latest/,,10600.0,20972549.0,107800.0,105855.0,https://pypi.org/project/xgboost,2024-07-31 08:14:26.000,1945.0,20868255.0,https://anaconda.org/conda-forge/xgboost,2024-08-28 02:29:22.781,5210537.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +20,Bokeh,bokeh/bokeh,data-viz,,https://github.com/bokeh/bokeh,https://github.com/bokeh/bokeh,BSD-3-Clause,2012-03-26 15:40:01.000,2024-09-05 13:46:10.000000,2024-09-05 05:49:08,20582.0,67.0,4176.0,443.0,6151.0,760.0,6969.0,19203.0,"Interactive Data Visualization in the browser, from Python.",698.0,45,True,2024-08-23 08:14:02.000,3.5.2,214.0,bokeh,conda-forge/bokeh,,,,4638994.0,93450.0,91749.0,https://pypi.org/project/bokeh,2024-08-23 08:14:02.000,1701.0,4348692.0,https://anaconda.org/conda-forge/bokeh,2024-08-23 12:55:11.815,14805433.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +21,nltk,nltk/nltk,nlp,,https://github.com/nltk/nltk,https://github.com/nltk/nltk,Apache-2.0,2009-09-07 10:53:58.000,2024-09-04 01:00:39.000000,2024-09-04 01:00:39,14678.0,146.0,2856.0,463.0,1485.0,273.0,1547.0,13404.0,Suite of libraries and programs for symbolic and statistical natural language processing for English.,461.0,45,True,2024-08-18 19:48:21.000,3.9.1,63.0,nltk,conda-forge/nltk,,,,21531340.0,306804.0,302235.0,https://pypi.org/project/nltk,2024-08-18 19:48:21.000,4569.0,21465994.0,https://anaconda.org/conda-forge/nltk,2024-08-18 23:14:52.073,2744535.0,1.0,,,,,,4.0,,,,,,,,,,,,,,,,,,, +22,StatsModels,statsmodels/statsmodels,ml-frameworks,,https://github.com/statsmodels/statsmodels,https://github.com/statsmodels/statsmodels,BSD-3-Clause,2011-06-12 17:04:50.000,2024-09-05 10:38:13.000000,2024-09-05 10:38:13,15476.0,98.0,2865.0,283.0,3913.0,2828.0,2780.0,9959.0,Statsmodels: statistical modeling and econometrics in Python.,434.0,45,True,2024-04-17 08:41:57.000,0.14.2,37.0,statsmodels,conda-forge/statsmodels,,,33.0,16200181.0,138847.0,134520.0,https://pypi.org/project/statsmodels,2024-04-17 08:41:57.000,4327.0,15911517.0,https://anaconda.org/conda-forge/statsmodels,2024-05-17 10:41:00.825,14721872.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +23,PySpark,apache/spark,ml-frameworks,,https://github.com/apache/spark,https://github.com/apache/spark,Apache-2.0,2014-02-25 08:00:08.000,2024-09-05 13:02:43.000000,2024-09-05 13:02:20,42077.0,821.0,28177.0,2025.0,47970.0,215.0,,39247.0,Apache Spark Python API.,3115.0,44,True,2024-08-12 14:57:56.000,3.5.2,46.0,pyspark,conda-forge/pyspark,,['spark'],,30302212.0,1513.0,,https://pypi.org/project/pyspark,2024-08-12 14:57:56.000,1513.0,30235908.0,https://anaconda.org/conda-forge/pyspark,2024-03-03 13:07:40.821,3381530.0,2.0,,,,,,,stable/spark,,,,,,,,,,,,,,,,,, +24,pytorch-lightning,Lightning-AI/lightning,ml-frameworks,,https://github.com/Lightning-AI/pytorch-lightning,https://github.com/Lightning-AI/pytorch-lightning,Apache-2.0,2019-03-31 00:45:57.000,2024-09-03 22:39:19.000000,2024-08-22 13:59:19,10415.0,91.0,3337.0,247.0,10257.0,750.0,6294.0,27910.0,"Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.",969.0,44,True,2024-08-07 09:46:38.000,2.4.0,277.0,pytorch-lightning,conda-forge/pytorch-lightning,,['pytorch'],8322.0,6318926.0,37505.0,36085.0,https://pypi.org/project/pytorch-lightning,2024-08-07 09:46:38.000,1420.0,6293942.0,https://anaconda.org/conda-forge/pytorch-lightning,2024-08-07 15:45:27.965,1263355.0,2.0,,,,,,,,Lightning-AI/pytorch-lightning,,,,,,,,,,,,,,,,, +25,mlflow,mlflow/mlflow,ml-experiments,,https://github.com/mlflow/mlflow,https://github.com/mlflow/mlflow,Apache-2.0,2018-06-05 16:05:58.000,2024-09-05 09:50:22.000000,2024-09-05 09:50:22,6428.0,392.0,4131.0,296.0,8960.0,1587.0,2558.0,18271.0,Open source platform for the machine learning lifecycle.,765.0,44,True,2024-08-30 22:00:41.000,2.16.0,111.0,mlflow,conda-forge/mlflow,,,,14963496.0,42464.0,41608.0,https://pypi.org/project/mlflow,2024-08-30 08:49:56.000,856.0,14918455.0,https://anaconda.org/conda-forge/mlflow,2024-09-04 14:05:24.643,2297113.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +26,Plotly,plotly/plotly.py,data-viz,,https://github.com/plotly/plotly.py,https://github.com/plotly/plotly.py,MIT,2013-11-21 05:53:08.000,2024-08-30 19:40:02.000000,2024-08-29 18:22:16,6632.0,117.0,2535.0,273.0,1692.0,530.0,2435.0,15967.0,The interactive graphing library for Python This project now includes Plotly Express!.,265.0,44,True,2024-08-29 17:58:45.000,5.24.0,300.0,plotly,conda-forge/plotly,,,,17866134.0,305245.0,299117.0,https://pypi.org/project/plotly,2024-08-29 17:54:43.000,6119.0,17728870.0,https://anaconda.org/conda-forge/plotly,2024-08-30 03:08:35.026,6843734.0,1.0,,,,,,,,,plotlywidget,https://www.npmjs.com/package/plotlywidget,2021-01-12 16:09:46.133,9.0,5654.0,,,,,,,,,,,, +27,networkx,networkx/networkx,graph,,https://github.com/networkx/networkx,https://github.com/networkx/networkx,BSD-3-Clause,2010-09-06 00:53:44.000,2024-09-04 20:26:08.000000,2024-09-02 06:15:24,7773.0,77.0,3202.0,281.0,3860.0,347.0,3018.0,14674.0,Network Analysis in Python.,744.0,44,True,2024-04-06 13:09:07.000,networkx-3.3,94.0,networkx,conda-forge/networkx,,,73.0,64361613.0,298297.0,289035.0,https://pypi.org/project/networkx,2024-04-06 12:59:44.000,9262.0,64004873.0,https://anaconda.org/conda-forge/networkx,2024-04-08 01:42:36.044,17480261.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +28,dask,dask/dask,distributed-ml,,https://github.com/dask/dask,https://github.com/dask/dask,BSD-3-Clause,2015-01-04 18:50:00.000,2024-09-05 08:14:59.000000,2024-09-04 14:46:00,8309.0,99.0,1693.0,212.0,5951.0,1096.0,4242.0,12371.0,Parallel computing with task scheduling.,608.0,44,True,2024-08-30 20:43:20.000,2024.8.2,206.0,dask,conda-forge/dask,,,,10903598.0,66368.0,64053.0,https://pypi.org/project/dask,2024-08-30 20:43:20.000,2315.0,10676383.0,https://anaconda.org/conda-forge/dask,2024-08-31 00:34:24.911,11815186.0,1.0,,,,,,,stable/dask,,,,,,,,,,,,,,,,,, +29,Gradio,gradio-app/gradio,others,,https://github.com/gradio-app/gradio,https://github.com/gradio-app/gradio,Apache-2.0,2018-12-19 08:24:04.000,2024-09-05 03:56:20.000000,2024-09-02 17:00:47,7001.0,296.0,2379.0,168.0,4207.0,546.0,4145.0,31960.0,"Wrap UIs around any model, share with anyone.",372.0,43,True,2024-09-04 06:35:28.000,@self/spaces-test@0.0.1,584.0,gradio,,,,,6255022.0,40474.0,39730.0,https://pypi.org/project/gradio,2024-09-04 06:40:21.000,744.0,6255022.0,,,,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +30,spaCy,explosion/spaCy,nlp,,https://github.com/explosion/spaCy,https://github.com/explosion/spaCy,MIT,2014-07-03 15:15:40.000,2024-09-04 12:31:25.000000,2024-08-20 10:16:08,16136.0,4.0,4344.0,560.0,4010.0,139.0,5511.0,29609.0,Industrial-strength Natural Language Processing (NLP) in Python.,751.0,43,True,2024-08-20 14:29:00.000,3.7.6,233.0,spacy,conda-forge/spacy,,,117.0,11866882.0,100391.0,97783.0,https://pypi.org/project/spacy,2024-08-20 14:29:00.000,2608.0,11788576.0,https://anaconda.org/conda-forge/spacy,2024-07-29 11:52:18.238,3993558.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +31,shap,slundberg/shap,interpretability,,https://github.com/shap/shap,https://github.com/shap/shap,MIT,2016-11-22 19:17:08.000,2024-09-05 10:55:38.000000,2024-09-05 10:55:38,2754.0,78.0,3233.0,239.0,948.0,768.0,1759.0,22438.0,A game theoretic approach to explain the output of any machine learning model.,250.0,43,True,2024-06-27 10:16:34.000,0.46.0,104.0,shap,conda-forge/shap,,,,6506013.0,20641.0,19903.0,https://pypi.org/project/shap,2024-06-27 10:16:34.000,738.0,6422895.0,https://anaconda.org/conda-forge/shap,2024-05-08 21:55:59.406,3740335.0,1.0,,,,,,,,shap/shap,,,,,,,,,,,,,,,,, +32,onnx,onnx/onnx,model-serialisation,,https://github.com/onnx/onnx,https://github.com/onnx/onnx,Apache-2.0,2017-09-07 04:53:45.000,2024-09-05 00:16:09.000000,2024-09-04 21:18:58,2805.0,68.0,3650.0,440.0,3325.0,341.0,2493.0,17598.0,Open standard for machine learning interoperability.,323.0,43,True,2024-08-01 13:15:32.000,1.16.2,34.0,onnx,conda-forge/onnx,,,21593.0,5758482.0,33748.0,32732.0,https://pypi.org/project/onnx,2024-08-01 13:10:23.000,1016.0,5734602.0,https://anaconda.org/conda-forge/onnx,2024-09-03 14:45:24.706,1204660.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +33,LightGBM,microsoft/LightGBM,ml-frameworks,,https://github.com/microsoft/LightGBM,https://github.com/microsoft/LightGBM,MIT,2016-08-05 05:45:50.000,2024-09-04 03:30:31.000000,2024-09-04 03:30:30,3566.0,83.0,3819.0,434.0,3244.0,367.0,3056.0,16510.0,"A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision..",318.0,43,True,2024-07-26 14:38:57.000,4.5.0,38.0,lightgbm,conda-forge/lightgbm,,,233786.0,10071468.0,37967.0,36890.0,https://pypi.org/project/lightgbm,2024-07-26 14:38:57.000,1077.0,10013983.0,https://anaconda.org/conda-forge/lightgbm,2024-08-02 18:29:39.160,2633258.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +34,triton,openai/triton,model-serialisation,,https://github.com/triton-lang/triton,https://github.com/triton-lang/triton,MIT,2014-08-30 17:07:16.000,2024-09-05 12:40:43.000000,2024-09-05 01:41:47,2638.0,283.0,1506.0,186.0,3129.0,617.0,767.0,12466.0,Development repository for the Triton language and compiler.,319.0,43,True,2024-07-09 07:22:23.000,3.0.0,195.0,triton,,,,,13542382.0,35802.0,35571.0,https://pypi.org/project/triton,2024-07-09 07:22:23.000,231.0,13542382.0,,,,1.0,,,,,,,,triton-lang/triton,,,,,,,,,,,,,,,,, +35,pydeck,visgl/deck.gl,geospatial-data,,https://github.com/visgl/deck.gl,https://github.com/visgl/deck.gl,MIT,2015-12-15 08:38:29.000,2024-09-05 01:55:22.000000,2024-09-04 17:53:05,4978.0,77.0,2074.0,1679.0,4843.0,341.0,2713.0,12041.0,WebGL2 powered visualization framework.,271.0,43,True,2024-09-04 13:59:16.023,9.0.29,669.0,pydeck,conda-forge/pydeck,,['jupyter'],,5217497.0,8403.0,7999.0,https://pypi.org/project/pydeck,2024-05-10 15:36:17.000,105.0,4566579.0,https://anaconda.org/conda-forge/pydeck,2023-06-16 19:17:51.392,601103.0,1.0,,,,,,,,,deck.gl,https://www.npmjs.com/package/deck.gl,2024-09-04 13:59:16.023,299.0,639989.0,,,,,,,,,,,, +36,litellm,BerriAI/litellm,nlp,,https://github.com/BerriAI/litellm,https://github.com/BerriAI/litellm,MIT,2023-07-27 00:09:52.000,2024-09-05 15:25:56.000000,2024-09-05 15:21:41,17365.0,4526.0,1366.0,66.0,2408.0,550.0,2541.0,11994.0,"Python SDK, Proxy Server to call 100+ LLM APIs using the OpenAI format - [Bedrock, Azure, OpenAI, VertexAI, Cohere,..",324.0,43,True,2024-09-05 04:45:50.000,1.44.17-stable,937.0,litellm,,,others,242.0,1559753.0,3534.0,3154.0,https://pypi.org/project/litellm,2024-09-05 15:25:56.000,380.0,1559632.0,,,,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +37,Optuna,optuna/optuna,hyperopt,,https://github.com/optuna/optuna,https://github.com/optuna/optuna,MIT,2018-02-21 06:12:56.000,2024-09-05 04:43:31.000000,2024-09-05 04:43:24,18214.0,491.0,994.0,115.0,3638.0,69.0,1596.0,10459.0,A hyperparameter optimization framework.,271.0,43,True,2024-09-02 05:17:47.000,4.0.0,66.0,optuna,conda-forge/optuna,,,,3351160.0,18145.0,17194.0,https://pypi.org/project/optuna,2024-09-02 05:17:47.000,951.0,3320886.0,https://anaconda.org/conda-forge/optuna,2024-09-03 06:05:16.374,1543998.0,1.0,,,,,,4.0,,,,,,,,,,,,,,,,,,, +38,PyTorch Image Models,rwightman/pytorch-image-models,image,,https://github.com/huggingface/pytorch-image-models,https://github.com/huggingface/pytorch-image-models,Apache-2.0,2019-02-02 05:51:12.000,2024-09-05 14:30:43.000000,2024-09-05 14:30:24,2454.0,148.0,4692.0,309.0,512.0,45.0,859.0,31348.0,"The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and..",149.0,42,True,2024-08-23 23:42:07.000,1.0.9,60.0,timm,conda-forge/timm,,['pytorch'],6969269.0,5947330.0,36485.0,35590.0,https://pypi.org/project/timm,2024-08-23 23:31:27.000,895.0,5834016.0,https://anaconda.org/conda-forge/timm,2024-08-24 14:28:50.700,221014.0,1.0,,,,,,,,huggingface/pytorch-image-models,,,,,,,,,,,,,,,,, +39,dash,plotly/dash,data-viz,,https://github.com/plotly/dash,https://github.com/plotly/dash,MIT,2015-04-10 01:53:08.000,2024-09-05 14:32:35.000000,2024-09-04 13:41:41,7623.0,122.0,2041.0,418.0,1112.0,463.0,1338.0,21132.0,Data Apps & Dashboards for Python. No JavaScript Required.,159.0,42,True,2024-09-04 14:31:07.000,2.18.0,180.0,dash,conda-forge/dash,,,76.0,3245981.0,69614.0,68345.0,https://pypi.org/project/dash,2024-09-04 14:26:34.000,1269.0,3217358.0,https://anaconda.org/conda-forge/dash,2024-09-05 04:54:06.311,1459763.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +40,torchvision,pytorch/vision,image,,https://github.com/pytorch/vision,https://github.com/pytorch/vision,BSD-3-Clause,2016-11-09 23:11:43.000,2024-09-05 13:28:27.000000,2024-09-04 10:38:51,3933.0,55.0,6910.0,433.0,5378.0,1007.0,2437.0,15947.0,"Datasets, Transforms and Models specific to Computer Vision.",606.0,42,True,2024-09-04 20:08:34.000,0.19.1,47.0,torchvision,conda-forge/torchvision,,['pytorch'],38565.0,13377945.0,5497.0,21.0,https://pypi.org/project/torchvision,2024-09-04 19:14:53.000,5476.0,13340535.0,https://anaconda.org/conda-forge/torchvision,2024-08-25 15:07:24.274,1553048.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +41,DVC,iterative/dvc,ml-experiments,,https://github.com/iterative/dvc,https://github.com/iterative/dvc,Apache-2.0,2017-03-04 08:16:33.000,2024-09-05 03:36:05.000000,2024-09-03 02:56:43,9329.0,49.0,1172.0,140.0,5505.0,222.0,4457.0,13566.0,ML Experiments and Data Management with Git.,301.0,42,True,2024-09-02 15:02:10.000,3.55.2,538.0,dvc,conda-forge/dvc,,,,600267.0,17607.0,17481.0,https://pypi.org/project/dvc,2024-09-02 15:02:10.000,126.0,557541.0,https://anaconda.org/conda-forge/dvc,2024-09-02 18:55:30.141,2179063.0,1.0,,,,,,,,,,,,,,dvc,dvc,dvc,,,,,,,,, +42,Seaborn,mwaskom/seaborn,data-viz,,https://github.com/mwaskom/seaborn,https://github.com/mwaskom/seaborn,BSD-3-Clause,2012-06-18 18:41:19.000,2024-08-14 20:01:50.000000,2024-07-22 11:32:48,3237.0,3.0,1904.0,261.0,1120.0,176.0,2403.0,12374.0,Statistical data visualization in Python.,213.0,42,True,2024-01-25 13:21:49.000,0.13.2,37.0,seaborn,conda-forge/seaborn,,,419.0,18094687.0,473046.0,462540.0,https://pypi.org/project/seaborn,2024-01-25 13:21:49.000,10506.0,17898371.0,https://anaconda.org/conda-forge/seaborn,2024-04-30 16:33:12.611,10012000.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +43,Altair,altair-viz/altair,data-viz,,https://github.com/vega/altair,https://github.com/vega/altair,BSD-3-Clause,2015-09-19 03:14:04.000,2024-09-05 09:18:52.000000,2024-09-05 09:18:51,3763.0,97.0,782.0,142.0,1462.0,178.0,1803.0,9199.0,Declarative statistical visualization library for Python.,170.0,42,True,2024-08-27 04:41:23.000,5.4.1,42.0,altair,conda-forge/altair,,,174.0,22084817.0,159050.0,158209.0,https://pypi.org/project/altair,2024-08-27 04:31:06.000,841.0,22012005.0,https://anaconda.org/conda-forge/altair,2024-08-27 10:22:34.589,2402786.0,1.0,,,,,,,,vega/altair,,,,,,,,,,,,,,,,, +44,wandb client,wandb/client,ml-experiments,,https://github.com/wandb/wandb,https://github.com/wandb/wandb,MIT,2017-03-24 05:46:23.000,2024-09-05 00:11:34.000000,2024-09-04 23:51:45,6907.0,319.0,651.0,58.0,5002.0,846.0,2426.0,8851.0,"The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation..",189.0,42,True,2024-08-28 22:11:23.000,0.17.8,283.0,wandb,conda-forge/wandb,,,277.0,12946058.0,54367.0,52983.0,https://pypi.org/project/wandb,2024-08-28 22:09:00.000,1384.0,12933950.0,https://anaconda.org/conda-forge/wandb,2024-08-28 20:54:30.560,605101.0,1.0,,,,,,,,wandb/wandb,,,,,,,,,,,,,,,,, +45,Tensorboard,tensorflow/tensorboard,ml-experiments,,https://github.com/tensorflow/tensorboard,https://github.com/tensorflow/tensorboard,Apache-2.0,2017-05-15 20:08:07.000,2024-09-03 22:11:37.000000,2024-08-27 03:03:32,5854.0,19.0,1645.0,191.0,5027.0,677.0,1238.0,6658.0,TensorFlows Visualization Toolkit.,320.0,42,True,2024-08-14 18:18:37.000,2.17.1,62.0,tensorboard,conda-forge/tensorboard,,['tensorflow'],,21513117.0,259225.0,257050.0,https://pypi.org/project/tensorboard,2024-08-14 18:10:47.000,2175.0,21415698.0,https://anaconda.org/conda-forge/tensorboard,2024-08-15 09:13:38.483,4968389.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +46,scikit-image,scikit-image/scikit-image,image,,https://github.com/scikit-image/scikit-image,https://github.com/scikit-image/scikit-image,,2011-07-07 22:07:20.000,2024-09-03 19:28:26.000000,2024-09-03 19:28:26,14109.0,99.0,2216.0,184.0,4475.0,791.0,2099.0,6019.0,Image processing in Python.,670.0,42,False,2024-06-18 19:05:37.000,0.24.0,67.0,scikit-image,conda-forge/scikit-image,,,,17382632.0,200381.0,194319.0,https://pypi.org/project/scikit-image,2024-06-18 19:03:37.000,6062.0,17249339.0,https://anaconda.org/conda-forge/scikit-image,2024-08-17 02:34:14.270,6797987.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +47,PaddleOCR,PaddlePaddle/PaddleOCR,ocr,,https://github.com/PaddlePaddle/PaddleOCR,https://github.com/PaddlePaddle/PaddleOCR,Apache-2.0,2020-05-08 10:38:16.000,2024-09-02 11:29:22.000000,2024-09-02 11:28:02,6278.0,82.0,7641.0,437.0,3060.0,174.0,9111.0,42390.0,"Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages..",249.0,41,True,2024-07-17 10:49:23.000,2.8.1,46.0,paddleocr,,,['paddle'],230881.0,475540.0,3293.0,3201.0,https://pypi.org/project/paddleocr,2024-07-17 10:49:23.000,92.0,470730.0,,,,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +48,DeepSpeed,microsoft/DeepSpeed,distributed-ml,,https://github.com/microsoft/DeepSpeed,https://github.com/microsoft/DeepSpeed,Apache-2.0,2020-01-23 18:35:18.000,2024-09-05 01:34:45.000000,2024-09-05 01:34:42,2470.0,148.0,4042.0,343.0,2922.0,1123.0,1706.0,34617.0,"DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and..",340.0,41,True,2024-09-05 01:33:59.000,0.15.1,95.0,deepspeed,,,['pytorch'],,461111.0,8778.0,8581.0,https://pypi.org/project/deepspeed,2024-09-05 01:33:59.000,197.0,460783.0,,,,1.0,deepspeed/deepspeed,https://hub.docker.com/r/deepspeed/deepspeed,2022-09-02 00:25:31.275782,4.0,18380.0,,,,,,,,,,,,,,,,,,,, +49,Faiss,facebookresearch/faiss,nn-search,,https://github.com/facebookresearch/faiss,https://github.com/facebookresearch/faiss,MIT,2017-02-07 16:07:05.000,2024-09-05 05:19:57.000000,2024-09-05 05:17:02,1219.0,91.0,3540.0,482.0,1147.0,236.0,2244.0,30340.0,A library for efficient similarity search and clustering of dense vectors.,187.0,41,True,2024-08-30 07:29:13.000,2.4.6,100.0,pymilvus,conda-forge/faiss,,,,825509.0,4099.0,3940.0,https://pypi.org/project/pymilvus,2024-08-30 07:29:13.000,159.0,794245.0,https://anaconda.org/conda-forge/faiss,2024-08-09 18:17:48.122,1594497.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +50,Milvus,milvus-io/milvus,nn-search,,https://github.com/milvus-io/milvus,https://github.com/milvus-io/milvus,Apache-2.0,2019-09-16 06:43:43.000,2024-09-05 13:09:28.364231,2024-09-05 12:01:05,20670.0,668.0,2799.0,275.0,22168.0,700.0,10976.0,29302.0,"A cloud-native vector database, storage for next generation AI applications.",288.0,41,True,2024-08-30 09:21:31.000,2.4.10,100.0,pymilvus,,,,259969.0,1904227.0,159.0,,https://pypi.org/project/pymilvus,2024-08-30 07:29:13.000,159.0,794245.0,,,,1.0,milvusdb/milvus,https://hub.docker.com/r/milvusdb/milvus,2024-09-05 13:09:28.364231,59.0,66334585.0,,,,,,,,,,,,,,,,,,,, +51,gensim,RaRe-Technologies/gensim,nlp,,https://github.com/piskvorky/gensim,https://github.com/piskvorky/gensim,LGPL-2.1,2011-02-10 07:43:04.000,2024-09-03 16:06:08.530000,2024-08-10 11:58:54,4534.0,14.0,4374.0,430.0,1708.0,382.0,1465.0,15547.0,Topic Modelling for Humans.,458.0,41,True,2024-07-19 14:39:26.000,4.3.3,94.0,gensim,conda-forge/gensim,,,4722.0,4201043.0,65193.0,63837.0,https://pypi.org/project/gensim,2024-07-19 14:39:26.000,1356.0,4168453.0,https://anaconda.org/conda-forge/gensim,2024-09-03 16:06:08.530,1366943.0,1.0,,,,,,,,piskvorky/gensim,,,,,,,,,,,,,,,,, +52,sentence-transformers,UKPLab/sentence-transformers,nlp,,https://github.com/UKPLab/sentence-transformers,https://github.com/UKPLab/sentence-transformers,Apache-2.0,2019-07-24 10:53:51.000,2024-08-30 08:44:27.000000,2024-08-30 08:44:27,1533.0,46.0,2427.0,138.0,526.0,1166.0,991.0,14780.0,State-of-the-Art Text Embeddings.,179.0,41,True,2024-06-07 13:01:30.000,3.0.1,53.0,sentence-transformers,conda-forge/sentence-transformers,,['pytorch'],,4913606.0,47128.0,45545.0,https://pypi.org/project/sentence-transformers,2024-06-07 13:01:10.000,1583.0,4905931.0,https://anaconda.org/conda-forge/sentence-transformers,2024-06-07 15:19:38.412,368404.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +53,yfinance,ranaroussi/yfinance,financial-data,,https://github.com/ranaroussi/yfinance,https://github.com/ranaroussi/yfinance,Apache-2.0,2017-05-21 10:16:15.000,2024-09-04 21:20:43.000000,2024-08-26 18:27:55,1294.0,66.0,2284.0,241.0,592.0,177.0,1170.0,12908.0,Download market data from Yahoo! Finances API.,122.0,41,True,2024-08-24 20:39:46.000,0.2.43,115.0,yfinance,ranaroussi/yfinance,,,,1966258.0,46265.0,45638.0,https://pypi.org/project/yfinance,2024-08-24 20:39:46.000,627.0,1963773.0,https://anaconda.org/ranaroussi/yfinance,2023-06-16 19:26:44.442,94462.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +54,PyMC3,pymc-devs/pymc,probabilistics,,https://github.com/pymc-devs/pymc,https://github.com/pymc-devs/pymc,Apache-2.0,2009-05-05 09:43:50.000,2024-09-03 15:45:07.000000,2024-09-03 15:45:06,10032.0,110.0,1986.0,224.0,4045.0,298.0,3055.0,8612.0,Bayesian Modeling and Probabilistic Programming in Python.,503.0,41,True,2024-07-11 13:49:51.000,5.16.2,89.0,pymc3,conda-forge/pymc3,,,1947.0,275288.0,4163.0,3971.0,https://pypi.org/project/pymc3,2024-05-31 12:35:21.000,192.0,263601.0,https://anaconda.org/conda-forge/pymc3,2024-06-02 18:14:42.309,595236.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +55,Catboost,catboost/catboost,ml-frameworks,,https://github.com/catboost/catboost,https://github.com/catboost/catboost,Apache-2.0,2017-07-18 05:29:04.000,2024-09-05 10:03:09.000000,2024-09-05 06:08:28,48537.0,505.0,1176.0,192.0,394.0,544.0,1777.0,7987.0,"A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification,..",1270.0,41,True,2024-09-05 10:59:44.000,1.2.6,112.0,catboost,conda-forge/catboost,,,294391.0,2650894.0,549.0,14.0,https://pypi.org/project/catboost,2024-09-05 10:03:09.000,535.0,2610929.0,https://anaconda.org/conda-forge/catboost,2024-04-18 20:39:24.300,1677221.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +56,SageMaker SDK,aws/sagemaker-python-sdk,ml-experiments,,https://github.com/aws/sagemaker-python-sdk,https://github.com/aws/sagemaker-python-sdk,Apache-2.0,2017-11-14 01:03:33.000,2024-09-04 20:23:27.000000,2024-09-04 20:23:27,3828.0,127.0,1129.0,137.0,3174.0,307.0,1203.0,2088.0,A library for training and deploying machine learning models on Amazon SageMaker.,456.0,41,True,2024-08-30 17:42:25.000,2.231.0,604.0,sagemaker,conda-forge/sagemaker-python-sdk,,"['mxnet', 'tensorflow']",,33835130.0,4482.0,4339.0,https://pypi.org/project/sagemaker,2024-08-30 17:42:25.000,143.0,33814126.0,https://anaconda.org/conda-forge/sagemaker-python-sdk,2024-07-31 06:30:51.886,1029235.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +57,Fastai,fastai/fastai,ml-frameworks,,https://github.com/fastai/fastai,https://github.com/fastai/fastai,Apache-2.0,2017-09-09 17:43:36.000,2024-08-27 06:50:53.000000,2024-08-27 06:50:42,2786.0,18.0,7546.0,607.0,2231.0,222.0,1593.0,26074.0,The fastai deep learning library.,670.0,40,True,2024-08-27 06:50:53.000,2.7.17,151.0,fastai,,,['pytorch'],,315129.0,18794.0,18490.0,https://pypi.org/project/fastai,2024-08-27 06:50:53.000,304.0,315129.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +58,PyTorch Geometric,pyg-team/pytorch_geometric,graph,,https://github.com/pyg-team/pytorch_geometric,https://github.com/pyg-team/pytorch_geometric,MIT,2017-10-06 16:03:03.000,2024-09-03 08:25:22.000000,2024-09-03 08:25:22,7613.0,77.0,3605.0,252.0,3111.0,1016.0,2654.0,20905.0,Graph Neural Network Library for PyTorch.,517.0,40,True,2024-04-19 11:59:51.000,2.5.3,44.0,torch-geometric,conda-forge/pytorch_geometric,,['pytorch'],,389778.0,6701.0,6377.0,https://pypi.org/project/torch-geometric,2024-04-19 11:59:51.000,324.0,388189.0,https://anaconda.org/conda-forge/pytorch_geometric,2024-08-16 19:08:43.757,79465.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +59,Albumentations,albumentations-team/albumentations,image,,https://github.com/albumentations-team/albumentations,https://github.com/albumentations-team/albumentations,MIT,2018-06-06 03:10:50.000,2024-09-02 16:21:40.000000,2024-09-02 16:21:40,978.0,74.0,1621.0,128.0,885.0,371.0,649.0,13988.0,Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125.,149.0,40,True,2024-08-16 00:23:18.000,1.4.14,69.0,albumentations,conda-forge/albumentations,,['pytorch'],,4533041.0,27156.0,26604.0,https://pypi.org/project/albumentations,2024-08-16 00:23:18.000,552.0,4529241.0,https://anaconda.org/conda-forge/albumentations,2024-08-20 07:47:48.612,190041.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +60,dlib,davisking/dlib,ml-frameworks,,https://github.com/davisking/dlib,https://github.com/davisking/dlib,BSL-1.0,2014-01-29 00:45:33.000,2024-09-01 13:05:09.000000,2024-09-01 13:05:09,8276.0,13.0,3351.0,478.0,711.0,50.0,2168.0,13347.0,A toolkit for making real world machine learning and data analysis applications in C++.,197.0,40,False,2024-08-09 19:26:11.000,19.24.6,39.0,dlib,conda-forge/dlib,,,25490.0,357231.0,30004.0,29791.0,https://pypi.org/project/dlib,2024-08-09 19:21:06.000,213.0,340590.0,https://anaconda.org/conda-forge/dlib,2024-08-31 20:33:43.161,837060.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +61,Tokenizers,huggingface/tokenizers,nlp,,https://github.com/huggingface/tokenizers,https://github.com/huggingface/tokenizers,Apache-2.0,2019-11-01 17:52:20.000,2024-09-03 22:28:12.000000,2024-08-12 05:35:33,1813.0,38.0,762.0,120.0,638.0,33.0,943.0,8870.0,Fast State-of-the-Art Tokenizers optimized for Research and Production.,93.0,40,True,2024-08-08 16:56:21.000,0.20.0,97.0,tokenizers,conda-forge/tokenizers,,,57.0,28598184.0,100087.0,99175.0,https://pypi.org/project/tokenizers,2024-08-08 16:55:26.000,912.0,28558418.0,https://anaconda.org/conda-forge/tokenizers,2024-08-12 03:17:57.893,1988293.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +62,speechbrain,speechbrain/speechbrain,audio,,https://github.com/speechbrain/speechbrain,https://github.com/speechbrain/speechbrain,Apache-2.0,2020-04-28 17:48:45.000,2024-09-05 14:19:42.000000,2024-09-05 14:19:42,9909.0,73.0,1351.0,131.0,1244.0,146.0,973.0,8514.0,A PyTorch-based Speech Toolkit.,240.0,40,True,2024-09-02 14:04:56.000,1.0.1,17.0,speechbrain,,,['pytorch'],,4037771.0,2275.0,2213.0,https://pypi.org/project/speechbrain,2024-09-02 14:25:26.000,62.0,4037771.0,,,,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +63,accelerate,huggingface/accelerate,pytorch-utils,,https://github.com/huggingface/accelerate,https://github.com/huggingface/accelerate,Apache-2.0,2020-10-30 13:27:12.000,2024-09-05 15:38:47.000000,2024-09-05 15:38:47,1547.0,91.0,925.0,95.0,1515.0,145.0,1434.0,7626.0,"A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic..",286.0,40,True,2024-09-05 15:36:16.000,0.34.1,57.0,accelerate,conda-forge/accelerate,,['pytorch'],,6517938.0,50432.0,49008.0,https://pypi.org/project/accelerate,2024-09-05 15:33:32.000,1424.0,6512326.0,https://anaconda.org/conda-forge/accelerate,2024-09-03 15:48:09.434,196424.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +64,Shapely,shapely/shapely,geospatial-data,,https://github.com/shapely/shapely,https://github.com/shapely/shapely,BSD-3-Clause,2011-12-31 19:43:11.000,2024-09-03 20:47:21.021000,2024-09-03 08:58:09,2299.0,32.0,565.0,90.0,866.0,288.0,939.0,3827.0,Manipulation and analysis of geometric objects.,158.0,40,True,2024-08-19 21:56:13.000,2.0.6,125.0,shapely,conda-forge/shapely,,,3635.0,32501511.0,81108.0,78173.0,https://pypi.org/project/shapely,2024-08-19 21:56:13.000,2935.0,32294031.0,https://anaconda.org/conda-forge/shapely,2024-09-03 20:47:21.021,10161508.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +65,dask.distributed,dask/distributed,distributed-ml,,https://github.com/dask/distributed,https://github.com/dask/distributed,BSD-3-Clause,2015-09-13 18:42:29.000,2024-09-05 08:13:24.000000,2024-09-04 16:38:14,5884.0,110.0,715.0,56.0,5135.0,1571.0,2364.0,1565.0,A distributed task scheduler for Dask.,328.0,40,True,2024-08-30 20:43:22.000,2024.8.2,238.0,distributed,conda-forge/distributed,,,,6095513.0,36963.0,36149.0,https://pypi.org/project/distributed,2024-08-30 20:43:22.000,814.0,5812010.0,https://anaconda.org/conda-forge/distributed,2024-08-30 22:53:22.106,14742163.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +66,OpenAI Gym,openai/gym,reinforcement-learning,,https://github.com/openai/gym,https://github.com/openai/gym,MIT,2016-04-27 14:59:16.000,2024-05-02 16:09:06.000000,2023-01-30 18:15:21,1757.0,,8590.0,1058.0,1452.0,102.0,1722.0,34440.0,A toolkit for developing and comparing reinforcement learning algorithms.,383.0,39,False,2023-07-20 15:30:49.667,0.0.1,108.0,gym,conda-forge/gym,,,,629681.0,58077.0,56529.0,https://pypi.org/project/gym,2023-07-20 15:30:49.667,1548.0,623777.0,https://anaconda.org/conda-forge/gym,2023-06-16 19:18:41.854,312958.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +67,Jina,jina-ai/jina,ml-frameworks,,https://github.com/jina-ai/jina,https://github.com/jina-ai/jina,Apache-2.0,2020-02-13 17:04:44.000,2024-09-05 10:11:47.000000,2024-09-05 09:59:32,8569.0,29.0,2220.0,211.0,4193.0,22.0,1936.0,20871.0,Build multimodal AI applications with cloud-native stack.,177.0,39,True,2024-09-05 09:59:53.000,3.27.5,2469.0,jina,conda-forge/jina-core,,,,90464.0,1786.0,1759.0,https://pypi.org/project/jina,2024-09-05 09:58:58.000,27.0,57532.0,https://anaconda.org/conda-forge/jina-core,2023-06-16 19:27:18.682,73081.0,2.0,jinaai/jina,https://hub.docker.com/r/jinaai/jina,2024-09-05 10:08:16.457296,8.0,1699656.0,,,,,,,,,,,,,,,,,,,, +68,Rasa,RasaHQ/rasa,nlp,,https://github.com/RasaHQ/rasa,https://github.com/RasaHQ/rasa,Apache-2.0,2016-10-14 12:27:49.000,2024-08-14 14:44:40.000000,2024-03-21 15:05:22,32610.0,,4591.0,352.0,6369.0,124.0,6642.0,18587.0,"Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management,..",596.0,39,True,2024-04-18 15:06:29.000,3.6.20,373.0,rasa,,,['tensorflow'],,141768.0,4482.0,4422.0,https://pypi.org/project/rasa,2024-04-18 15:06:12.000,60.0,141768.0,,,,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +69,flair,flairNLP/flair,nlp,,https://github.com/flairNLP/flair,https://github.com/flairNLP/flair,MIT,2018-06-11 11:04:18.000,2024-09-03 11:27:56.000000,2024-08-30 09:20:57,6142.0,168.0,2088.0,201.0,1226.0,110.0,2213.0,13800.0,A very simple framework for state-of-the-art Natural Language Processing (NLP).,270.0,39,True,2024-07-25 12:21:58.000,0.14.0,33.0,flair,conda-forge/python-flair,,['pytorch'],,86410.0,3621.0,3480.0,https://pypi.org/project/flair,2024-07-25 12:15:28.000,141.0,85803.0,https://anaconda.org/conda-forge/python-flair,2024-01-05 20:59:40.138,30364.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +70,dgl,dmlc/dgl,graph,,https://github.com/dmlc/dgl,https://github.com/dmlc/dgl,Apache-2.0,2018-04-20 14:49:09.000,2024-09-05 06:59:25.000000,2024-09-05 06:59:25,4384.0,257.0,2997.0,172.0,5012.0,524.0,2349.0,13338.0,"Python package built to ease deep learning on graph, on top of existing DL frameworks.",295.0,39,True,2024-09-03 04:16:25.000,2.4.0,453.0,dgl,,,,,112876.0,433.0,285.0,https://pypi.org/project/dgl,2024-05-13 01:10:39.000,148.0,112876.0,,,,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +71,CuPy,cupy/cupy,gpu-utilities,,https://github.com/cupy/cupy,https://github.com/cupy/cupy,MIT,2016-11-01 09:54:45.000,2024-08-30 05:10:50.000000,2024-08-30 05:10:49,28935.0,315.0,805.0,126.0,6318.0,636.0,1712.0,8107.0,NumPy & SciPy for GPU.,385.0,39,True,2024-08-22 07:42:45.000,13.3.0,141.0,cupy,conda-forge/cupy,,,182316.0,119156.0,2492.0,2226.0,https://pypi.org/project/cupy,2024-08-22 07:08:16.000,266.0,28953.0,https://anaconda.org/conda-forge/cupy,2024-08-22 12:51:10.755,4512558.0,1.0,cupy/cupy,https://hub.docker.com/r/cupy/cupy,2024-08-22 07:44:42.171252,13.0,66167.0,,,,,,,,,,,,,,,,,,,, +72,sktime,alan-turing-institute/sktime,time-series-data,,https://github.com/sktime/sktime,https://github.com/sktime/sktime,BSD-3-Clause,2018-11-06 15:08:24.000,2024-09-05 14:53:52.000000,2024-09-05 14:52:15,4869.0,262.0,1311.0,102.0,4145.0,932.0,1563.0,7731.0,A unified framework for machine learning with time series.,389.0,39,True,2024-08-27 11:56:34.000,0.32.3,78.0,sktime,conda-forge/sktime-all-extras,,['sklearn'],96.0,722930.0,3320.0,3200.0,https://pypi.org/project/sktime,2024-08-27 11:56:34.000,120.0,696509.0,https://anaconda.org/conda-forge/sktime-all-extras,2024-08-27 19:11:08.275,1003993.0,1.0,,,,,,,,sktime/sktime,,,,,,,,,,,,,,,,, +73,folium,python-visualization/folium,geospatial-data,,https://github.com/python-visualization/folium,https://github.com/python-visualization/folium,MIT,2013-05-09 04:21:35.000,2024-09-04 07:45:40.000000,2024-09-04 07:45:33,1880.0,24.0,2220.0,163.0,867.0,88.0,1027.0,6841.0,Python Data. Leaflet.js Maps.,170.0,39,True,2024-06-16 15:22:45.000,0.17.0,32.0,folium,conda-forge/folium,,,,1504780.0,42873.0,42161.0,https://pypi.org/project/folium,2024-06-16 15:22:45.000,712.0,1436271.0,https://anaconda.org/conda-forge/folium,2024-06-17 06:35:28.582,3014422.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +74,GeoPandas,geopandas/geopandas,geospatial-data,,https://github.com/geopandas/geopandas,https://github.com/geopandas/geopandas,BSD-3-Clause,2013-06-27 17:03:47.000,2024-09-01 08:07:48.000000,2024-09-01 08:07:48,2019.0,41.0,919.0,104.0,1683.0,440.0,1259.0,4428.0,Python tools for geographic data.,234.0,39,True,2024-07-02 12:26:55.000,1.0.1,57.0,geopandas,conda-forge/geopandas,,['pandas'],2665.0,6666206.0,42567.0,39820.0,https://pypi.org/project/geopandas,2024-07-02 12:26:50.000,2747.0,6589249.0,https://anaconda.org/conda-forge/geopandas,2024-07-02 15:18:57.572,3923462.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +75,TensorFlow Datasets,tensorflow/datasets,tensorflow-utils,,https://github.com/tensorflow/datasets,https://github.com/tensorflow/datasets,Apache-2.0,2018-09-10 21:27:22.000,2024-09-05 14:30:29.000000,2024-09-05 14:30:21,6445.0,117.0,1530.0,109.0,4401.0,681.0,742.0,4266.0,"TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...",312.0,39,True,2024-06-05 08:15:47.000,4.9.6,39.0,tensorflow-datasets,conda-forge/tensorflow-datasets,,['tensorflow'],,1555850.0,19425.0,19099.0,https://pypi.org/project/tensorflow-datasets,2024-06-05 08:15:42.000,326.0,1555002.0,https://anaconda.org/conda-forge/tensorflow-datasets,2023-06-16 19:25:46.849,33934.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +76,MNE,mne-tools/mne-python,medical-data,,https://github.com/mne-tools/mne-python,https://github.com/mne-tools/mne-python,BSD-3-Clause,2011-01-28 03:31:13.000,2024-09-04 18:05:33.000000,2024-09-04 18:05:32,18102.0,110.0,1306.0,81.0,7982.0,527.0,4349.0,2661.0,MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python.,378.0,39,True,2024-08-19 02:18:45.000,1.8.0,80.0,mne,conda-forge/mne,,,,159291.0,4693.0,4313.0,https://pypi.org/project/mne,2024-08-19 02:18:45.000,380.0,151306.0,https://anaconda.org/conda-forge/mne,2024-08-19 02:39:24.602,415234.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +77,PyFlink,apache/flink,ml-frameworks,,https://github.com/apache/flink,https://github.com/apache/flink,Apache-2.0,2014-06-07 07:00:10.000,2024-09-05 03:22:35.000000,2024-09-05 03:22:35,35757.0,327.0,13217.0,947.0,25277.0,1220.0,,23766.0,Apache Flink Python API.,1904.0,38,True,2024-06-14 14:43:26.000,1.19.1,49.0,apache-flink,,,,,150523.0,56.0,21.0,https://pypi.org/project/apache-flink,2024-08-01 04:14:17.000,35.0,150523.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +78,MXNet,apache/incubator-mxnet,ml-frameworks,,https://github.com/apache/mxnet,https://github.com/apache/mxnet,Apache-2.0,2015-04-30 16:21:15.000,2023-10-25 21:28:33.000000,2023-01-26 21:28:45,11896.0,,6800.0,1069.0,11114.0,1804.0,7751.0,20761.0,"Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler;..",981.0,38,False,2022-10-24 07:38:03.000,1.9.1,983.0,mxnet,mxnet,,['mxnet'],27439.0,471183.0,7594.0,7470.0,https://pypi.org/project/mxnet,2022-05-17 21:11:13.000,118.0,470773.0,https://anaconda.org/anaconda/mxnet,2023-06-16 13:24:22.589,11052.0,2.0,,,,,,,,apache/mxnet,,,,,,,,,6.0,,,,,,,, +79,pyecharts,pyecharts/pyecharts,data-viz,,https://github.com/pyecharts/pyecharts,https://github.com/pyecharts/pyecharts,MIT,2017-06-22 02:50:25.000,2024-07-10 02:16:05.000000,2024-06-20 12:51:40,1687.0,22.0,2841.0,378.0,467.0,4.0,1894.0,14749.0,Python Echarts Plotting Library.,44.0,38,True,2024-06-20 15:50:49.000,2.0.6,74.0,pyecharts,,https://github.com/pyecharts/pyecharts/blob/master/README.en.md,['jupyter'],68.0,134092.0,4616.0,4407.0,https://pypi.org/project/pyecharts,2024-06-20 15:48:17.000,209.0,134089.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +80,MoviePy,Zulko/moviepy,image,,https://github.com/Zulko/moviepy,https://github.com/Zulko/moviepy,MIT,2013-08-12 09:39:28.000,2024-08-20 10:05:57.000000,2024-05-27 18:04:07,1101.0,,1540.0,257.0,682.0,473.0,1058.0,12312.0,Video editing with Python.,161.0,38,True,2020-05-07 16:29:35.000,1.0.3,85.0,moviepy,conda-forge/moviepy,,,,1308586.0,45249.0,44335.0,https://pypi.org/project/moviepy,2021-12-15 14:41:26.454,914.0,1305513.0,https://anaconda.org/conda-forge/moviepy,2023-06-16 13:23:34.876,264311.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +81,sentencepiece,google/sentencepiece,nlp,,https://github.com/google/sentencepiece,https://github.com/google/sentencepiece,Apache-2.0,2017-03-07 10:03:48.000,2024-09-01 15:52:35.000000,2024-08-18 00:47:35,986.0,23.0,1157.0,124.0,307.0,31.0,710.0,10030.0,Unsupervised text tokenizer for Neural Network-based text generation.,89.0,38,True,2024-02-19 17:03:42.000,0.2.0,35.0,sentencepiece,conda-forge/sentencepiece,,,40987.0,22188381.0,77472.0,75740.0,https://pypi.org/project/sentencepiece,2024-02-19 17:03:42.000,1732.0,22167848.0,https://anaconda.org/conda-forge/sentencepiece,2024-08-23 08:25:25.532,998617.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +82,Kornia,kornia/kornia,image,,https://github.com/kornia/kornia,https://github.com/kornia/kornia,Apache-2.0,2018-08-22 10:31:37.000,2024-09-03 21:17:53.000000,2024-09-02 21:37:48,2793.0,49.0,955.0,128.0,1926.0,287.0,654.0,9767.0,Geometric Computer Vision Library for Spatial AI.,266.0,38,True,2024-06-28 15:16:20.000,0.7.3,40.0,kornia,conda-forge/kornia,,['pytorch'],1391.0,1889460.0,11738.0,11476.0,https://pypi.org/project/kornia,2024-06-28 15:16:20.000,262.0,1886240.0,https://anaconda.org/conda-forge/kornia,2024-06-28 20:04:02.857,144063.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +83,PyCaret,pycaret/pycaret,ml-experiments,,https://github.com/pycaret/pycaret,https://github.com/pycaret/pycaret,MIT,2019-11-23 18:40:48.000,2024-08-30 03:35:21.000000,2024-08-30 03:34:11,5357.0,122.0,1748.0,134.0,1019.0,364.0,1947.0,8792.0,"An open-source, low-code machine learning library in Python.",141.0,38,True,2024-04-28 18:46:27.000,3.3.2,98.0,pycaret,conda-forge/pycaret,,,705.0,268851.0,6290.0,6259.0,https://pypi.org/project/pycaret,2024-04-28 18:46:21.000,31.0,267746.0,https://anaconda.org/conda-forge/pycaret,2024-04-25 15:07:46.052,53495.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +84,PyVista,pyvista/pyvista,data-viz,,https://github.com/pyvista/pyvista,https://github.com/pyvista/pyvista,MIT,2017-05-31 18:01:42.000,2024-09-05 13:39:02.000000,2024-09-05 13:38:11,4704.0,245.0,472.0,35.0,3635.0,602.0,1119.0,2581.0,3D plotting and mesh analysis through a streamlined interface for the Visualization Toolkit (VTK).,162.0,38,True,2024-07-22 04:26:19.000,0.44.1,98.0,pyvista,conda-forge/pyvista,,['jupyter'],810.0,276368.0,3893.0,3366.0,https://pypi.org/project/pyvista,2024-07-20 05:33:22.000,527.0,265749.0,https://anaconda.org/conda-forge/pyvista,2024-07-20 12:44:44.232,541131.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +85,huggingface_hub,huggingface/huggingface_hub,model-serialisation,,https://github.com/huggingface/huggingface_hub,https://github.com/huggingface/huggingface_hub,Apache-2.0,2020-12-22 10:20:28.000,2024-09-05 14:01:57.000000,2024-09-05 07:46:04,1544.0,108.0,511.0,59.0,1486.0,144.0,774.0,1960.0,The official Python client for the Huggingface Hub.,193.0,38,True,2024-08-19 15:17:05.000,0.24.6,122.0,huggingface_hub,conda-forge/huggingface_hub,,,,40978066.0,1696.0,,https://pypi.org/project/huggingface_hub,2024-08-19 15:15:01.000,1696.0,40929582.0,https://anaconda.org/conda-forge/huggingface_hub,2024-08-19 22:26:15.558,2084843.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +86,imageio,imageio/imageio,image,,https://github.com/imageio/imageio,https://github.com/imageio/imageio,BSD-2-Clause,2013-05-04 22:56:45.000,2024-08-19 12:09:51.456000,2024-08-19 02:35:18,1541.0,9.0,290.0,31.0,494.0,98.0,507.0,1457.0,Python library for reading and writing image data.,114.0,38,True,2024-08-19 02:35:29.000,2.35.1,94.0,imageio,conda-forge/imageio,,,1174.0,26056186.0,141223.0,138868.0,https://pypi.org/project/imageio,2024-08-19 02:35:25.000,2355.0,25919460.0,https://anaconda.org/conda-forge/imageio,2024-08-19 12:09:51.456,6835506.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +87,jieba,fxsjy/jieba,chinese-nlp,,https://github.com/fxsjy/jieba,https://github.com/fxsjy/jieba,MIT,2012-09-29 07:52:01.000,2024-08-21 09:23:45.000000,2020-02-15 08:33:35,523.0,,6713.0,1282.0,167.0,674.0,227.0,33051.0,Chinese Words Segmentation Utilities.,49.0,37,False,2020-01-20 14:27:23.000,0.42.1,32.0,jieba,conda-forge/jieba,,,,1471478.0,31437.0,30621.0,https://pypi.org/project/jieba,2020-01-20 14:27:23.000,816.0,1469680.0,https://anaconda.org/conda-forge/jieba,2023-06-16 13:21:35.778,160075.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +88,MMDetection,open-mmlab/mmdetection,image,,https://github.com/open-mmlab/mmdetection,https://github.com/open-mmlab/mmdetection,Apache-2.0,2018-08-22 07:06:06.000,2024-08-21 02:01:07.000000,2024-02-05 13:23:18,2706.0,,9357.0,369.0,3153.0,1751.0,6702.0,29008.0,OpenMMLab Detection Toolbox and Benchmark.,480.0,37,True,2024-01-05 06:25:30.000,3.3.0,53.0,mmdet,,,['pytorch'],,190801.0,2990.0,2909.0,https://pypi.org/project/mmdet,2024-01-05 06:25:30.000,81.0,190801.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +89,Netron,lutzroeder/netron,interpretability,,https://github.com/lutzroeder/netron,https://github.com/lutzroeder/netron,MIT,2010-12-26 12:53:43.000,2024-09-05 07:12:07.000000,2024-09-05 07:11:35,8397.0,328.0,2732.0,297.0,218.0,21.0,1098.0,27433.0,"Visualizer for neural network, deep learning and machine learning models.",2.0,37,True,2024-08-30 11:38:30.000,7.8.5,662.0,netron,,,"['pytorch', 'tensorflow']",98619.0,132315.0,634.0,551.0,https://pypi.org/project/netron,2024-08-30 11:38:30.000,83.0,33696.0,,,,1.0,,,,,,3.0,,,,,,,,,,,,,,,,,,, +90,InsightFace,deepinsight/insightface,image,,https://github.com/deepinsight/insightface,https://github.com/deepinsight/insightface,MIT,2017-09-01 00:36:51.000,2024-08-30 11:23:11.000000,2024-08-30 11:23:11,2332.0,39.0,5316.0,511.0,174.0,1115.0,1370.0,22733.0,State-of-the-art 2D and 3D Face Analysis Project.,61.0,37,True,2023-04-02 08:03:01.222,0.7.3,28.0,insightface,,,['mxnet'],4473507.0,608441.0,2652.0,2623.0,https://pypi.org/project/insightface,2022-12-17 02:14:00.699,29.0,345294.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +91,imgaug,aleju/imgaug,image,,https://github.com/aleju/imgaug,https://github.com/aleju/imgaug,MIT,2015-07-10 20:31:33.000,2024-07-30 01:38:33.000000,2020-06-01 14:58:26,2913.0,,2430.0,230.0,339.0,304.0,225.0,14332.0,Image augmentation for machine learning experiments.,36.0,37,False,2020-02-06 06:18:40.000,0.4.0,11.0,imgaug,conda-forge/imgaug,,,,541462.0,21729.0,21464.0,https://pypi.org/project/imgaug,2020-02-05 20:54:22.000,265.0,538701.0,https://anaconda.org/conda-forge/imgaug,2023-06-16 16:15:24.882,174003.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +92,pandas-profiling,ydataai/pandas-profiling,data-viz,,https://github.com/ydataai/ydata-profiling,https://github.com/ydataai/ydata-profiling,MIT,2016-01-09 23:47:55.000,2024-09-03 15:47:14.000000,2024-09-03 09:14:49,1479.0,33.0,1664.0,152.0,806.0,231.0,571.0,12370.0,1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.,130.0,37,True,2024-07-15 18:20:05.000,4.9.0,62.0,pandas-profiling,conda-forge/pandas-profiling,,"['jupyter', 'pandas']",152.0,336457.0,4173.0,3990.0,https://pypi.org/project/pandas-profiling,2023-02-03 17:59:40.571,183.0,331726.0,https://anaconda.org/conda-forge/pandas-profiling,2023-06-16 13:22:30.453,458902.0,2.0,,,,,,,,ydataai/ydata-profiling,,,,,,,,,,,,,,,,, +93,deepface,serengil/deepface,image,,https://github.com/serengil/deepface,https://github.com/serengil/deepface,MIT,2020-02-08 20:42:28.000,2024-09-03 08:56:11.000000,2024-09-03 08:56:11,1631.0,143.0,1980.0,142.0,233.0,6.0,1093.0,11656.0,"A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python.",66.0,37,True,2024-08-17 07:30:49.000,0.0.93,92.0,deepface,,,,,97628.0,3954.0,3912.0,https://pypi.org/project/deepface,2024-08-17 07:24:30.000,42.0,97628.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +94,Theano,Theano/Theano,ml-frameworks,,https://github.com/Theano/Theano,https://github.com/Theano/Theano,BSD-3-Clause,2011-08-10 03:48:06.000,2024-01-15 03:16:24.000000,2024-01-15 03:16:24,28133.0,,2483.0,539.0,4118.0,694.0,2087.0,9881.0,"Theano was a Python library that allows you to define, optimize, and evaluate mathematical expressions involving..",386.0,37,True,2020-07-27 16:13:54.000,1.0.5,45.0,theano,conda-forge/theano,,,,114999.0,15612.0,15440.0,https://pypi.org/project/theano,2020-07-27 16:13:54.000,172.0,90081.0,https://anaconda.org/conda-forge/theano,2023-06-16 13:23:49.668,2442032.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +95,PySyft,OpenMined/PySyft,privacy-ml,,https://github.com/OpenMined/PySyft,https://github.com/OpenMined/PySyft,Apache-2.0,2017-07-18 20:41:16.000,2024-09-05 15:10:11.000000,2024-09-05 14:15:14,32493.0,2269.0,1991.0,199.0,5787.0,37.0,3389.0,9426.0,Perform data science on data that remains in someone elses server.,515.0,37,True,2024-09-04 20:09:29.000,0.9.1,313.0,syft,,,['pytorch'],2154.0,12410.0,4.0,1.0,https://pypi.org/project/syft,2024-09-05 07:00:58.000,3.0,12195.0,,,,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +96,TextBlob,sloria/TextBlob,nlp,,https://github.com/sloria/TextBlob,https://github.com/sloria/TextBlob,MIT,2013-06-30 18:29:18.000,2024-09-02 22:04:30.000000,2024-08-07 18:02:18,598.0,13.0,1129.0,262.0,192.0,106.0,171.0,9078.0,"Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation,..",37.0,37,True,2024-02-15 20:31:28.000,0.18.0,61.0,textblob,conda-forge/textblob,,,121.0,2097572.0,42402.0,42028.0,https://pypi.org/project/textblob,2024-02-15 20:39:47.000,374.0,2094874.0,https://anaconda.org/conda-forge/textblob,2023-06-16 13:22:54.304,261741.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +97,espnet,espnet/espnet,audio,,https://github.com/espnet/espnet,https://github.com/espnet/espnet,Apache-2.0,2017-12-13 00:45:11.000,2024-09-04 18:48:43.000000,2024-09-04 18:25:41,22063.0,462.0,2146.0,180.0,3355.0,341.0,2075.0,8262.0,End-to-End Speech Processing Toolkit.,446.0,37,True,2024-02-06 03:28:17.000,.202402,52.0,espnet,,,,81.0,50479.0,381.0,369.0,https://pypi.org/project/espnet,2024-02-06 03:28:41.000,12.0,50478.0,,,,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +98,Flax,google/flax,ml-frameworks,,https://github.com/google/flax,https://github.com/google/flax,Apache-2.0,2020-01-10 09:48:37.000,2024-09-05 11:56:43.000000,2024-09-05 01:28:59,4653.0,173.0,623.0,85.0,2528.0,262.0,730.0,5929.0,Flax is a neural network library for JAX that is designed for flexibility.,236.0,37,True,2024-08-27 17:51:42.000,0.9.0,47.0,flax,conda-forge/flax,,['jax'],51.0,668380.0,9420.0,8969.0,https://pypi.org/project/flax,2024-08-27 17:51:42.000,451.0,666738.0,https://anaconda.org/conda-forge/flax,2024-08-27 20:55:17.110,68970.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +99,PyQtGraph,pyqtgraph/pyqtgraph,data-viz,,https://github.com/pyqtgraph/pyqtgraph,https://github.com/pyqtgraph/pyqtgraph,MIT,2013-09-12 07:18:21.000,2024-08-22 17:31:22.000000,2024-08-22 17:31:17,4163.0,96.0,1096.0,153.0,1714.0,416.0,893.0,3838.0,Fast data visualization and GUI tools for scientific / engineering applications.,287.0,37,True,2024-04-29 02:18:56.000,0.13.7,25.0,pyqtgraph,conda-forge/pyqtgraph,,,,276665.0,11125.0,10126.0,https://pypi.org/project/pyqtgraph,2024-04-29 02:18:56.000,999.0,265181.0,https://anaconda.org/conda-forge/pyqtgraph,2024-05-02 20:24:38.556,585711.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +100,HoloViews,holoviz/holoviews,data-viz,,https://github.com/holoviz/holoviews,https://github.com/holoviz/holoviews,BSD-3-Clause,2014-05-07 16:59:22.000,2024-08-29 16:34:03.000000,2024-08-29 16:34:02,10829.0,39.0,401.0,59.0,3053.0,1101.0,2215.0,2684.0,"With Holoviews, your data visualizes itself.",144.0,37,True,2024-08-01 13:45:47.955,3.0.3,168.0,holoviews,conda-forge/holoviews,,['jupyter'],,676537.0,12230.0,11845.0,https://pypi.org/project/holoviews,2024-07-31 08:09:44.000,380.0,642079.0,https://anaconda.org/conda-forge/holoviews,2024-07-07 07:21:50.008,1748226.0,2.0,,,,,,,,,@pyviz/jupyterlab_pyviz,https://www.npmjs.com/package/@pyviz/jupyterlab_pyviz,2024-08-01 13:45:47.955,5.0,180.0,,,,,,,,,,,, +101,Rasterio,rasterio/rasterio,geospatial-data,,https://github.com/rasterio/rasterio,https://github.com/rasterio/rasterio,BSD-3-Clause,2013-11-04 16:36:27.000,2024-09-05 14:15:01.000000,2024-09-05 14:15:01,3883.0,33.0,524.0,146.0,1193.0,142.0,1667.0,2213.0,Rasterio reads and writes geospatial raster datasets.,158.0,37,True,2024-09-04 04:51:20.000,1.3.11,160.0,rasterio,conda-forge/rasterio,,,923.0,3266100.0,14204.0,12815.0,https://pypi.org/project/rasterio,2024-09-04 04:20:11.000,1389.0,3187374.0,https://anaconda.org/conda-forge/rasterio,2024-09-04 14:30:01.289,3463632.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +102,Fiona,Toblerity/Fiona,geospatial-data,,https://github.com/Toblerity/Fiona,https://github.com/Toblerity/Fiona,BSD-3-Clause,2011-12-31 19:47:00.000,2024-09-05 01:10:28.000000,2024-09-05 01:10:15,1554.0,27.0,202.0,47.0,599.0,31.0,769.0,1144.0,Fiona reads and writes geographic data files.,74.0,37,True,2024-09-04 03:19:07.000,1.10.0,116.0,fiona,conda-forge/fiona,,,,5109390.0,22432.0,22170.0,https://pypi.org/project/fiona,2024-09-04 01:14:04.000,262.0,4990988.0,https://anaconda.org/conda-forge/fiona,2024-09-04 14:00:00.641,5920141.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +103,horovod,horovod/horovod,distributed-ml,,https://github.com/horovod/horovod,https://github.com/horovod/horovod,Apache-2.0,2017-08-09 19:39:59.000,2024-08-31 11:57:00.000000,2024-08-31 11:55:45,1340.0,7.0,2222.0,334.0,1600.0,405.0,1860.0,14147.0,"Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.",173.0,36,True,2023-06-12 09:28:02.604,0.28.1,77.0,horovod,,,,,149620.0,1250.0,1217.0,https://pypi.org/project/horovod,2023-06-12 09:28:02.604,33.0,149620.0,,,,2.0,,,,,,,stable/horovod,,,,,,,,,,,,,,,,,, +104,ivy,unifyai/ivy,ml-frameworks,,https://github.com/ivy-llc/ivy,https://github.com/ivy-llc/ivy,Apache-2.0,2021-01-19 08:37:25.000,2024-09-05 04:04:49.000000,2024-09-05 04:04:48,18563.0,270.0,5801.0,70.0,11726.0,938.0,15954.0,14029.0,Convert Machine Learning Code Between Frameworks.,1480.0,36,True,2023-06-29 19:33:01.167,0.0.0,123.0,ivy,,,,,2044.0,12.0,,https://pypi.org/project/ivy,2024-08-09 04:51:17.000,12.0,2044.0,,,,2.0,,,,,,,,ivy-llc/ivy,,,,,,,,,,,,,,,,, +105,AllenNLP,allenai/allennlp,nlp,,https://github.com/allenai/allennlp,https://github.com/allenai/allennlp,Apache-2.0,2017-05-15 15:52:41.000,2023-06-16 16:12:37.768000,2022-11-22 00:42:46,2719.0,,2243.0,280.0,3096.0,91.0,2477.0,11730.0,"An open-source NLP research library, built on PyTorch.",267.0,36,False,2022-10-18 23:54:05.191,2.10.1,265.0,allennlp,conda-forge/allennlp,,['pytorch'],66.0,67572.0,4324.0,4199.0,https://pypi.org/project/allennlp,2022-10-18 23:54:05.191,125.0,65453.0,https://anaconda.org/conda-forge/allennlp,2023-06-16 16:12:37.768,146252.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +106,NeMo,NVIDIA/NeMo,nlp,,https://github.com/NVIDIA/NeMo,https://github.com/NVIDIA/NeMo,Apache-2.0,2019-08-05 20:16:42.000,2024-09-05 14:14:47.000000,2024-09-05 07:54:57,7032.0,459.0,2376.0,201.0,7437.0,133.0,2164.0,11437.0,"A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal,..",344.0,36,True,2024-08-15 21:55:14.000,r2.0.0rc1,74.0,nemo-toolkit,,,['pytorch'],230059.0,83808.0,34.0,21.0,https://pypi.org/project/nemo-toolkit,2024-08-15 22:05:43.000,13.0,79974.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +107,carla,carla-simulator/carla,others,,https://github.com/carla-simulator/carla,https://github.com/carla-simulator/carla,MIT,2017-10-24 09:06:23.000,2024-09-04 18:34:41.000000,2024-08-29 12:58:48,6290.0,52.0,3561.0,244.0,1663.0,1079.0,4394.0,11081.0,Open-source simulator for autonomous driving research.,190.0,36,True,2023-11-14 22:51:02.000,0.9.15,26.0,carla,,,,,10274.0,800.0,789.0,https://pypi.org/project/carla,2023-11-14 22:51:02.000,11.0,10274.0,,,,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +108,Datasette,simonw/datasette,others,,https://github.com/simonw/datasette,https://github.com/simonw/datasette,Apache-2.0,2017-10-23 00:39:03.000,2024-09-03 15:37:27.000000,2024-09-03 15:37:26,2650.0,59.0,660.0,99.0,492.0,592.0,1259.0,9236.0,An open source multi-tool for exploring and publishing data.,80.0,36,True,2024-06-21 23:45:38.000,0.64.8,151.0,datasette,conda-forge/datasette,,,67.0,61402.0,1722.0,1313.0,https://pypi.org/project/datasette,2024-08-16 05:13:16.000,409.0,60366.0,https://anaconda.org/conda-forge/datasette,2024-06-24 15:27:37.980,42454.0,1.0,,,,,,3.0,,,,,,,,datasette,,,,,,,,,,, +109,PyOD,yzhao062/pyod,others,,https://github.com/yzhao062/pyod,https://github.com/yzhao062/pyod,BSD-2-Clause,2017-10-03 20:29:04.000,2024-07-23 01:26:10.000000,2024-06-22 03:57:49,1820.0,26.0,1356.0,143.0,248.0,223.0,146.0,8411.0,"A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques.",59.0,36,True,2024-06-22 04:46:20.000,2.0.1,93.0,pyod,conda-forge/pyod,,,,646629.0,4252.0,4140.0,https://pypi.org/project/pyod,2024-06-22 04:42:15.000,112.0,644359.0,https://anaconda.org/conda-forge/pyod,2024-06-22 08:10:13.582,118091.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +110,Autograd,HIPS/autograd,others,,https://github.com/HIPS/autograd,https://github.com/HIPS/autograd,MIT,2014-11-24 15:50:23.000,2024-09-02 17:48:59.000000,2024-09-02 17:48:57,1436.0,16.0,905.0,215.0,234.0,178.0,242.0,6917.0,Efficiently computes derivatives of NumPy code.,59.0,36,True,2024-08-22 19:07:12.000,1.7.0,30.0,autograd,conda-forge/autograd,,,,1828773.0,9593.0,9312.0,https://pypi.org/project/autograd,2024-08-22 19:07:12.000,281.0,1811388.0,https://anaconda.org/conda-forge/autograd,2024-08-26 07:50:41.522,469413.0,1.0,,,,,,3.0,,,,,,,,,,,,,,,,,,, +111,MONAI,Project-MONAI/MONAI,medical-data,,https://github.com/Project-MONAI/MONAI,https://github.com/Project-MONAI/MONAI,Apache-2.0,2019-10-11 16:41:38.000,2024-09-04 10:42:49.000000,2024-09-04 10:42:49,3129.0,82.0,1034.0,90.0,3462.0,348.0,2750.0,5666.0,AI Toolkit for Healthcare Imaging.,203.0,36,True,2024-06-26 07:23:34.000,1.3.2,95.0,monai,conda-forge/monai,,['pytorch'],,166068.0,2846.0,2738.0,https://pypi.org/project/monai,2024-09-02 07:30:00.000,108.0,165198.0,https://anaconda.org/conda-forge/monai,2024-06-26 07:27:45.102,28729.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +112,DeepChem,deepchem/deepchem,others,,https://github.com/deepchem/deepchem,https://github.com/deepchem/deepchem,MIT,2015-09-24 23:20:28.000,2024-08-23 18:44:41.000000,2024-08-23 16:39:43,10527.0,51.0,1650.0,144.0,2415.0,622.0,1237.0,5385.0,"Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology.",247.0,36,True,2024-04-03 16:21:23.000,2.8.0,915.0,deepchem,conda-forge/deepchem,,['tensorflow'],,39616.0,435.0,422.0,https://pypi.org/project/deepchem,2024-08-23 18:44:41.000,13.0,37474.0,https://anaconda.org/conda-forge/deepchem,2024-04-05 16:46:45.105,109279.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +113,opencv-python,opencv/opencv-python,image,,https://github.com/opencv/opencv-python,https://github.com/opencv/opencv-python,MIT,2016-04-08 13:36:40.000,2024-08-11 15:17:42.000000,2024-07-24 14:28:18,965.0,4.0,833.0,91.0,217.0,124.0,682.0,4420.0,"Automated CI toolchain to produce precompiled opencv-python, opencv-python-headless, opencv-contrib-python and opencv-..",49.0,36,True,2024-06-17 17:55:00.000,84,74.0,opencv-python,,,,,17433489.0,445864.0,435571.0,https://pypi.org/project/opencv-python,2024-06-17 18:28:13.000,10293.0,17433489.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +114,Thinc,explosion/thinc,ml-frameworks,,https://github.com/explosion/thinc,https://github.com/explosion/thinc,MIT,2014-10-16 16:34:59.000,2024-09-02 10:35:13.000000,2024-09-02 09:57:22,5337.0,12.0,275.0,78.0,796.0,21.0,125.0,2814.0,"A refreshing functional take on deep learning, compatible with your favorite libraries.",63.0,36,True,2024-09-02 10:35:13.000,9.1.0,238.0,thinc,conda-forge/thinc,,,87.0,9993159.0,52268.0,52135.0,https://pypi.org/project/thinc,2024-09-02 10:35:13.000,133.0,9934671.0,https://anaconda.org/conda-forge/thinc,2024-07-14 15:52:37.957,3041420.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +115,metrics,Lightning-AI/metrics,distributed-ml,,https://github.com/Lightning-AI/torchmetrics,https://github.com/Lightning-AI/torchmetrics,Apache-2.0,2020-12-22 20:02:42.000,2024-09-05 10:41:37.000000,2024-09-04 19:30:23,1903.0,93.0,388.0,30.0,1636.0,82.0,774.0,2069.0,"Torchmetrics - Machine learning metrics for distributed, scalable PyTorch applications.",246.0,36,True,2024-08-03 11:32:06.000,1.4.1,47.0,metrics,conda-forge/torchmetrics,,['pytorch'],5500.0,40932.0,29482.0,29480.0,https://pypi.org/project/metrics,2018-04-28 10:58:56.000,2.0,4212.0,https://anaconda.org/conda-forge/torchmetrics,2024-05-16 05:28:17.806,1536812.0,2.0,,,,,,,,Lightning-AI/torchmetrics,,,,,,,,,,,,,,,,, +116,arviz,arviz-devs/arviz,interpretability,,https://github.com/arviz-devs/arviz,https://github.com/arviz-devs/arviz,Apache-2.0,2015-07-29 11:51:10.000,2024-08-28 20:17:07.000000,2024-08-28 20:17:07,1559.0,13.0,391.0,47.0,1507.0,176.0,684.0,1581.0,Exploratory analysis of Bayesian models with Python.,161.0,36,True,2024-07-19 19:33:56.000,0.19.0,38.0,arviz,conda-forge/arviz,,,144.0,1520808.0,7701.0,7412.0,https://pypi.org/project/arviz,2024-07-19 19:33:56.000,289.0,1478550.0,https://anaconda.org/conda-forge/arviz,2024-07-20 08:30:56.752,2197336.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +117,Nilearn,nilearn/nilearn,medical-data,,https://github.com/nilearn/nilearn,https://github.com/nilearn/nilearn,BSD-3-Clause,2011-01-09 19:02:23.000,2024-09-05 14:00:06.000000,2024-09-05 14:00:06,10348.0,51.0,576.0,70.0,2476.0,281.0,1805.0,1159.0,Machine learning for NeuroImaging in Python.,241.0,36,True,2024-04-09 09:15:50.000,0.10.4,47.0,nilearn,conda-forge/nilearn,,['sklearn'],209.0,58624.0,3694.0,3404.0,https://pypi.org/project/nilearn,2024-04-09 09:09:58.000,290.0,52322.0,https://anaconda.org/conda-forge/nilearn,2024-04-09 13:18:52.622,289683.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +118,Face Recognition,ageitgey/face_recognition,image,,https://github.com/ageitgey/face_recognition,https://github.com/ageitgey/face_recognition,MIT,2017-03-03 21:52:39.000,2024-08-21 06:22:36.000000,2022-06-10 09:12:18,238.0,,13413.0,1565.0,231.0,785.0,587.0,52792.0,The worlds simplest facial recognition api for Python and the command line.,54.0,35,False,2020-02-20 14:26:01.000,1.3.0,23.0,face_recognition,conda-forge/face_recognition,,['pytorch'],1297.0,124215.0,3238.0,3122.0,https://pypi.org/project/face_recognition,2020-02-20 14:26:01.000,116.0,123671.0,https://anaconda.org/conda-forge/face_recognition,2023-06-16 19:21:40.721,25440.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +119,Coqui TTS,coqui-ai/TTS,audio,,https://github.com/coqui-ai/TTS,https://github.com/coqui-ai/TTS,MPL-2.0,2020-05-20 15:45:28.000,2024-08-16 12:07:14.000000,2024-02-10 14:20:58,4668.0,,4001.0,279.0,744.0,71.0,1024.0,33194.0,"- a deep learning toolkit for Text-to-Speech, battle-tested in research and production.",165.0,35,True,2023-12-12 15:27:06.000,0.22.0,98.0,tts,conda-forge/tts,,"['pytorch', 'tensorflow']",2855299.0,167512.0,1691.0,1640.0,https://pypi.org/project/tts,2023-12-12 15:27:06.000,51.0,99065.0,https://anaconda.org/conda-forge/tts,2023-06-16 19:27:41.222,16254.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +120,fairseq,facebookresearch/fairseq,nlp,,https://github.com/facebookresearch/fairseq,https://github.com/facebookresearch/fairseq,MIT,2017-08-29 16:26:12.000,2024-07-26 12:51:31.000000,2024-07-22 08:17:18,2324.0,1.0,6351.0,428.0,1341.0,1271.0,3049.0,30108.0,Facebook AI Research Sequence-to-Sequence Toolkit written in Python.,427.0,35,True,2022-06-27 19:32:58.000,0.12.2,16.0,fairseq,conda-forge/fairseq,,['pytorch'],349.0,184716.0,3597.0,3480.0,https://pypi.org/project/fairseq,2022-06-27 19:32:38.000,117.0,182939.0,https://anaconda.org/conda-forge/fairseq,2024-05-17 03:12:57.351,88665.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +121,fastText,facebookresearch/fastText,nlp,,https://github.com/facebookresearch/fastText,https://github.com/facebookresearch/fastText,MIT,2016-07-16 13:38:42.000,2024-06-12 09:44:40.000000,2024-03-13 15:16:33,391.0,,4709.0,846.0,268.0,556.0,611.0,25829.0,Library for fast text representation and classification.,68.0,35,True,2024-06-12 09:44:40.000,0.9.3,37.0,fasttext,conda-forge/fasttext,,,,1665792.0,6768.0,6528.0,https://pypi.org/project/fasttext,2024-06-12 09:44:40.000,240.0,1663745.0,https://anaconda.org/conda-forge/fasttext,2024-05-19 03:10:51.802,98297.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +122,Recommenders,microsoft/recommenders,recommender-systems,,https://github.com/recommenders-team/recommenders,https://github.com/recommenders-team/recommenders,MIT,2018-09-19 10:06:07.000,2024-08-30 18:31:04.000000,2024-08-27 10:39:25,8997.0,78.0,3021.0,273.0,1283.0,159.0,699.0,18755.0,Best Practices on Recommendation Systems.,135.0,35,True,2024-05-01 18:45:29.000,1.2.0,13.0,recommenders,,,,553.0,31399.0,122.0,118.0,https://pypi.org/project/recommenders,2024-05-01 18:45:29.000,4.0,31392.0,,,,1.0,,,,,,,,recommenders-team/recommenders,,,,,,,,,,,,,,,,, +123,haystack,deepset-ai/haystack,nlp,,https://github.com/deepset-ai/haystack,https://github.com/deepset-ai/haystack,Apache-2.0,2019-11-14 09:05:28.000,2024-09-05 15:21:49.000000,2024-09-04 16:05:56,3625.0,187.0,1819.0,132.0,3961.0,132.0,3376.0,16538.0,"LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models,..",259.0,35,True,2024-09-04 14:04:33.000,2.5.0,100.0,haystack,,,,,5558.0,473.0,468.0,https://pypi.org/project/haystack,2021-12-15 14:01:39.322,5.0,5558.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +124,OCRmyPDF,ocrmypdf/OCRmyPDF,ocr,,https://github.com/ocrmypdf/OCRmyPDF,https://github.com/ocrmypdf/OCRmyPDF,MPL-2.0,2013-12-20 08:26:28.000,2024-09-05 08:46:33.000000,2024-09-05 08:46:26,3867.0,45.0,986.0,135.0,180.0,109.0,1061.0,13520.0,"OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them to be searched.",100.0,35,True,2024-08-31 09:35:44.000,16.5.0,244.0,ocrmypdf,conda-forge/ocrmypdf,,,4884.0,126827.0,998.0,966.0,https://pypi.org/project/ocrmypdf,2024-08-31 09:35:10.000,32.0,124692.0,https://anaconda.org/conda-forge/ocrmypdf,2023-06-16 19:24:58.228,75716.0,1.0,,,,,,,,,,,,,,ocrmypdf,ocrmypdf,,,,,,,,,, +125,Annoy,spotify/annoy,nn-search,,https://github.com/spotify/annoy,https://github.com/spotify/annoy,Apache-2.0,2013-04-01 20:29:40.000,2024-09-05 05:37:11.713000,2024-07-29 00:37:39,894.0,4.0,1142.0,319.0,268.0,56.0,343.0,13065.0,Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk.,89.0,35,True,2023-06-14 16:39:02.504,1.17.3,47.0,annoy,conda-forge/python-annoy,,,,1119506.0,4389.0,4191.0,https://pypi.org/project/annoy,2023-06-14 16:39:02.504,198.0,1109031.0,https://anaconda.org/conda-forge/python-annoy,2024-09-05 05:37:11.713,502805.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +126,glfw,glfw/glfw,image,,https://github.com/glfw/glfw,https://github.com/glfw/glfw,Zlib,2013-04-18 15:24:53.000,2024-08-15 14:02:46.000000,2024-04-12 16:27:53,4816.0,,5131.0,385.0,717.0,643.0,1362.0,12812.0,"A multi-platform library for OpenGL, OpenGL ES, Vulkan, window and input.",199.0,35,False,2024-02-24 10:01:09.000,2.7.0,58.0,glfw,conda-forge/glfw,,,3920432.0,256332.0,1620.0,1430.0,https://pypi.org/project/glfw,2024-02-24 10:01:09.000,190.0,216326.0,https://anaconda.org/conda-forge/glfw,2024-02-24 15:41:47.790,241565.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +127,Pydub,jiaaro/pydub,audio,,https://github.com/jiaaro/pydub,https://github.com/jiaaro/pydub,MIT,2011-05-02 18:42:38.000,2024-07-25 08:47:51.000000,2022-12-08 17:49:19,746.0,,1020.0,133.0,232.0,360.0,274.0,8743.0,Manipulate audio with a simple and easy high level interface.,95.0,35,False,2021-03-10 02:10:41.000,0.25.1,68.0,pydub,conda-forge/pydub,,,,5713922.0,67799.0,66468.0,https://pypi.org/project/pydub,2021-03-10 02:09:53.000,1331.0,5712280.0,https://anaconda.org/conda-forge/pydub,2023-06-16 16:12:25.533,113331.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +128,einops,arogozhnikov/einops,ml-frameworks,,https://github.com/arogozhnikov/einops,https://github.com/arogozhnikov/einops,MIT,2018-09-22 00:45:08.000,2024-08-08 01:22:06.000000,2024-08-08 01:21:29,682.0,5.0,344.0,68.0,113.0,35.0,142.0,8328.0,"Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others).",27.0,35,True,2024-04-28 04:07:49.000,0.8.0,15.0,einops,conda-forge/einops,,,,4890277.0,46031.0,43991.0,https://pypi.org/project/einops,2024-04-28 04:07:49.000,2040.0,4884639.0,https://anaconda.org/conda-forge/einops,2024-04-28 06:22:09.150,264989.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +129,cuDF,rapidsai/cudf,gpu-utilities,,https://github.com/rapidsai/cudf,https://github.com/rapidsai/cudf,Apache-2.0,2017-05-07 03:43:37.000,2024-09-05 15:15:08.000000,2024-09-05 13:52:01,39401.0,516.0,882.0,150.0,10346.0,1036.0,5446.0,8223.0,cuDF - GPU DataFrame Library.,294.0,35,True,2024-08-14 22:39:42.000,24.08.02,53.0,cudf,,,,,2818.0,78.0,56.0,https://pypi.org/project/cudf,2020-06-01 20:07:47.000,22.0,2818.0,,,,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +130,FiftyOne,voxel51/fiftyone,data-viz,,https://github.com/voxel51/fiftyone,https://github.com/voxel51/fiftyone,Apache-2.0,2020-04-22 13:43:28.000,2024-09-05 13:07:33.000000,2024-09-04 16:06:58,21064.0,570.0,535.0,55.0,3260.0,519.0,1049.0,8057.0,"Visualize, create, and debug image and video datasets and model predictions.",132.0,35,True,2024-08-20 15:56:11.000,0.25.0,145.0,fiftyone,,,"['tensorflow', 'pytorch', 'jupyter']",,119206.0,697.0,677.0,https://pypi.org/project/fiftyone,2024-08-20 15:17:07.000,20.0,119206.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +131,BentoML,bentoml/BentoML,model-serialisation,,https://github.com/bentoml/BentoML,https://github.com/bentoml/BentoML,Apache-2.0,2019-04-02 01:39:27.000,2024-09-05 07:13:08.000000,2024-09-05 07:13:08,3234.0,121.0,773.0,78.0,3629.0,167.0,912.0,6952.0,"The easiest way to serve AI apps and models - Build reliable Inference APIs, LLM apps, Multi-model chains, RAG..",207.0,35,True,2024-08-23 11:45:30.000,1.3.3,158.0,bentoml,,,,1294.0,106975.0,2040.0,2014.0,https://pypi.org/project/bentoml,2024-08-23 11:45:30.000,26.0,106951.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +132,H2O-3,h2oai/h2o-3,distributed-ml,,https://github.com/h2oai/h2o-3,https://github.com/h2oai/h2o-3,Apache-2.0,2014-03-03 16:08:07.000,2024-09-05 00:36:37.000000,2024-08-29 22:15:09,32510.0,49.0,1994.0,384.0,6865.0,2832.0,6655.0,6852.0,"H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM)..",268.0,35,True,,,155.0,h2o,,,,,313236.0,67.0,21.0,https://pypi.org/project/h2o,2024-08-29 13:55:23.000,46.0,313236.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +133,imbalanced-learn,scikit-learn-contrib/imbalanced-learn,sklearn-utils,,https://github.com/scikit-learn-contrib/imbalanced-learn,https://github.com/scikit-learn-contrib/imbalanced-learn,MIT,2014-08-16 05:08:26.000,2024-05-28 15:38:50.650000,2024-05-28 14:28:56,865.0,,1275.0,142.0,500.0,44.0,561.0,6800.0,A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning.,84.0,35,True,2024-05-28 15:13:16.000,0.12.3,37.0,imbalanced-learn,conda-forge/imbalanced-learn,,['sklearn'],,11765134.0,31875.0,31445.0,https://pypi.org/project/imbalanced-learn,2024-05-28 15:11:10.000,430.0,11753217.0,https://anaconda.org/conda-forge/imbalanced-learn,2024-05-28 15:38:50.650,607777.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +134,mlpack,mlpack/mlpack,ml-frameworks,,https://github.com/mlpack/mlpack,https://github.com/mlpack/mlpack,BSD-3-Clause,2014-12-17 18:16:59.000,2024-09-04 15:53:54.000000,2024-09-03 13:23:23,30261.0,292.0,1590.0,183.0,2167.0,24.0,1610.0,5006.0,"mlpack: a fast, header-only C++ machine learning library.",321.0,35,True,2024-05-28 22:59:10.000,4.4.0,47.0,mlpack,conda-forge/mlpack,,,,8724.0,4.0,,https://pypi.org/project/mlpack,2024-07-25 00:43:07.000,4.0,4098.0,https://anaconda.org/conda-forge/mlpack,2024-05-29 13:49:41.651,235964.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +135,Ignite,pytorch/ignite,ml-frameworks,,https://github.com/pytorch/ignite,https://github.com/pytorch/ignite,BSD-3-Clause,2017-11-23 17:31:21.000,2024-09-05 09:58:24.000000,2024-09-05 09:42:18,1719.0,17.0,610.0,60.0,1867.0,157.0,1265.0,4509.0,High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.,619.0,35,True,2024-08-13 12:47:02.000,0.5.1,1729.0,pytorch-ignite,pytorch/ignite,,['pytorch'],,170596.0,3256.0,3161.0,https://pypi.org/project/pytorch-ignite,2024-09-05 00:15:01.000,95.0,167988.0,https://anaconda.org/pytorch/ignite,2024-08-13 12:46:51.642,195646.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +136,Core ML Tools,apple/coremltools,model-serialisation,,https://github.com/apple/coremltools,https://github.com/apple/coremltools,BSD-3-Clause,2017-06-30 07:39:02.000,2024-08-31 01:21:52.000000,2024-08-31 01:21:52,1174.0,22.0,624.0,122.0,918.0,345.0,1088.0,4316.0,"Core ML tools contain supporting tools for Core ML model conversion, editing, and validation.",176.0,35,True,2024-04-22 23:27:42.000,7.2,49.0,coremltools,conda-forge/coremltools,,,10949.0,905019.0,4157.0,4081.0,https://pypi.org/project/coremltools,2024-08-16 01:15:18.000,76.0,903440.0,https://anaconda.org/conda-forge/coremltools,2023-06-16 19:23:14.592,68106.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +137,tensorflow-probability,tensorflow/probability,probabilistics,,https://github.com/tensorflow/probability,https://github.com/tensorflow/probability,Apache-2.0,2017-10-23 23:50:54.000,2024-08-23 17:55:31.000000,2024-08-23 17:55:30,12168.0,28.0,1091.0,163.0,465.0,682.0,754.0,4233.0,Probabilistic reasoning and statistical analysis in TensorFlow.,496.0,35,True,2024-03-12 19:43:46.000,0.24.0,52.0,tensorflow-probability,conda-forge/tensorflow-probability,,['tensorflow'],,1534347.0,607.0,1.0,https://pypi.org/project/tensorflow-probability,2024-03-12 19:43:39.000,606.0,1531057.0,https://anaconda.org/conda-forge/tensorflow-probability,2024-05-27 12:58:13.692,141506.0,1.0,,,,,,-3.0,,,,,,,,,,,,,,,,,,, +138,TorchServe,pytorch/serve,model-serialisation,,https://github.com/pytorch/serve,https://github.com/pytorch/serve,Apache-2.0,2019-10-03 03:17:43.000,2024-09-01 14:09:34.000000,2024-08-24 00:17:46,3856.0,72.0,835.0,59.0,1675.0,397.0,1262.0,4166.0,"Serve, optimize and scale PyTorch models in production.",211.0,35,True,2024-07-18 18:56:54.000,0.11.1,25.0,torchserve,pytorch/torchserve,,['pytorch'],6189.0,79734.0,733.0,711.0,https://pypi.org/project/torchserve,2024-07-18 17:19:00.000,22.0,52373.0,https://anaconda.org/pytorch/torchserve,2024-07-18 17:18:59.921,252285.0,2.0,pytorch/torchserve,https://hub.docker.com/r/pytorch/torchserve,2024-07-18 18:10:34.554819,28.0,1326644.0,,,,,,,,,,,,,,,,,,,, +139,plotnine,has2k1/plotnine,data-viz,,https://github.com/has2k1/plotnine,https://github.com/has2k1/plotnine,MIT,2017-04-24 19:00:44.000,2024-09-04 22:59:49.000000,2024-08-01 18:14:49,2387.0,17.0,210.0,63.0,144.0,90.0,584.0,3963.0,A Grammar of Graphics for Python.,111.0,35,True,2024-05-10 08:15:43.000,0.13.6,27.0,plotnine,conda-forge/plotnine,,,,2764406.0,8859.0,8554.0,https://pypi.org/project/plotnine,2024-05-09 20:44:49.000,305.0,2756670.0,https://anaconda.org/conda-forge/plotnine,2024-05-10 08:18:51.149,394578.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +140,spark-nlp,JohnSnowLabs/spark-nlp,nlp,,https://github.com/JohnSnowLabs/spark-nlp,https://github.com/JohnSnowLabs/spark-nlp,Apache-2.0,2017-09-24 19:36:44.000,2024-09-05 15:31:54.000000,2024-09-01 18:18:11,8568.0,38.0,707.0,98.0,13304.0,43.0,851.0,3801.0,State of the Art Natural Language Processing.,113.0,35,True,2024-08-29 12:23:33.000,5.4.2,146.0,spark-nlp,,,['spark'],,4029205.0,532.0,495.0,https://pypi.org/project/spark-nlp,2024-08-28 16:05:44.000,37.0,4029205.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +141,VisPy,vispy/vispy,data-viz,,https://github.com/vispy/vispy,https://github.com/vispy/vispy,BSD-3-Clause,2013-03-21 18:43:22.000,2024-09-04 12:47:04.775000,2024-08-27 09:55:50,7396.0,11.0,618.0,115.0,1181.0,353.0,1115.0,3289.0,High-performance interactive 2D/3D data visualization library.,198.0,35,True,2024-06-17 12:39:47.000,0.14.3,39.0,vispy,conda-forge/vispy,,['jupyter'],,196048.0,1830.0,1657.0,https://pypi.org/project/vispy,2024-06-17 12:32:22.000,170.0,183834.0,https://anaconda.org/conda-forge/vispy,2024-09-04 12:47:04.775,585915.0,2.0,,,,,,,,,vispy,https://www.npmjs.com/package/vispy,2020-03-15 14:39:41.516,3.0,8.0,,,,,,,,,,,, +142,torchaudio,pytorch/audio,audio,,https://github.com/pytorch/audio,https://github.com/pytorch/audio,BSD-2-Clause,2017-05-05 00:38:05.000,2024-09-05 13:28:32.000000,2024-08-27 15:26:44,2313.0,4.0,641.0,73.0,2892.0,249.0,726.0,2476.0,"Data manipulation and transformation for audio signal processing, powered by PyTorch.",227.0,35,True,2024-09-04 20:06:34.000,2.4.1,37.0,torchaudio,,,['pytorch'],,6218890.0,1263.0,,https://pypi.org/project/torchaudio,2024-09-04 19:15:37.000,1263.0,6218890.0,,,,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +143,ArcGIS API,Esri/arcgis-python-api,geospatial-data,,https://github.com/Esri/arcgis-python-api,https://github.com/Esri/arcgis-python-api,Apache-2.0,2016-03-16 01:09:14.000,2024-09-05 06:40:46.000000,2024-09-04 22:40:43,4378.0,75.0,1074.0,152.0,1258.0,71.0,681.0,1861.0,Documentation and samples for ArcGIS API for Python.,91.0,35,True,2024-07-09 18:02:58.000,2.3.1,49.0,arcgis,,,,12067.0,71658.0,858.0,818.0,https://pypi.org/project/arcgis,2024-07-09 17:29:35.000,40.0,71533.0,,,,2.0,esridocker/arcgis-api-python-notebook,https://hub.docker.com/r/esridocker/arcgis-api-python-notebook,,,,,,,,,,,,,,,,,,,,,,, +144,TensorFlow Text,tensorflow/text,nlp,,https://github.com/tensorflow/text,https://github.com/tensorflow/text,Apache-2.0,2019-05-29 22:10:03.000,2024-09-05 06:54:28.000000,2024-09-05 06:54:23,889.0,10.0,335.0,42.0,1050.0,185.0,169.0,1220.0,Making text a first-class citizen in TensorFlow.,116.0,35,True,2024-07-15 22:42:38.000,2.17.0,71.0,tensorflow-text,,,['tensorflow'],,6408586.0,7496.0,7286.0,https://pypi.org/project/tensorflow-text,2024-07-15 22:26:08.000,210.0,6408586.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +145,scikit-learn-intelex,intel/scikit-learn-intelex,sklearn-utils,,https://github.com/intel/scikit-learn-intelex,https://github.com/intel/scikit-learn-intelex,Apache-2.0,2018-08-07 06:45:41.000,2024-09-05 15:50:28.000000,2024-09-05 15:50:28,1809.0,121.0,171.0,30.0,1746.0,90.0,189.0,1206.0,Intel(R) Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application.,81.0,35,True,2024-08-13 15:40:01.000,2024.6.0,29.0,scikit-learn-intelex,conda-forge/scikit-learn-intelex,,['sklearn'],,120809.0,11971.0,11922.0,https://pypi.org/project/scikit-learn-intelex,2024-08-07 15:13:02.000,49.0,112778.0,https://anaconda.org/conda-forge/scikit-learn-intelex,2024-08-20 09:58:15.356,329271.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +146,pyproj,pyproj4/pyproj,geospatial-data,,https://github.com/pyproj4/pyproj,https://github.com/pyproj4/pyproj,MIT,2014-12-29 21:38:25.000,2024-09-04 08:35:41.569000,2024-08-30 12:40:09,1568.0,18.0,211.0,33.0,702.0,32.0,585.0,1039.0,Python interface to PROJ (cartographic projections and coordinate transformations library).,65.0,35,True,2023-09-21 02:07:12.000,3.6.1,61.0,pyproj,conda-forge/pyproj,,,,8958110.0,34779.0,33112.0,https://pypi.org/project/pyproj,2023-09-21 02:07:12.000,1667.0,8789322.0,https://anaconda.org/conda-forge/pyproj,2024-09-04 08:35:41.569,8439424.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +147,ColossalAI,hpcaitech/colossalai,distributed-ml,,https://github.com/hpcaitech/ColossalAI,https://github.com/hpcaitech/ColossalAI,Apache-2.0,2021-10-28 16:19:44.000,2024-09-04 03:52:24.000000,2024-09-03 08:37:16,3673.0,277.0,4296.0,384.0,4156.0,415.0,1257.0,38571.0,"Making large AI models cheaper, faster and more accessible.",193.0,34,True,2024-07-31 02:06:47.000,0.4.2,42.0,,,,,,,409.0,409.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +148,DeepSpeech,mozilla/DeepSpeech,audio,,https://github.com/mozilla/DeepSpeech,https://github.com/mozilla/DeepSpeech,MPL-2.0,2016-06-02 15:04:53.000,2024-09-03 21:17:43.000000,2021-11-17 17:52:52,3466.0,,3938.0,670.0,1678.0,149.0,1987.0,25019.0,"DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices..",163.0,34,False,2020-12-10 17:22:09.000,0.9.3,100.0,deepspeech,conda-forge/deepspeech,,['tensorflow'],1176068.0,22810.0,470.0,446.0,https://pypi.org/project/deepspeech,2020-12-19 10:05:12.000,24.0,6396.0,https://anaconda.org/conda-forge/deepspeech,2023-06-16 19:27:01.157,3076.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +149,EasyOCR,JaidedAI/EasyOCR,ocr,,https://github.com/JaidedAI/EasyOCR,https://github.com/JaidedAI/EasyOCR,Apache-2.0,2020-03-14 11:46:39.000,2024-08-14 05:22:49.000000,2024-07-25 01:00:20,617.0,2.0,3090.0,314.0,258.0,416.0,594.0,23600.0,"Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic,..",129.0,34,True,2023-09-04 11:55:27.000,1.7.1,32.0,easyocr,,,,14060947.0,726898.0,8190.0,7985.0,https://pypi.org/project/easyocr,2023-09-04 11:55:27.000,205.0,451194.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +150,ChatterBot,gunthercox/ChatterBot,nlp,,https://github.com/gunthercox/ChatterBot,https://github.com/gunthercox/ChatterBot,BSD-3-Clause,2014-09-28 14:49:00.000,2024-04-24 19:01:00.000000,2021-06-01 10:43:00,1848.0,,4403.0,544.0,716.0,402.0,1282.0,14014.0,"ChatterBot is a machine learning, conversational dialog engine for creating chat bots.",103.0,34,False,2020-08-22 18:42:43.000,1.0.8,86.0,chatterbot,,,,,29222.0,5921.0,5903.0,https://pypi.org/project/chatterbot,2020-08-22 18:40:36.000,18.0,29222.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +151,NNI,microsoft/nni,hyperopt,,https://github.com/microsoft/nni,https://github.com/microsoft/nni,MIT,2018-06-01 05:51:44.000,2024-07-03 10:55:10.000000,2023-10-26 05:31:53,3012.0,,1807.0,284.0,3507.0,415.0,1684.0,13968.0,"An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural..",192.0,34,True,2023-09-14 12:12:06.000,3.0,55.0,nni,,,,,162010.0,760.0,713.0,https://pypi.org/project/nni,2023-09-14 12:22:00.000,47.0,162010.0,,,,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +152,Pyro,pyro-ppl/pyro,probabilistics,,https://github.com/pyro-ppl/pyro,https://github.com/pyro-ppl/pyro,Apache-2.0,2017-06-16 05:03:47.000,2024-08-27 17:00:49.000000,2024-08-04 23:25:47,2485.0,11.0,983.0,201.0,2318.0,258.0,845.0,8490.0,Deep universal probabilistic programming with Python and PyTorch.,155.0,34,True,2024-06-02 00:37:37.000,1.9.1,36.0,pyro-ppl,conda-forge/pyro-ppl,,['pytorch'],,328251.0,186.0,,https://pypi.org/project/pyro-ppl,2024-06-02 00:37:37.000,186.0,323718.0,https://anaconda.org/conda-forge/pyro-ppl,2024-06-03 00:37:06.159,190387.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +153,Vowpal Wabbit,VowpalWabbit/vowpal_wabbit,ml-frameworks,,https://github.com/VowpalWabbit/vowpal_wabbit,https://github.com/VowpalWabbit/vowpal_wabbit,BSD-3-Clause,2009-07-31 19:36:58.000,2024-09-05 13:46:25.848000,2024-08-01 18:55:53,10421.0,6.0,1926.0,351.0,3428.0,130.0,1138.0,8456.0,Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as..,338.0,34,True,2024-08-08 17:57:21.000,9.10.0,30.0,vowpalwabbit,conda-forge/vowpalwabbit,,,,56411.0,40.0,,https://pypi.org/project/vowpalwabbit,2024-08-08 17:57:21.000,40.0,51889.0,https://anaconda.org/conda-forge/vowpalwabbit,2024-09-05 13:46:25.848,212545.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +154,Metaflow,Netflix/metaflow,ml-experiments,,https://github.com/Netflix/metaflow,https://github.com/Netflix/metaflow,Apache-2.0,2019-09-17 17:48:25.000,2024-09-05 08:14:49.000000,2024-09-05 06:07:38,1027.0,82.0,751.0,284.0,1362.0,317.0,410.0,8008.0,"Build and manage real-life ML, AI, and data science projects with ease!.",93.0,34,True,2024-09-04 23:07:10.000,2.12.19,143.0,metaflow,conda-forge/metaflow,,,,716505.0,763.0,718.0,https://pypi.org/project/metaflow,2024-09-04 23:07:10.000,45.0,712366.0,https://anaconda.org/conda-forge/metaflow,2024-08-23 00:56:47.364,206985.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +155,UMAP,lmcinnes/umap,data-viz,,https://github.com/lmcinnes/umap,https://github.com/lmcinnes/umap,BSD-3-Clause,2017-07-02 01:11:17.000,2024-08-18 00:48:19.000000,2024-08-18 00:48:18,1815.0,22.0,796.0,127.0,285.0,473.0,337.0,7338.0,Uniform Manifold Approximation and Projection.,134.0,34,True,2024-04-03 16:53:16.000,0.5.6,40.0,umap-learn,conda-forge/umap-learn,,,,1424940.0,959.0,1.0,https://pypi.org/project/umap-learn,2024-04-03 16:53:16.000,958.0,1374141.0,https://anaconda.org/conda-forge/umap-learn,2024-08-14 17:32:09.484,2590751.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +156,PML,KevinMusgrave/pytorch-metric-learning,pytorch-utils,,https://github.com/KevinMusgrave/pytorch-metric-learning,https://github.com/KevinMusgrave/pytorch-metric-learning,MIT,2019-10-23 17:20:35.000,2024-07-25 01:34:14.000000,2024-07-24 12:37:14,1228.0,13.0,657.0,63.0,136.0,61.0,444.0,5937.0,"The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.",42.0,34,True,2024-07-25 01:34:14.000,2.6.1,212.0,pytorch-metric-learning,metric-learning/pytorch-metric-learning,,['pytorch'],,839541.0,1846.0,1796.0,https://pypi.org/project/pytorch-metric-learning,2024-07-25 01:34:14.000,50.0,839331.0,https://anaconda.org/metric-learning/pytorch-metric-learning,2023-06-16 19:17:36.446,11778.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +157,ClearML,allegroai/clearml,ml-experiments,,https://github.com/allegroai/clearml,https://github.com/allegroai/clearml,Apache-2.0,2019-06-10 08:18:32.000,2024-09-04 21:13:26.000000,2024-09-04 21:13:26,2420.0,51.0,642.0,96.0,268.0,477.0,561.0,5552.0,"ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline,..",100.0,34,True,2024-08-27 19:48:22.000,1.16.4,169.0,clearml,,,,2762.0,314803.0,1299.0,1264.0,https://pypi.org/project/clearml,2024-08-27 19:47:15.000,35.0,314280.0,,,,2.0,allegroai/trains,https://hub.docker.com/r/allegroai/trains,2020-10-05 10:16:46.865671,,30243.0,,,,,,,,,,,,,,,,,,,, +158,ART,Trusted-AI/adversarial-robustness-toolbox,adversarial,,https://github.com/Trusted-AI/adversarial-robustness-toolbox,https://github.com/Trusted-AI/adversarial-robustness-toolbox,MIT,2018-03-15 14:40:43.000,2024-09-05 07:21:42.000000,2024-08-29 20:55:31,12385.0,68.0,1144.0,101.0,1375.0,154.0,757.0,4741.0,"Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction,..",138.0,34,True,2024-07-03 17:29:44.000,1.18.1,60.0,adversarial-robustness-toolbox,conda-forge/adversarial-robustness-toolbox,,,,27508.0,597.0,577.0,https://pypi.org/project/adversarial-robustness-toolbox,2024-07-03 17:21:24.000,20.0,26566.0,https://anaconda.org/conda-forge/adversarial-robustness-toolbox,2024-07-03 22:45:10.329,47101.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +159,StatsForecast,Nixtla/statsforecast,time-series-data,,https://github.com/Nixtla/statsforecast,https://github.com/Nixtla/statsforecast,Apache-2.0,2021-11-24 02:19:14.000,2024-09-03 22:59:59.000000,2024-09-03 22:57:39,1307.0,16.0,266.0,38.0,461.0,99.0,233.0,3841.0,Lightning fast forecasting with statistical and econometric models.,43.0,34,True,2024-07-17 21:37:08.000,1.7.6,34.0,statsforecast,conda-forge/statsforecast,,,,770487.0,1147.0,1090.0,https://pypi.org/project/statsforecast,2024-07-17 21:37:08.000,57.0,767508.0,https://anaconda.org/conda-forge/statsforecast,2024-07-18 06:07:43.894,89390.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +160,rubrix,recognai/rubrix,nlp,,https://github.com/argilla-io/argilla,https://github.com/argilla-io/argilla,Apache-2.0,2021-04-28 14:37:42.000,2024-09-05 15:17:56.000000,2024-09-05 15:14:52,3353.0,289.0,351.0,29.0,3177.0,140.0,1970.0,3779.0,Argilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets.,95.0,34,True,2024-09-05 15:11:08.000,2.1.0,100.0,rubrix,conda-forge/rubrix,,,,1752.0,2686.0,2686.0,https://pypi.org/project/rubrix,2022-10-24 18:22:00.951,,687.0,https://anaconda.org/conda-forge/rubrix,2023-06-16 19:28:09.653,35166.0,2.0,,,,,,,,argilla-io/argilla,,,,,,,,,,,,,,,,, +161,STUMPY,TDAmeritrade/stumpy,time-series-data,,https://github.com/TDAmeritrade/stumpy,https://github.com/TDAmeritrade/stumpy,BSD-3-Clause,2019-05-03 19:23:44.000,2024-08-16 14:16:04.000000,2024-08-16 14:16:04,1353.0,45.0,316.0,60.0,244.0,66.0,444.0,3604.0,STUMPY is a powerful and scalable Python library for modern time series analysis.,41.0,34,True,2024-07-09 04:43:23.000,1.13.0,29.0,stumpy,conda-forge/stumpy,,,,351045.0,895.0,865.0,https://pypi.org/project/stumpy,2024-07-09 04:21:56.000,30.0,331111.0,https://anaconda.org/conda-forge/stumpy,2024-07-09 04:54:55.949,1016641.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +162,BoTorch,pytorch/botorch,hyperopt,,https://github.com/pytorch/botorch,https://github.com/pytorch/botorch,MIT,2018-07-30 23:59:57.000,2024-09-05 12:54:08.000000,2024-09-05 02:02:04,1972.0,86.0,388.0,52.0,1719.0,65.0,457.0,3052.0,Bayesian optimization in PyTorch.,125.0,34,True,2024-07-22 21:09:12.000,0.11.3,46.0,botorch,conda-forge/botorch,,['pytorch'],,184626.0,1214.0,1131.0,https://pypi.org/project/botorch,2024-07-22 21:09:12.000,83.0,182144.0,https://anaconda.org/conda-forge/botorch,2024-07-23 15:58:22.505,121640.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +163,optimum,huggingface/optimum,gpu-utilities,,https://github.com/huggingface/optimum,https://github.com/huggingface/optimum,Apache-2.0,2021-07-20 12:36:40.000,2024-09-05 14:15:02.000000,2024-09-05 14:01:33,1087.0,45.0,423.0,56.0,1268.0,408.0,413.0,2438.0,Accelerate training and inference of Transformers and Diffusers with easy to use hardware optimization tools.,118.0,34,True,2024-08-16 13:25:20.000,1.21.4,69.0,optimum,conda-forge/optimum,,,,891070.0,3439.0,3284.0,https://pypi.org/project/optimum,2024-08-16 13:22:26.000,155.0,890309.0,https://anaconda.org/conda-forge/optimum,2024-05-29 19:43:21.254,22086.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +164,Ax,facebook/Ax,hyperopt,,https://github.com/facebook/Ax,https://github.com/facebook/Ax,MIT,2019-02-09 15:23:44.000,2024-09-05 07:29:00.000000,2024-09-05 02:02:04,3244.0,176.0,301.0,69.0,1986.0,54.0,712.0,2340.0,Adaptive Experimentation Platform.,174.0,34,True,2024-07-23 19:26:30.000,0.4.1,42.0,ax-platform,conda-forge/ax-platform,,['pytorch'],,94257.0,835.0,785.0,https://pypi.org/project/ax-platform,2024-07-23 19:26:30.000,50.0,93593.0,https://anaconda.org/conda-forge/ax-platform,2024-07-24 14:52:58.388,25927.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +165,PennyLane,PennyLaneAI/PennyLane,others,,https://github.com/PennyLaneAI/pennylane,https://github.com/PennyLaneAI/pennylane,Apache-2.0,2018-04-17 16:45:42.000,2024-09-05 15:27:40.000000,2024-09-05 14:24:45,4478.0,245.0,583.0,46.0,4905.0,310.0,1060.0,2257.0,"PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry...",184.0,34,True,2024-09-03 23:49:00.000,0.38.0,59.0,pennylane,conda-forge/pennylane,,,88.0,69711.0,107.0,,https://pypi.org/project/pennylane,2024-09-03 23:49:00.000,107.0,65924.0,https://anaconda.org/conda-forge/pennylane,2024-07-09 13:59:12.283,128747.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +166,snakemake,snakemake/snakemake,ml-experiments,,https://github.com/snakemake/snakemake,https://github.com/snakemake/snakemake,MIT,2015-10-17 15:43:54.867,2024-09-05 08:27:29.000000,2024-09-05 08:26:24,5272.0,81.0,541.0,19.0,1364.0,1109.0,682.0,2226.0,"This is the development home of the workflow management system Snakemake. For general information, see.",342.0,34,True,2024-09-05 08:23:46.000,8.19.3,352.0,snakemake,bioconda/snakemake,,,,108825.0,2290.0,2063.0,https://pypi.org/project/snakemake,2024-09-05 08:23:46.000,227.0,98062.0,https://anaconda.org/bioconda/snakemake,2024-08-21 12:22:56.372,1151746.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +167,TFX,tensorflow/tfx,tensorflow-utils,,https://github.com/tensorflow/tfx,https://github.com/tensorflow/tfx,Apache-2.0,2019-02-04 17:14:36.000,2024-09-04 19:31:25.000000,2024-09-04 19:30:08,5816.0,166.0,701.0,87.0,5995.0,245.0,857.0,2104.0,TFX is an end-to-end platform for deploying production ML pipelines.,189.0,34,True,2024-05-13 23:20:24.000,1.15.1,98.0,tfx,,,['tensorflow'],,39139.0,1566.0,1549.0,https://pypi.org/project/tfx,2024-05-13 23:20:24.000,17.0,39139.0,,,,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +168,Graphviz,xflr6/graphviz,data-viz,,https://github.com/xflr6/graphviz,https://github.com/xflr6/graphviz,MIT,2014-01-12 17:49:29.000,2024-05-13 18:30:44.000000,2024-05-13 18:28:50,1241.0,,208.0,32.0,47.0,13.0,166.0,1619.0,Simple Python interface for Graphviz.,23.0,34,True,2024-03-21 07:50:43.000,0.20.3,58.0,graphviz,anaconda/python-graphviz,,,,13497770.0,74628.0,72074.0,https://pypi.org/project/graphviz,2024-03-21 07:50:43.000,2554.0,13497224.0,https://anaconda.org/anaconda/python-graphviz,2024-04-08 21:04:04.101,48608.0,2.0,,,,,,-3.0,,,,,,,,,,,,,,,,,,, +169,cartopy,SciTools/cartopy,data-viz,,https://github.com/SciTools/cartopy,https://github.com/SciTools/cartopy,BSD-3-Clause,2012-08-03 07:43:59.000,2024-09-03 20:55:53.000000,2024-09-03 20:55:53,3070.0,38.0,359.0,54.0,1185.0,312.0,968.0,1406.0,Cartopy - a cartographic python library with matplotlib support.,127.0,34,True,2024-04-10 17:52:06.000,0.23.0,30.0,cartopy,conda-forge/cartopy,,,,380924.0,6214.0,5537.0,https://pypi.org/project/cartopy,2024-04-10 17:52:06.000,677.0,304340.0,https://anaconda.org/conda-forge/cartopy,2024-05-16 22:28:29.744,3982400.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +170,Wand,emcconville/wand,image,,https://github.com/emcconville/wand,https://github.com/emcconville/wand,MIT,2011-09-30 21:36:38.000,2024-07-08 02:24:05.000000,2024-02-11 16:39:29,1856.0,,200.0,32.0,212.0,26.0,401.0,1389.0,The ctypes-based simple ImageMagick binding for Python.,104.0,34,True,2023-11-04 01:41:17.000,0.6.13,56.0,wand,conda-forge/wand,,,49335.0,753695.0,19785.0,19533.0,https://pypi.org/project/wand,2023-11-03 23:18:50.000,252.0,751850.0,https://anaconda.org/conda-forge/wand,2023-06-16 16:16:46.218,69638.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +171,igraph,igraph/python-igraph,graph,,https://github.com/igraph/python-igraph,https://github.com/igraph/python-igraph,GPL-2.0,2015-01-08 23:55:16.000,2024-09-04 13:45:48.000000,2024-09-04 13:45:43,2902.0,64.0,247.0,35.0,224.0,48.0,510.0,1283.0,Python interface for igraph.,75.0,34,False,2024-07-08 23:38:30.000,0.11.6,42.0,python-igraph,conda-forge/igraph,,,563830.0,204812.0,4484.0,4097.0,https://pypi.org/project/python-igraph,2024-07-08 23:38:30.000,387.0,186692.0,https://anaconda.org/conda-forge/igraph,2024-06-28 12:12:37.634,590874.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +172,NiBabel,nipy/nibabel,medical-data,,https://github.com/nipy/nibabel,https://github.com/nipy/nibabel,MIT,2010-07-22 16:28:30.000,2024-08-13 00:14:45.000000,2024-07-26 13:09:43,5902.0,40.0,257.0,37.0,823.0,134.0,405.0,645.0,Python package to access a cacophony of neuro-imaging file formats.,104.0,34,True,2024-02-27 04:17:30.000,5.2.1,42.0,nibabel,conda-forge/nibabel,,,,621704.0,22281.0,21142.0,https://pypi.org/project/nibabel,2024-02-27 04:13:17.000,1139.0,606753.0,https://anaconda.org/conda-forge/nibabel,2024-02-27 14:41:50.570,762513.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +173,detectron2,facebookresearch/detectron2,image,,https://github.com/facebookresearch/detectron2,https://github.com/facebookresearch/detectron2,Apache-2.0,2019-09-05 21:30:20.000,2024-08-26 11:04:11.128000,2024-08-22 17:00:16,1529.0,6.0,7384.0,386.0,681.0,519.0,3065.0,29902.0,"Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.",272.0,33,True,2021-11-15 22:08:26.000,0.6,10.0,detectron2,conda-forge/detectron2,,['pytorch'],,7917.0,1994.0,1981.0,https://pypi.org/project/detectron2,2020-02-06 00:35:57.000,13.0,,https://anaconda.org/conda-forge/detectron2,2024-08-26 11:04:11.128,395884.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +174,MindsDB,mindsdb/mindsdb,ml-frameworks,,https://github.com/mindsdb/mindsdb,https://github.com/mindsdb/mindsdb,libpng-2.0,2018-08-02 17:56:45.000,2024-09-05 14:02:00.000000,2024-09-04 14:43:15,18617.0,231.0,4788.0,393.0,5311.0,170.0,3785.0,26165.0,The platform for building AI from enterprise data.,837.0,33,False,2024-09-03 13:15:40.000,24.9.1.0,482.0,mindsdb,,,['pytorch'],,10617.0,,,https://pypi.org/project/mindsdb,2024-09-03 13:16:52.000,,10617.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +175,tinygrad,geohot/tinygrad,pytorch-utils,,https://github.com/tinygrad/tinygrad,https://github.com/tinygrad/tinygrad,MIT,2020-10-18 16:23:12.000,2024-09-05 14:18:34.000000,2024-09-05 13:06:25,5802.0,1163.0,2821.0,273.0,5581.0,103.0,603.0,26062.0,You like pytorch? You like micrograd? You love tinygrad!.,333.0,33,True,2024-08-13 23:19:48.000,0.9.2,8.0,,,,['pytorch'],,,93.0,93.0,,,,,,,,1.0,,,,,,,,tinygrad/tinygrad,,,,,,,,,,,,,,,,, +176,qdrant,qdrant/qdrant,nlp,,https://github.com/qdrant/qdrant,https://github.com/qdrant/qdrant,Apache-2.0,2020-05-30 21:37:01.000,2024-09-05 13:56:35.000000,2024-08-29 14:14:49,3228.0,433.0,1323.0,120.0,3547.0,280.0,974.0,19701.0,"Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud..",116.0,33,True,2024-08-29 16:32:22.000,1.11.3,81.0,,,,,135866.0,3313.0,114.0,114.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +177,Prophet,facebook/prophet,time-series-data,,https://github.com/facebook/prophet,https://github.com/facebook/prophet,MIT,2016-11-16 01:50:08.000,2024-09-03 22:09:45.000000,2024-05-18 14:08:15,800.0,,4501.0,452.0,459.0,420.0,1729.0,18256.0,Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear..,179.0,33,True,2023-10-10 12:57:04.000,1.1.5,16.0,fbprophet,conda-forge/prophet,,,2741.0,342047.0,112.0,21.0,https://pypi.org/project/fbprophet,2020-09-05 16:12:50.000,91.0,311641.0,https://anaconda.org/conda-forge/prophet,2023-10-20 01:36:39.935,1245442.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +178,Lime,marcotcr/lime,interpretability,,https://github.com/marcotcr/lime,https://github.com/marcotcr/lime,BSD-2-Clause,2016-03-15 22:18:10.000,2024-07-25 20:32:21.000000,2021-07-29 23:17:25,531.0,,1795.0,263.0,117.0,120.0,535.0,11496.0,Lime: Explaining the predictions of any machine learning classifier.,62.0,33,False,2020-04-03 22:05:03.000,0.2.0.0,39.0,lime,conda-forge/lime,,,,399317.0,6384.0,6186.0,https://pypi.org/project/lime,2020-06-26 21:38:15.000,198.0,396885.0,https://anaconda.org/conda-forge/lime,2023-06-16 13:18:57.655,226215.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +179,Ludwig,ludwig-ai/ludwig,ml-frameworks,,https://github.com/ludwig-ai/ludwig,https://github.com/ludwig-ai/ludwig,Apache-2.0,2018-12-27 23:58:12.000,2024-08-21 07:05:41.000000,2024-08-21 07:05:41,3857.0,4.0,1185.0,193.0,2863.0,361.0,766.0,11078.0,"Low-code framework for building custom LLMs, neural networks, and other AI models.",157.0,33,True,2024-07-30 00:29:49.000,0.10.4,56.0,ludwig,,,['tensorflow'],,2837.0,276.0,270.0,https://pypi.org/project/ludwig,2024-07-30 00:29:49.000,6.0,2837.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +180,wordcloud,amueller/word_cloud,data-viz,,https://github.com/amueller/word_cloud,https://github.com/amueller/word_cloud,MIT,2012-11-04 22:57:59.000,2024-09-03 22:35:30.000000,2023-12-09 05:39:53,576.0,,2311.0,217.0,247.0,125.0,417.0,10069.0,A little word cloud generator in Python.,72.0,33,True,2023-12-09 14:04:35.000,1.9.3,20.0,wordcloud,conda-forge/wordcloud,,,,1426760.0,545.0,21.0,https://pypi.org/project/wordcloud,2023-12-09 14:04:35.000,524.0,1416171.0,https://anaconda.org/conda-forge/wordcloud,2024-03-19 22:44:23.623,529489.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +181,PyTorch3D,facebookresearch/pytorch3d,image,,https://github.com/facebookresearch/pytorch3d,https://github.com/facebookresearch/pytorch3d,,2019-10-25 02:23:45.000,2024-08-15 23:22:23.000000,2024-08-15 23:18:22,1171.0,16.0,1258.0,148.0,174.0,265.0,1327.0,8636.0,PyTorch3D is FAIRs library of reusable components for deep learning with 3D data.,148.0,33,False,2024-06-27 11:32:25.000,0.7.7,18.0,pytorch3d,pytorch3d/pytorch3d,,['pytorch'],,13898.0,956.0,942.0,https://pypi.org/project/pytorch3d,2022-04-28 15:53:26.000,14.0,9749.0,https://anaconda.org/pytorch3d/pytorch3d,2024-06-27 11:25:52.604,240650.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +182,SpeechRecognition,Uberi/speech_recognition,audio,,https://github.com/Uberi/speech_recognition,https://github.com/Uberi/speech_recognition,BSD-3-Clause,2014-04-23 04:53:54.000,2024-08-13 19:06:58.000000,2024-08-13 19:06:55,544.0,1.0,2389.0,281.0,159.0,325.0,318.0,8293.0,"Speech recognition module for Python, supporting several engines and APIs, online and offline.",51.0,33,True,2024-05-05 04:42:09.000,3.10.4,59.0,SpeechRecognition,conda-forge/speechrecognition,,,,1056761.0,569.0,21.0,https://pypi.org/project/SpeechRecognition,2024-05-05 04:36:10.000,548.0,1052690.0,https://anaconda.org/conda-forge/speechrecognition,2024-05-06 02:00:59.322,199491.0,2.0,,,,,,-3.0,,,,,,,,,,,,,,,,,,, +183,Perspective,finos/perspective,data-viz,,https://github.com/finos/perspective,https://github.com/finos/perspective,Apache-2.0,2017-11-02 16:27:54.000,2024-09-04 16:24:24.000000,2024-09-03 05:23:45,6065.0,70.0,1132.0,121.0,1696.0,98.0,690.0,8262.0,"A data visualization and analytics component, especially well-suited for large and/or streaming datasets.",94.0,33,True,2024-09-03 06:53:38.000,3.0.3,130.0,perspective-python,conda-forge/perspective,,['jupyter'],3812.0,33451.0,169.0,139.0,https://pypi.org/project/perspective-python,2024-09-03 06:52:27.000,24.0,8090.0,https://anaconda.org/conda-forge/perspective,2024-08-24 00:07:23.633,1083760.0,2.0,,,,,,,,,@finos/perspective-jupyterlab,https://www.npmjs.com/package/@finos/perspective-jupyterlab,2024-09-03 06:50:59.267,6.0,3839.0,,,,,,,,,,,, +184,tensorboardX,lanpa/tensorboardX,ml-experiments,,https://github.com/lanpa/tensorboardX,https://github.com/lanpa/tensorboardX,MIT,2017-06-13 13:54:19.000,2024-09-03 22:18:55.000000,2023-11-12 14:28:03,528.0,,865.0,84.0,276.0,81.0,376.0,7848.0,"tensorboard for pytorch (and chainer, mxnet, numpy, ...).",82.0,33,True,2023-07-30 14:05:26.000,2.6.2,24.0,tensorboardX,conda-forge/tensorboardx,,,438.0,2856011.0,48323.0,47698.0,https://pypi.org/project/tensorboardX,2023-08-20 13:38:18.000,625.0,2831822.0,https://anaconda.org/conda-forge/tensorboardx,2023-08-20 16:29:43.490,1209219.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +185,Bayesian Optimization,fmfn/BayesianOptimization,hyperopt,,https://github.com/bayesian-optimization/BayesianOptimization,https://github.com/bayesian-optimization/BayesianOptimization,MIT,2014-06-06 08:18:56.000,2024-08-20 18:16:26.000000,2024-07-23 07:44:51,373.0,13.0,1525.0,129.0,156.0,13.0,346.0,7777.0,A Python implementation of global optimization with gaussian processes.,47.0,33,True,2024-07-10 12:02:35.000,1.5.1,16.0,bayesian-optimization,,,,155.0,435015.0,3043.0,2899.0,https://pypi.org/project/bayesian-optimization,2024-07-10 12:02:35.000,144.0,435014.0,,,,1.0,,,,,,,,bayesian-optimization/BayesianOptimization,,,,,,,,,,,,,,,,, +186,AutoGluon,autogluon/autogluon,hyperopt,,https://github.com/autogluon/autogluon,https://github.com/autogluon/autogluon,Apache-2.0,2019-07-29 18:51:24.000,2024-09-05 09:04:27.000000,2024-09-04 18:51:00,2298.0,65.0,897.0,101.0,2575.0,345.0,1077.0,7626.0,Fast and Accurate ML in 3 Lines of Code.,125.0,33,True,2024-06-14 20:30:21.000,1.1.1,1596.0,autogluon,conda-forge/autogluon,https://auto.gluon.ai,"['pytorch', 'sklearn']",,87778.0,827.0,802.0,https://pypi.org/project/autogluon,2024-09-05 09:04:27.000,25.0,86734.0,https://anaconda.org/conda-forge/autogluon,2024-06-18 07:07:41.213,17733.0,1.0,autogluon/autogluon,https://hub.docker.com/r/autogluon/autogluon,2024-03-07 07:21:23.461952,17.0,9816.0,,,,,,,,,,,,,,,,,,,, +187,Hyperopt,hyperopt/hyperopt,hyperopt,,https://github.com/hyperopt/hyperopt,https://github.com/hyperopt/hyperopt,BSD-3-Clause,2011-09-06 22:24:59.000,2024-08-05 23:12:38.000000,2024-03-13 19:58:20,1220.0,,1045.0,122.0,276.0,174.0,495.0,7188.0,Distributed Asynchronous Hyperparameter Optimization in Python.,103.0,33,True,2021-11-17 10:07:00.808,0.2.7,13.0,hyperopt,conda-forge/hyperopt,,,,2291978.0,17101.0,16658.0,https://pypi.org/project/hyperopt,2021-11-17 10:07:00.808,443.0,2281082.0,https://anaconda.org/conda-forge/hyperopt,2023-06-16 16:14:11.076,784556.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +188,featuretools,alteryx/featuretools,hyperopt,,https://github.com/alteryx/featuretools,https://github.com/alteryx/featuretools,BSD-3-Clause,2017-09-08 22:15:17.000,2024-09-02 17:04:17.000000,2024-06-21 13:43:40,1379.0,7.0,869.0,155.0,1730.0,149.0,865.0,7182.0,An open source python library for automated feature engineering.,72.0,33,True,2024-05-14 18:59:58.000,1.31.0,106.0,featuretools,conda-forge/featuretools,,,,62695.0,1822.0,1748.0,https://pypi.org/project/featuretools,2024-05-14 18:59:58.000,74.0,58712.0,https://anaconda.org/conda-forge/featuretools,2024-05-15 15:26:44.535,203139.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +189,librosa,librosa/librosa,audio,,https://github.com/librosa/librosa,https://github.com/librosa/librosa,ISC,2012-10-20 14:21:01.000,2024-08-19 10:49:43.000000,2024-08-19 10:49:35,3281.0,7.0,954.0,137.0,661.0,54.0,1155.0,6984.0,Python library for audio and music analysis.,123.0,33,True,2024-05-14 15:48:50.000,0.10.2.post1,43.0,librosa,conda-forge/librosa,,,,2717172.0,1330.0,,https://pypi.org/project/librosa,2024-05-14 15:49:38.000,1330.0,2701096.0,https://anaconda.org/conda-forge/librosa,2024-05-15 16:59:32.016,803833.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +190,InterpretML,interpretml/interpret,interpretability,,https://github.com/interpretml/interpret,https://github.com/interpretml/interpret,MIT,2019-05-03 05:47:52.000,2024-09-05 01:46:07.000000,2024-09-05 01:10:22,3346.0,181.0,726.0,144.0,123.0,103.0,341.0,6199.0,Fit interpretable models. Explain blackbox machine learning.,46.0,33,True,2024-08-07 19:03:09.000,0.6.3,51.0,interpret,,,['jupyter'],,87779.0,782.0,733.0,https://pypi.org/project/interpret,2024-08-07 19:03:09.000,49.0,87779.0,,,,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +191,Chainer,chainer/chainer,ml-frameworks,,https://github.com/chainer/chainer,https://github.com/chainer/chainer,MIT,2015-06-05 05:50:37.000,2023-08-28 17:18:20.000000,2022-10-17 02:18:00,30611.0,,1368.0,286.0,6588.0,12.0,2032.0,5884.0,A flexible framework of neural networks for deep learning.,326.0,33,False,2022-06-29 08:19:03.000,7.8.1.post1,111.0,chainer,conda-forge/chainer,,,,47307.0,3360.0,3302.0,https://pypi.org/project/chainer,2022-01-05 05:33:36.000,58.0,46961.0,https://anaconda.org/conda-forge/chainer,2023-06-16 19:17:58.452,19061.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +192,DEAP,deap/deap,distributed-ml,,https://github.com/DEAP/deap,https://github.com/DEAP/deap,LGPL-3.0,2014-05-21 20:07:39.000,2024-09-03 13:46:04.210000,2024-05-07 13:49:33,2334.0,,1118.0,191.0,238.0,277.0,285.0,5751.0,Distributed Evolutionary Algorithms in Python.,88.0,33,False,2023-07-21 10:51:54.000,1.4.1,27.0,deap,conda-forge/deap,,,,208297.0,5398.0,5153.0,https://pypi.org/project/deap,2023-07-21 10:51:54.000,245.0,199155.0,https://anaconda.org/conda-forge/deap,2024-09-03 13:46:04.210,429717.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +193,Captum,pytorch/captum,interpretability,,https://github.com/pytorch/captum,https://github.com/pytorch/captum,BSD-3-Clause,2019-08-27 15:34:41.000,2024-08-30 15:18:25.000000,2024-08-22 17:38:55,1117.0,25.0,482.0,265.0,799.0,230.0,338.0,4792.0,Model interpretability and understanding for PyTorch.,116.0,33,True,2023-12-05 09:21:02.000,0.7.0,10.0,captum,conda-forge/captum,,['pytorch'],,255610.0,2442.0,2316.0,https://pypi.org/project/captum,2023-12-05 08:32:04.000,126.0,253839.0,https://anaconda.org/conda-forge/captum,2023-06-16 19:28:19.191,58453.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +194,geopy,geopy/geopy,geospatial-data,,https://github.com/geopy/geopy,https://github.com/geopy/geopy,MIT,2010-03-04 22:05:28.000,2024-08-14 15:31:25.000000,2023-11-23 21:41:49,1136.0,,644.0,89.0,271.0,41.0,252.0,4429.0,Geocoding library for Python.,133.0,33,True,2023-11-23 21:50:14.000,2.4.1,61.0,geopy,conda-forge/geopy,,,75.0,5803222.0,874.0,,https://pypi.org/project/geopy,2023-11-23 21:49:30.000,874.0,5775135.0,https://anaconda.org/conda-forge/geopy,2024-02-28 17:12:19.096,1432450.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +195,ftfy,rspeer/python-ftfy,nlp,,https://github.com/rspeer/python-ftfy,https://github.com/rspeer/python-ftfy,Apache-2.0,2012-08-24 16:14:59.000,2024-09-03 22:54:33.000000,2024-08-06 01:28:54,637.0,16.0,119.0,75.0,75.0,13.0,129.0,3753.0,"Fixes mojibake and other glitches in Unicode text, after the fact.",19.0,33,True,2024-08-06 01:36:27.000,6.2.3,53.0,ftfy,conda-forge/ftfy,,,6.0,5372067.0,22922.0,22370.0,https://pypi.org/project/ftfy,2024-08-06 01:30:44.000,552.0,5365291.0,https://anaconda.org/conda-forge/ftfy,2024-08-06 18:05:02.848,298158.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +196,torchtext,pytorch/text,nlp,,https://github.com/pytorch/text,https://github.com/pytorch/text,BSD-3-Clause,2016-12-12 00:56:03.000,2024-09-05 11:34:49.000000,2024-08-14 20:32:21,1311.0,2.0,813.0,308.0,1470.0,331.0,518.0,3493.0,"Models, data loaders and abstractions for language processing, powered by PyTorch.",156.0,33,True,2024-04-24 16:20:45.000,0.18.0,34.0,torchtext,,,['pytorch'],,1048153.0,285.0,,https://pypi.org/project/torchtext,2024-04-24 15:49:45.000,285.0,1048153.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +197,datashader,holoviz/datashader,data-viz,,https://github.com/holoviz/datashader,https://github.com/holoviz/datashader,BSD-3-Clause,2015-12-23 18:02:20.000,2024-08-18 13:16:01.000000,2024-08-08 09:18:37,1519.0,7.0,363.0,90.0,763.0,136.0,448.0,3295.0,Quickly and accurately render even the largest data.,56.0,33,True,2024-07-04 16:40:09.000,0.16.3,51.0,datashader,conda-forge/datashader,,,,134895.0,4869.0,4676.0,https://pypi.org/project/datashader,2024-07-04 12:26:22.000,193.0,113912.0,https://anaconda.org/conda-forge/datashader,2024-07-08 10:48:31.985,1091154.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +198,hdbscan,scikit-learn-contrib/hdbscan,others,,https://github.com/scikit-learn-contrib/hdbscan,https://github.com/scikit-learn-contrib/hdbscan,BSD-3-Clause,2015-04-22 13:32:37.000,2024-08-15 21:14:21.000000,2024-08-15 21:14:21,1029.0,22.0,492.0,56.0,145.0,358.0,170.0,2761.0,A high performance implementation of HDBSCAN clustering.,92.0,33,True,2024-08-05 22:10:29.000,release-0.8.38-1,54.0,hdbscan,conda-forge/hdbscan,,['sklearn'],,620044.0,4295.0,3966.0,https://pypi.org/project/hdbscan,2024-08-05 22:21:39.000,329.0,575151.0,https://anaconda.org/conda-forge/hdbscan,2024-08-14 05:14:15.129,2109979.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +199,scikit-optimize,scikit-optimize/scikit-optimize,hyperopt,,https://github.com/scikit-optimize/scikit-optimize,https://github.com/scikit-optimize/scikit-optimize,BSD-3-Clause,2016-03-20 21:10:54.000,2024-06-05 12:17:25.116000,2021-10-12 13:32:38,1570.0,,545.0,63.0,546.0,322.0,393.0,2738.0,Sequential model-based optimization with a `scipy.optimize` interface.,76.0,33,False,2024-06-04 19:12:54.000,0.10.2,23.0,scikit-optimize,conda-forge/scikit-optimize,,,,827580.0,6811.0,6445.0,https://pypi.org/project/scikit-optimize,2024-06-04 19:12:54.000,366.0,812468.0,https://anaconda.org/conda-forge/scikit-optimize,2024-06-05 12:17:25.116,740514.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +200,pgmpy,pgmpy/pgmpy,probabilistics,,https://github.com/pgmpy/pgmpy,https://github.com/pgmpy/pgmpy,MIT,2013-09-20 08:18:58.000,2024-09-04 20:35:55.000000,2024-09-04 20:35:48,2982.0,25.0,698.0,74.0,893.0,293.0,632.0,2696.0,"Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in..",127.0,33,True,2024-08-09 17:03:45.000,0.1.26,26.0,pgmpy,,,,499.0,74021.0,1194.0,1142.0,https://pypi.org/project/pgmpy,2024-08-09 16:48:04.000,52.0,74012.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +201,jellyfish,jamesturk/jellyfish,nlp,,https://github.com/jamesturk/jellyfish,https://github.com/jamesturk/jellyfish,MIT,2010-07-09 20:41:11.000,2024-07-30 20:34:59.057000,2024-07-28 08:14:03,562.0,9.0,157.0,42.0,80.0,7.0,130.0,2037.0,a python library for doing approximate and phonetic matching of strings.,32.0,33,True,2024-07-28 08:19:05.000,1.1.0,44.0,jellyfish,conda-forge/jellyfish,,,,5445651.0,10523.0,10258.0,https://pypi.org/project/jellyfish,2024-07-28 08:19:05.000,265.0,5426320.0,https://anaconda.org/conda-forge/jellyfish,2024-07-30 20:34:59.057,985899.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +202,Pythran,serge-sans-paille/pythran,others,,https://github.com/serge-sans-paille/pythran,https://github.com/serge-sans-paille/pythran,BSD-3-Clause,2012-05-29 08:02:14.000,2024-09-03 03:38:51.615000,2024-09-02 05:23:34,3744.0,29.0,190.0,49.0,1382.0,133.0,728.0,1993.0,Ahead of Time compiler for numeric kernels.,72.0,33,True,2024-05-28 05:22:14.000,0.16.1,61.0,pythran,conda-forge/pythran,,,,210331.0,2576.0,2557.0,https://pypi.org/project/pythran,2024-05-28 05:22:14.000,19.0,196371.0,https://anaconda.org/conda-forge/pythran,2024-09-03 03:38:51.615,670089.0,2.0,,,,,,,,,,,,,,,,,,pythran,python-pythran,,,,,, +203,PyCUDA,inducer/pycuda,gpu-utilities,,https://github.com/inducer/pycuda,https://github.com/inducer/pycuda,MIT,2011-04-06 02:53:31.000,2024-08-17 22:59:08.823000,2024-07-30 13:52:24,1606.0,12.0,285.0,56.0,141.0,83.0,190.0,1816.0,"CUDA integration for Python, plus shiny features.",82.0,33,True,2024-07-30 16:38:24.000,2024.1.2,55.0,pycuda,conda-forge/pycuda,,,,62182.0,3233.0,3077.0,https://pypi.org/project/pycuda,2024-07-30 13:53:42.000,156.0,49585.0,https://anaconda.org/conda-forge/pycuda,2024-08-17 22:59:08.823,529087.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +204,tensorly,tensorly/tensorly,others,,https://github.com/tensorly/tensorly,https://github.com/tensorly/tensorly,BSD-2-Clause,2016-10-21 23:14:52.000,2024-08-15 14:54:51.000000,2024-08-15 14:54:50,1948.0,56.0,288.0,45.0,284.0,58.0,212.0,1536.0,TensorLy: Tensor Learning in Python.,68.0,33,True,2024-06-09 17:29:20.000,0.8.2,20.0,tensorly,conda-forge/tensorly,,,,78491.0,826.0,734.0,https://pypi.org/project/tensorly,2023-03-08 01:09:02.237,92.0,70670.0,https://anaconda.org/conda-forge/tensorly,2024-06-10 02:35:16.323,367622.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +205,ipyleaflet,jupyter-widgets/ipyleaflet,geospatial-data,,https://github.com/jupyter-widgets/ipyleaflet,https://github.com/jupyter-widgets/ipyleaflet,MIT,2014-05-07 16:32:10.000,2024-08-21 06:38:39.000000,2024-07-22 07:57:37,1193.0,7.0,363.0,67.0,616.0,292.0,358.0,1482.0,A Jupyter - Leaflet.js bridge.,90.0,33,True,2024-07-22 08:02:59.000,0.19.2,84.0,ipyleaflet,conda-forge/ipyleaflet,,['jupyter'],,288659.0,11057.0,10776.0,https://pypi.org/project/ipyleaflet,2024-07-22 08:02:59.000,272.0,258297.0,https://anaconda.org/conda-forge/ipyleaflet,2024-07-22 12:26:50.743,1241059.0,2.0,,,,,,,,,jupyter-leaflet,https://www.npmjs.com/package/jupyter-leaflet,2024-07-22 08:02:28.803,9.0,6496.0,,,,,,,,,,,, +206,agate,wireservice/agate,others,,https://github.com/wireservice/agate,https://github.com/wireservice/agate,MIT,2014-04-25 13:59:09.000,2024-07-30 07:34:33.171000,2024-07-30 00:56:56,1557.0,2.0,155.0,40.0,133.0,4.0,644.0,1169.0,A Python data analysis library that is optimized for humans instead of machines.,53.0,33,True,2024-07-30 00:58:25.000,1.12.0,37.0,agate,conda-forge/agate,,,,9935088.0,3729.0,3680.0,https://pypi.org/project/agate,2024-07-30 00:58:25.000,49.0,9929442.0,https://anaconda.org/conda-forge/agate,2024-07-30 07:34:33.171,225876.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +207,NIPYPE,nipy/nipype,medical-data,,https://github.com/nipy/nipype,https://github.com/nipy/nipype,Apache-2.0,2010-07-22 17:06:49.000,2024-08-01 09:45:41.000000,2024-05-30 14:50:18,14882.0,,506.0,50.0,2299.0,403.0,962.0,745.0,Workflows and interfaces for neuroimaging packages.,256.0,33,True,2023-04-06 12:55:55.544,1.8.6,64.0,nipype,conda-forge/nipype,,,,188208.0,5011.0,4864.0,https://pypi.org/project/nipype,2023-04-06 12:55:55.544,147.0,174437.0,https://anaconda.org/conda-forge/nipype,2023-09-22 18:28:24.915,674782.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +208,zipline,quantopian/zipline,financial-data,,https://github.com/quantopian/zipline,https://github.com/quantopian/zipline,Apache-2.0,2012-10-19 15:50:29.000,2024-02-13 08:02:51.000000,2020-10-14 16:36:49,6226.0,,4706.0,1008.0,1869.0,363.0,658.0,17473.0,"Zipline, a Pythonic Algorithmic Trading Library.",161.0,32,False,2020-10-05 15:46:20.429,1.4.1,30.0,zipline,conda-forge/zipline,,,,2656.0,1017.0,1007.0,https://pypi.org/project/zipline,2020-10-05 15:46:20.429,10.0,2479.0,https://anaconda.org/conda-forge/zipline,2023-06-16 19:21:35.991,8543.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +209,tensor2tensor,tensorflow/tensor2tensor,tensorflow-utils,,https://github.com/tensorflow/tensor2tensor,https://github.com/tensorflow/tensor2tensor,Apache-2.0,2017-06-15 16:57:39.000,2023-06-02 18:55:09.000000,2023-04-01 10:19:28,4379.0,,3461.0,465.0,671.0,590.0,672.0,15290.0,Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.,244.0,32,False,2020-06-17 16:31:34.798,1.15.7,79.0,tensor2tensor,,,['tensorflow'],,6734.0,1521.0,1507.0,https://pypi.org/project/tensor2tensor,2020-06-17 16:31:34.798,14.0,6734.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +210,Turi Create,apple/turicreate,ml-frameworks,,https://github.com/apple/turicreate,https://github.com/apple/turicreate,BSD-3-Clause,2017-12-01 00:42:04.000,2023-11-01 06:14:06.000000,2021-11-29 19:55:31,1571.0,,1135.0,338.0,1683.0,523.0,1294.0,11191.0,Turi Create simplifies the development of custom machine learning models.,87.0,32,False,2020-09-30 22:51:40.000,6.4.1,31.0,turicreate,,,,10421.0,16235.0,379.0,374.0,https://pypi.org/project/turicreate,2020-09-30 22:51:40.000,5.0,16107.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +211,ParlAI,facebookresearch/ParlAI,nlp,,https://github.com/facebookresearch/ParlAI,https://github.com/facebookresearch/ParlAI,MIT,2017-04-24 17:10:44.000,2023-11-03 14:30:00.000000,2023-11-03 14:30:00,4358.0,,2095.0,283.0,3401.0,51.0,1494.0,10463.0,A framework for training and evaluating AI models on a variety of openly available dialogue datasets.,218.0,32,True,2023-06-06 20:46:16.091,1.7.2,25.0,parlai,,,['pytorch'],,3715.0,257.0,252.0,https://pypi.org/project/parlai,2022-09-20 02:56:01.305,5.0,3715.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +212,Sonnet,deepmind/sonnet,ml-frameworks,,https://github.com/google-deepmind/sonnet,https://github.com/google-deepmind/sonnet,Apache-2.0,2017-04-03 11:34:35.000,2024-07-30 21:21:24.000000,2024-04-08 20:21:10,864.0,,1289.0,423.0,88.0,32.0,161.0,9746.0,TensorFlow-based neural network library.,59.0,32,True,2024-01-02 11:15:06.000,2.0.2,29.0,dm-sonnet,conda-forge/sonnet,,['tensorflow'],,17646.0,1351.0,1332.0,https://pypi.org/project/dm-sonnet,2024-01-02 11:15:06.000,19.0,17078.0,https://anaconda.org/conda-forge/sonnet,2023-06-16 16:19:12.602,32999.0,3.0,,,,,,,,google-deepmind/sonnet,,,,,,,,,,,,,,,,, +213,TPOT,EpistasisLab/tpot,hyperopt,,https://github.com/EpistasisLab/tpot,https://github.com/EpistasisLab/tpot,LGPL-3.0,2015-11-03 21:08:40.000,2024-07-25 10:51:05.000000,2024-02-23 19:03:07,2440.0,,1559.0,287.0,434.0,293.0,639.0,9652.0,A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.,121.0,32,False,2024-02-23 19:06:10.000,0.12.2,63.0,tpot,conda-forge/tpot,,['sklearn'],,47953.0,2972.0,2934.0,https://pypi.org/project/tpot,2024-02-23 19:06:10.000,38.0,42712.0,https://anaconda.org/conda-forge/tpot,2024-02-26 15:57:08.680,267314.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +214,cleanlab,cleanlab/cleanlab,others,,https://github.com/cleanlab/cleanlab,https://github.com/cleanlab/cleanlab,AGPL-3.0,2018-05-11 01:55:21.000,2024-09-04 16:32:20.000000,2024-09-04 16:32:12,1733.0,80.0,711.0,89.0,795.0,121.0,270.0,9364.0,"The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.",50.0,32,False,2024-06-25 23:18:36.000,2.6.6,31.0,cleanlab,conda-forge/cleanlab,,,,23896.0,389.0,371.0,https://pypi.org/project/cleanlab,2024-06-25 23:18:36.000,18.0,23193.0,https://anaconda.org/conda-forge/cleanlab,2024-06-26 17:29:18.404,28826.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +215,PaddleSeg,PaddlePaddle/PaddleSeg,image,,https://github.com/PaddlePaddle/PaddleSeg,https://github.com/PaddlePaddle/PaddleSeg,Apache-2.0,2019-08-26 02:32:22.000,2024-08-31 00:08:42.000000,2024-08-23 06:11:11,2922.0,6.0,1664.0,90.0,1674.0,228.0,1872.0,8537.0,"Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in..",126.0,32,True,2023-10-18 03:54:18.000,2.9.0,19.0,paddleseg,,,['paddle'],,1691.0,1273.0,1266.0,https://pypi.org/project/paddleseg,2022-11-30 11:24:02.578,7.0,1691.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +216,tsfresh,blue-yonder/tsfresh,time-series-data,,https://github.com/blue-yonder/tsfresh,https://github.com/blue-yonder/tsfresh,MIT,2016-10-26 11:29:17.000,2024-08-04 02:13:02.666000,2024-08-03 20:47:58,560.0,6.0,1206.0,169.0,436.0,68.0,474.0,8345.0,Automatic extraction of relevant features from time series:.,96.0,32,True,2024-08-03 20:51:43.000,0.20.3,32.0,tsfresh,conda-forge/tsfresh,,['sklearn'],,310733.0,113.0,21.0,https://pypi.org/project/tsfresh,2024-08-03 20:51:43.000,92.0,284114.0,https://anaconda.org/conda-forge/tsfresh,2024-08-04 02:13:02.666,1384223.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +217,stanza,stanfordnlp/stanza,nlp,,https://github.com/stanfordnlp/stanza,https://github.com/stanfordnlp/stanza,Apache-2.0,2017-09-26 08:00:56.000,2024-09-04 21:50:46.000000,2024-04-20 16:29:42,4447.0,,884.0,141.0,496.0,97.0,793.0,7203.0,"Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages.",68.0,32,True,2024-04-20 18:58:25.000,1.8.2,25.0,stanza,stanfordnlp/stanza,,,,425715.0,3222.0,3048.0,https://pypi.org/project/stanza,2024-04-20 18:57:48.000,174.0,425569.0,https://anaconda.org/stanfordnlp/stanza,2023-06-16 19:18:21.932,7896.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +218,OpenNMT,OpenNMT/OpenNMT-py,nlp,,https://github.com/OpenNMT/OpenNMT-py,https://github.com/OpenNMT/OpenNMT-py,MIT,2017-02-22 19:01:50.000,2024-06-27 17:56:28.000000,2024-06-27 17:56:21,2895.0,4.0,2243.0,176.0,1152.0,27.0,1429.0,6701.0,Open Source Neural Machine Translation and (Large) Language Models in PyTorch.,191.0,32,True,2024-03-18 14:02:12.000,3.5.1,50.0,OpenNMT-py,,,['pytorch'],,8393.0,311.0,288.0,https://pypi.org/project/OpenNMT-py,2024-03-18 14:02:12.000,23.0,8393.0,,,,2.0,,,,,,-3.0,,,,,,,,,,,,,,,,,,, +219,BigDL,intel-analytics/BigDL,distributed-ml,,https://github.com/intel-analytics/ipex-llm,https://github.com/intel-analytics/ipex-llm,Apache-2.0,2016-08-29 07:59:50.000,2024-09-05 09:06:07.000000,2024-09-05 09:06:07,3426.0,486.0,1238.0,246.0,9488.0,954.0,1576.0,6449.0,"Accelerate local LLM inference and finetuning (LLaMA, Mistral, ChatGLM, Qwen, Baichuan, Mixtral, Gemma, Phi, MiniCPM,..",108.0,32,True,2024-08-22 09:06:57.000,2.1.0,869.0,bigdl,,,,626.0,4199.0,7.0,,https://pypi.org/project/bigdl,2024-03-24 14:04:20.000,2.0,4192.0,,,,2.0,,,,,,,,intel-analytics/ipex-llm,,,,,,,,,,,,com.intel.analytics.bigdl:bigdl-SPARK_2.4,https://search.maven.org/artifact/com.intel.analytics.bigdl/bigdl-SPARK_2.4,2021-04-20 01:33:14,5.0,, +220,tensorpack,tensorpack/tensorpack,ml-frameworks,,https://github.com/tensorpack/tensorpack,https://github.com/tensorpack/tensorpack,Apache-2.0,2015-12-25 23:08:44.000,2023-08-06 00:30:36.000000,2023-08-06 00:30:36,2944.0,,1813.0,196.0,206.0,13.0,1343.0,6296.0,"A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility.",58.0,32,False,2020-04-24 19:04:45.487,0.10.1,37.0,tensorpack,conda-forge/tensorpack,,['tensorflow'],177.0,13870.0,1608.0,1590.0,https://pypi.org/project/tensorpack,2021-01-22 19:59:12.425,18.0,13546.0,https://anaconda.org/conda-forge/tensorpack,2023-06-16 19:27:42.012,11281.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +221,kaggle,Kaggle/kaggle-api,ml-experiments,,https://github.com/Kaggle/kaggle-api,https://github.com/Kaggle/kaggle-api,Apache-2.0,2018-01-25 03:02:39.000,2024-09-04 21:56:50.000000,2024-09-04 21:45:33,194.0,16.0,1072.0,198.0,138.0,153.0,327.0,6116.0,Official Kaggle API.,46.0,32,True,2024-07-24 19:08:19.000,1.6.17,74.0,kaggle,conda-forge/kaggle,,,,203033.0,223.0,21.0,https://pypi.org/project/kaggle,2024-07-24 19:08:19.000,202.0,199351.0,https://anaconda.org/conda-forge/kaggle,2024-07-27 21:52:01.276,176764.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +222,Tesseract,madmaze/pytesseract,ocr,,https://github.com/madmaze/pytesseract,https://github.com/madmaze/pytesseract,Apache-2.0,2010-10-27 23:02:49.000,2024-08-16 02:36:10.000000,2024-05-08 23:39:06,618.0,,714.0,110.0,192.0,18.0,348.0,5753.0,Python-tesseract is an optical character recognition (OCR) tool for python.,49.0,32,True,2024-08-16 02:36:10.000,0.3.13,28.0,pytesseract,conda-forge/pytesseract,,,,3090860.0,941.0,,https://pypi.org/project/pytesseract,2024-08-16 02:36:10.000,941.0,3078423.0,https://anaconda.org/conda-forge/pytesseract,2023-10-15 19:50:43.241,621879.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +223,aim,aimhubio/aim,ml-experiments,,https://github.com/aimhubio/aim,https://github.com/aimhubio/aim,Apache-2.0,2019-05-31 18:25:07.000,2024-09-04 20:02:13.000000,2024-08-29 12:26:27,2209.0,26.0,315.0,43.0,2177.0,363.0,664.0,5121.0,Aim An easy-to-use & supercharged open-source experiment tracker.,76.0,32,True,2024-08-14 09:46:54.000,3.24.0,1105.0,aim,conda-forge/aim,,,,96759.0,698.0,660.0,https://pypi.org/project/aim,2024-09-02 20:08:21.000,38.0,94868.0,https://anaconda.org/conda-forge/aim,2024-06-14 16:22:37.168,71862.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +224,MLxtend,rasbt/mlxtend,sklearn-utils,,https://github.com/rasbt/mlxtend,https://github.com/rasbt/mlxtend,BSD-3-Clause,2014-08-14 01:56:16.000,2024-07-02 00:51:45.000000,2024-07-02 00:51:45,1646.0,1.0,855.0,115.0,528.0,146.0,342.0,4857.0,A library of extension and helper modules for Pythons data analysis and machine learning libraries.,107.0,32,True,2024-01-05 09:13:47.000,0.23.1,52.0,mlxtend,conda-forge/mlxtend,,['sklearn'],,604684.0,15021.0,14848.0,https://pypi.org/project/mlxtend,2024-01-05 09:13:47.000,173.0,598279.0,https://anaconda.org/conda-forge/mlxtend,2024-01-05 18:58:45.309,320255.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +225,Dedupe,dedupeio/dedupe,nlp,,https://github.com/dedupeio/dedupe,https://github.com/dedupeio/dedupe,MIT,2012-04-20 14:57:36.000,2024-08-15 14:31:34.000000,2024-08-15 14:20:30,3331.0,28.0,548.0,120.0,379.0,72.0,743.0,4082.0,"A python library for accurate and scalable fuzzy matching, record deduplication and entity-resolution.",72.0,32,True,2024-08-15 14:31:34.000,3.0.3,179.0,dedupe,conda-forge/dedupe,,,,77683.0,352.0,333.0,https://pypi.org/project/dedupe,2024-08-15 14:31:34.000,19.0,75574.0,https://anaconda.org/conda-forge/dedupe,2023-06-16 19:28:08.623,69628.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +226,AzureML SDK,Azure/MachineLearningNotebooks,ml-experiments,,https://github.com/Azure/MachineLearningNotebooks,https://github.com/Azure/MachineLearningNotebooks,MIT,2018-08-17 17:29:14.000,2024-08-08 15:36:05.000000,2024-08-08 15:36:05,1297.0,2.0,2506.0,1954.0,535.0,390.0,1076.0,4062.0,Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft.,64.0,32,True,2024-08-05 21:53:53.000,1.57.0,104.0,azureml-sdk,,,,634.0,491873.0,31.0,,https://pypi.org/project/azureml-sdk,2024-08-05 21:53:53.000,31.0,491865.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +227,GPyTorch,cornellius-gp/gpytorch,probabilistics,,https://github.com/cornellius-gp/gpytorch,https://github.com/cornellius-gp/gpytorch,MIT,2017-06-09 14:48:20.000,2024-09-05 03:23:42.000000,2024-09-05 03:23:42,3891.0,33.0,552.0,58.0,909.0,363.0,977.0,3517.0,A highly efficient implementation of Gaussian Processes in PyTorch.,135.0,32,True,2024-06-27 15:53:07.000,1.12,39.0,gpytorch,conda-forge/gpytorch,,['pytorch'],,244066.0,2476.0,2307.0,https://pypi.org/project/gpytorch,2024-06-27 15:58:50.000,169.0,240733.0,https://anaconda.org/conda-forge/gpytorch,2024-06-28 20:37:43.289,173359.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +228,tensorflow-hub,tensorflow/hub,tensorflow-utils,,https://github.com/tensorflow/hub,https://github.com/tensorflow/hub,Apache-2.0,2018-03-12 07:55:42.000,2024-06-06 21:49:17.000000,2024-06-06 21:49:15,1186.0,,1666.0,152.0,210.0,13.0,692.0,3462.0,A library for transfer learning by reusing parts of TensorFlow models.,107.0,32,True,2024-01-30 15:53:29.000,0.16.1,20.0,tensorflow-hub,conda-forge/tensorflow-hub,,['tensorflow'],,1914394.0,298.0,,https://pypi.org/project/tensorflow-hub,2024-01-30 14:49:07.000,298.0,1912276.0,https://anaconda.org/conda-forge/tensorflow-hub,2024-05-07 05:39:07.350,103822.0,2.0,,,,,,-3.0,,,,,,,,,,,,,,,,,,, +229,FairScale,facebookresearch/fairscale,distributed-ml,,https://github.com/facebookresearch/fairscale,https://github.com/facebookresearch/fairscale,BSD-3-Clause,2020-07-07 19:02:01.000,2024-08-30 20:15:08.000000,2024-05-03 16:54:19,704.0,,273.0,45.0,828.0,102.0,285.0,3134.0,PyTorch extensions for high performance and large scale training.,75.0,32,True,2022-12-11 18:09:31.906,0.4.13,35.0,fairscale,conda-forge/fairscale,,['pytorch'],,510370.0,6292.0,6139.0,https://pypi.org/project/fairscale,2022-12-11 18:09:31.906,153.0,502054.0,https://anaconda.org/conda-forge/fairscale,2023-11-28 00:29:10.363,282767.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +230,lightly,lightly-ai/lightly,image,,https://github.com/lightly-ai/lightly,https://github.com/lightly-ai/lightly,MIT,2020-10-13 13:02:56.000,2024-09-04 13:56:55.000000,2024-08-20 08:04:50,1245.0,61.0,245.0,29.0,1093.0,89.0,486.0,2913.0,A python library for self-supervised learning on images.,42.0,32,True,2024-08-20 10:04:51.000,1.5.12,126.0,lightly,,,['pytorch'],,32177.0,320.0,306.0,https://pypi.org/project/lightly,2024-08-20 10:05:59.000,14.0,32177.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +231,Lifelines,CamDavidsonPilon/lifelines,medical-data,,https://github.com/CamDavidsonPilon/lifelines,https://github.com/CamDavidsonPilon/lifelines,MIT,2013-08-28 00:16:42.000,2024-06-27 16:03:16.815000,2024-06-26 15:35:26,2300.0,7.0,551.0,69.0,483.0,260.0,710.0,2340.0,Survival analysis in Python.,118.0,32,True,2024-06-26 15:36:45.000,0.29.0,171.0,lifelines,conda-forge/lifelines,,,,745554.0,2992.0,2852.0,https://pypi.org/project/lifelines,2024-06-26 15:36:45.000,140.0,738598.0,https://anaconda.org/conda-forge/lifelines,2024-06-27 16:03:16.815,361747.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +232,TF Addons,tensorflow/addons,tensorflow-utils,,https://github.com/tensorflow/addons,https://github.com/tensorflow/addons,Apache-2.0,2018-11-26 23:57:17.000,2024-09-03 20:56:01.000000,2024-04-15 22:25:34,1519.0,,610.0,57.0,1884.0,90.0,899.0,1688.0,Useful extra functionality for TensorFlow 2.x maintained by SIG-addons.,207.0,32,True,2023-11-28 01:45:31.000,0.23.0,38.0,tensorflow-addons,,,['tensorflow'],,925066.0,363.0,,https://pypi.org/project/tensorflow-addons,2023-11-28 01:45:31.000,363.0,925066.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +233,Opacus,pytorch/opacus,privacy-ml,,https://github.com/pytorch/opacus,https://github.com/pytorch/opacus,Apache-2.0,2019-12-07 01:58:09.000,2024-08-29 18:19:04.000000,2024-08-29 18:13:19,728.0,14.0,331.0,46.0,381.0,72.0,225.0,1668.0,Training PyTorch models with differential privacy.,81.0,32,True,2024-08-03 10:32:52.000,1.5.2,24.0,opacus,conda-forge/opacus,,['pytorch'],116.0,260323.0,894.0,858.0,https://pypi.org/project/opacus,2024-08-03 10:32:52.000,36.0,259801.0,https://anaconda.org/conda-forge/opacus,2024-08-05 12:31:17.057,16658.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +234,Geocoder,DenisCarriere/geocoder,geospatial-data,,https://github.com/DenisCarriere/geocoder,https://github.com/DenisCarriere/geocoder,MIT,2014-01-13 04:19:21.000,2024-04-20 16:14:16.000000,2018-10-12 15:53:05,1251.0,,284.0,51.0,158.0,114.0,218.0,1617.0,Python Geocoder.,73.0,32,False,2021-12-15 15:58:16.110,1.1.4,110.0,geocoder,conda-forge/geocoder,,,,743362.0,11307.0,11102.0,https://pypi.org/project/geocoder,2021-12-15 15:58:16.110,205.0,741726.0,https://anaconda.org/conda-forge/geocoder,2023-06-16 13:21:27.128,148945.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,geocoder, +235,pmdarima,alkaline-ml/pmdarima,time-series-data,,https://github.com/alkaline-ml/pmdarima,https://github.com/alkaline-ml/pmdarima,MIT,2017-03-30 14:58:30.000,2024-08-19 19:12:04.000000,2024-02-23 02:45:37,1079.0,,231.0,34.0,254.0,62.0,272.0,1572.0,"A statistical library designed to fill the void in Pythons time series analysis capabilities, including the equivalent..",23.0,32,True,2023-10-23 16:52:00.000,2.0.4,44.0,pmdarima,conda-forge/pmdarima,,,,2252557.0,9287.0,9134.0,https://pypi.org/project/pmdarima,2023-10-23 14:02:41.000,153.0,2227875.0,https://anaconda.org/conda-forge/pmdarima,2024-07-14 16:03:51.778,1160080.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +236,PySAL,pysal/pysal,geospatial-data,,https://github.com/pysal/pysal,https://github.com/pysal/pysal,BSD-3-Clause,2013-02-19 17:27:42.000,2024-07-31 17:39:21.000000,2024-07-31 17:39:21,4358.0,131.0,303.0,79.0,669.0,17.0,634.0,1309.0,PySAL: Python Spatial Analysis Library Meta-Package.,79.0,32,True,2024-07-30 17:42:50.000,24.07,41.0,pysal,conda-forge/pysal,,,,49983.0,1679.0,1630.0,https://pypi.org/project/pysal,2024-07-30 17:42:53.000,49.0,38579.0,https://anaconda.org/conda-forge/pysal,2024-07-30 21:31:48.610,570233.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +237,pyopencl,inducer/pyopencl,others,,https://github.com/inducer/pyopencl,https://github.com/inducer/pyopencl,MIT,2011-04-06 02:51:33.000,2024-08-30 16:16:32.000000,2024-08-30 16:16:31,3374.0,29.0,239.0,49.0,404.0,74.0,277.0,1052.0,"OpenCL integration for Python, plus shiny features.",96.0,32,True,2024-06-25 02:02:14.000,2024.2.7,102.0,pyopencl,conda-forge/pyopencl,,,,82675.0,2189.0,2017.0,https://pypi.org/project/pyopencl,2024-06-25 02:02:14.000,172.0,58208.0,https://anaconda.org/conda-forge/pyopencl,2024-06-26 04:14:07.618,1247842.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +238,Satpy,pytroll/satpy,geospatial-data,,https://github.com/pytroll/satpy,https://github.com/pytroll/satpy,GPL-3.0,2016-02-09 20:29:43.000,2024-09-04 15:14:53.000000,2024-09-04 15:14:51,13939.0,294.0,290.0,34.0,1846.0,482.0,659.0,1048.0,Python package for earth-observing satellite data processing.,160.0,32,False,2024-08-15 13:27:18.000,0.51.0,96.0,satpy,conda-forge/satpy,,,,12195.0,167.0,139.0,https://pypi.org/project/satpy,2024-08-15 13:27:18.000,28.0,7947.0,https://anaconda.org/conda-forge/satpy,2024-08-15 19:19:25.115,216695.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +239,Hail,hail-is/hail,medical-data,,https://github.com/hail-is/hail,https://github.com/hail-is/hail,MIT,2015-10-27 20:55:42.000,2024-08-29 15:51:12.000000,2024-08-29 15:51:12,11555.0,51.0,241.0,57.0,12256.0,239.0,2210.0,965.0,Cloud-native genomic dataframes and batch computing.,95.0,32,True,2024-08-12 18:22:08.000,0.2.130.post1,154.0,hail,,,['spark'],,204253.0,174.0,140.0,https://pypi.org/project/hail,2024-08-08 16:40:33.000,34.0,204253.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +240,DIPY,dipy/dipy,medical-data,,https://github.com/dipy/dipy,https://github.com/dipy/dipy,,2010-02-06 11:43:08.000,2024-09-05 13:31:30.000000,2024-09-05 13:31:30,14374.0,304.0,434.0,54.0,2208.0,191.0,799.0,699.0,"DIPY is the paragon 3D/4D+ imaging library in Python. Contains generic methods for spatial normalization, signal..",163.0,32,False,2024-03-08 22:14:36.000,1.9.0,28.0,dipy,conda-forge/dipy,,,,40639.0,1329.0,1207.0,https://pypi.org/project/dipy,2024-03-08 22:14:36.000,122.0,30275.0,https://anaconda.org/conda-forge/dipy,2024-03-10 04:37:57.447,497504.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +241,datalad,datalad/datalad,others,,https://github.com/datalad/datalad,https://github.com/datalad/datalad,MIT,2013-11-01 19:40:08.000,2024-08-31 11:24:45.000000,2024-08-31 11:15:33,17267.0,65.0,111.0,28.0,3610.0,528.0,3407.0,522.0,"Keep code, data, containers under control with git and git-annex.",57.0,32,True,2024-08-08 02:59:23.000,1.1.3,119.0,datalad,conda-forge/datalad,,,,33415.0,511.0,416.0,https://pypi.org/project/datalad,2024-08-08 02:59:23.000,95.0,21819.0,https://anaconda.org/conda-forge/datalad,2024-08-08 08:36:45.951,591438.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +242,spleeter,deezer/spleeter,audio,,https://github.com/deezer/spleeter,https://github.com/deezer/spleeter,MIT,2019-09-26 15:40:46.000,2024-08-04 12:17:57.000000,2023-07-13 08:50:20,531.0,,2796.0,385.0,122.0,239.0,561.0,25593.0,Deezer source separation library including pretrained models.,19.0,31,False,2023-07-10 10:07:01.047,2.4.0,37.0,spleeter,conda-forge/spleeter,,['tensorflow'],3378448.0,76978.0,783.0,771.0,https://pypi.org/project/spleeter,2022-06-10 13:19:35.000,12.0,18147.0,https://anaconda.org/conda-forge/spleeter,2023-06-16 16:18:57.741,91078.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +243,vit-pytorch,lucidrains/vit-pytorch,image,,https://github.com/lucidrains/vit-pytorch,https://github.com/lucidrains/vit-pytorch,MIT,2020-10-03 22:47:24.000,2024-08-28 19:22:10.000000,2024-08-28 19:21:31,321.0,14.0,2941.0,146.0,54.0,132.0,139.0,19523.0,"Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single..",21.0,31,True,2024-08-28 19:22:10.000,1.7.12,202.0,vit-pytorch,,,['pytorch'],,18371.0,536.0,523.0,https://pypi.org/project/vit-pytorch,2024-08-28 19:22:10.000,13.0,18371.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +244,Magenta,magenta/magenta,audio,,https://github.com/magenta/magenta,https://github.com/magenta/magenta,Apache-2.0,2016-05-05 20:10:40.000,2024-08-01 02:26:10.000000,2024-08-01 02:26:04,1422.0,1.0,3735.0,754.0,1140.0,413.0,589.0,19076.0,Magenta: Music and Art Generation with Machine Intelligence.,155.0,31,True,2023-12-02 01:16:14.308,0.1.0,68.0,magenta,,,['tensorflow'],,4242.0,532.0,527.0,https://pypi.org/project/magenta,2022-08-01 18:23:00.243,5.0,4242.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +245,Qlib,microsoft/qlib,financial-data,,https://github.com/microsoft/qlib,https://github.com/microsoft/qlib,MIT,2020-08-14 06:46:00.000,2024-09-03 10:18:37.000000,2024-08-30 09:01:55,1994.0,16.0,2583.0,295.0,937.0,238.0,690.0,15130.0,"Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and..",134.0,31,True,2024-05-24 08:18:55.000,0.9.5,34.0,pyqlib,,,['pytorch'],676.0,1940.0,22.0,21.0,https://pypi.org/project/pyqlib,2024-05-24 08:18:55.000,1.0,1926.0,,,,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +246,PaddleHub,PaddlePaddle/PaddleHub,others,,https://github.com/PaddlePaddle/PaddleHub,https://github.com/PaddlePaddle/PaddleHub,Apache-2.0,2018-12-21 06:00:48.000,2024-08-07 03:17:23.000000,2024-08-07 03:17:23,2667.0,2.0,2074.0,182.0,1006.0,574.0,726.0,12664.0,"Awesome pre-trained models toolkit based on PaddlePaddle. (400+ models including Image, Text, Audio, Video and Cross-..",70.0,31,True,2023-09-20 10:33:08.000,2.4.0,50.0,paddlehub,,,['paddle'],748.0,5698.0,1714.0,1707.0,https://pypi.org/project/paddlehub,2023-09-20 10:33:08.000,7.0,5687.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +247,TFlearn,tflearn/tflearn,ml-frameworks,,https://github.com/tflearn/tflearn,https://github.com/tflearn/tflearn,MIT,2016-03-31 12:05:53.000,2024-05-06 11:34:20.000000,2020-11-30 04:34:51,613.0,,2410.0,457.0,261.0,577.0,364.0,9618.0,Deep learning library featuring a higher-level API for TensorFlow.,145.0,31,False,2020-11-11 19:26:11.000,0.5.0,8.0,tflearn,,,['tensorflow'],,5353.0,5007.0,4993.0,https://pypi.org/project/tflearn,2020-11-11 19:13:47.000,14.0,5353.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +248,fuzzywuzzy,seatgeek/fuzzywuzzy,nlp,,https://github.com/seatgeek/fuzzywuzzy,https://github.com/seatgeek/fuzzywuzzy,GPL-2.0,2011-07-08 19:32:34.000,2023-06-16 13:22:53.603000,2021-09-09 20:54:41,384.0,,878.0,259.0,148.0,107.0,104.0,9206.0,Fuzzy String Matching in Python.,70.0,31,False,2020-02-13 22:14:12.000,0.18.0,27.0,fuzzywuzzy,conda-forge/fuzzywuzzy,,,,7888163.0,1192.0,21.0,https://pypi.org/project/fuzzywuzzy,2020-02-13 21:06:25.000,1171.0,7882501.0,https://anaconda.org/conda-forge/fuzzywuzzy,2023-06-16 13:22:53.603,554888.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +249,AutoKeras,keras-team/autokeras,hyperopt,,https://github.com/keras-team/autokeras,https://github.com/keras-team/autokeras,Apache-2.0,2017-11-19 23:18:20.000,2024-03-20 22:02:13.000000,2024-03-20 22:02:12,1391.0,,1399.0,302.0,894.0,142.0,759.0,9109.0,AutoML library for deep learning.,143.0,31,True,2024-03-20 21:40:33.000,2.0.0,59.0,autokeras,,,['tensorflow'],18712.0,48635.0,741.0,728.0,https://pypi.org/project/autokeras,2024-03-20 21:40:33.000,13.0,48407.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +250,imageai,OlafenwaMoses/ImageAI,image,,https://github.com/OlafenwaMoses/ImageAI,https://github.com/OlafenwaMoses/ImageAI,MIT,2018-03-19 23:12:33.000,2024-08-03 09:45:20.000000,2024-02-20 22:38:05,385.0,,2158.0,287.0,98.0,311.0,446.0,8549.0,A python library built to empower developers to build applications and systems with self-contained Computer Vision..,19.0,31,True,2023-01-02 17:10:24.749,3.0.3,13.0,imageai,conda-forge/imageai,,,937470.0,18226.0,1677.0,1658.0,https://pypi.org/project/imageai,2023-01-02 17:10:24.749,19.0,5897.0,https://anaconda.org/conda-forge/imageai,2023-06-16 19:21:01.568,7787.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +251,Apex,NVIDIA/apex,gpu-utilities,,https://github.com/NVIDIA/apex,https://github.com/NVIDIA/apex,BSD-3-Clause,2018-04-23 16:28:52.000,2024-08-30 11:22:48.000000,2024-08-30 11:22:47,1185.0,11.0,1375.0,101.0,656.0,722.0,526.0,8285.0,A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch.,129.0,31,True,,,4.0,,conda-forge/nvidia-apex,,['pytorch'],,6374.0,2680.0,2680.0,,,,,https://anaconda.org/conda-forge/nvidia-apex,2024-05-17 03:07:31.985,299613.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +252,auto-sklearn,automl/auto-sklearn,hyperopt,,https://github.com/automl/auto-sklearn,https://github.com/automl/auto-sklearn,BSD-3-Clause,2015-07-02 15:38:10.000,2024-09-03 14:08:17.000000,2023-04-18 11:08:13,2759.0,,1269.0,215.0,719.0,196.0,829.0,7534.0,Automated Machine Learning with scikit-learn.,88.0,31,False,2023-02-13 12:35:21.000,0.15.0,42.0,auto-sklearn,conda-forge/auto-sklearn,,['sklearn'],59.0,13691.0,634.0,600.0,https://pypi.org/project/auto-sklearn,2022-09-20 10:32:07.471,34.0,13084.0,https://anaconda.org/conda-forge/auto-sklearn,2023-06-16 19:25:30.278,24920.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +253,DeepPavlov,deepmipt/DeepPavlov,nlp,,https://github.com/deeppavlov/DeepPavlov,https://github.com/deeppavlov/DeepPavlov,Apache-2.0,2017-11-17 14:35:29.000,2024-08-12 17:22:54.000000,2024-08-12 17:08:04,2710.0,2.0,1140.0,208.0,1051.0,24.0,615.0,6646.0,An open source library for deep learning end-to-end dialog systems and chatbots.,77.0,31,True,2024-08-12 17:22:54.000,1.7.0,64.0,deeppavlov,,,['tensorflow'],,10217.0,409.0,405.0,https://pypi.org/project/deeppavlov,2024-08-12 17:22:54.000,4.0,10217.0,,,,2.0,,,,,,,,deeppavlov/DeepPavlov,,,,,,,,,,,,,,,,, +254,skorch,skorch-dev/skorch,ml-frameworks,,https://github.com/skorch-dev/skorch,https://github.com/skorch-dev/skorch,BSD-3-Clause,2017-07-18 00:13:54.000,2024-09-03 12:07:36.000000,2024-05-30 14:31:49,1091.0,,385.0,81.0,538.0,62.0,457.0,5758.0,A scikit-learn compatible neural network library that wraps PyTorch.,62.0,31,True,2024-05-27 15:25:43.000,1.0.0,20.0,skorch,conda-forge/skorch,,"['pytorch', 'sklearn']",,160247.0,1459.0,1374.0,https://pypi.org/project/skorch,2024-05-27 15:23:17.000,85.0,143885.0,https://anaconda.org/conda-forge/skorch,2024-05-30 08:55:05.943,785413.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +255,torchdiffeq,rtqichen/torchdiffeq,pytorch-utils,,https://github.com/rtqichen/torchdiffeq,https://github.com/rtqichen/torchdiffeq,MIT,2018-11-14 17:51:25.000,2024-05-29 15:01:39.000000,2023-10-19 19:24:51,248.0,,910.0,125.0,38.0,74.0,147.0,5452.0,Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.,21.0,31,True,2024-05-29 15:01:39.000,0.2.4,8.0,torchdiffeq,conda-forge/torchdiffeq,,['pytorch'],,823505.0,3865.0,3765.0,https://pypi.org/project/torchdiffeq,2024-05-29 15:01:39.000,100.0,823175.0,https://anaconda.org/conda-forge/torchdiffeq,2023-06-16 19:19:05.182,17187.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +256,River,online-ml/river,others,,https://github.com/online-ml/river,https://github.com/online-ml/river,BSD-3-Clause,2019-01-24 15:18:26.000,2024-09-04 06:56:44.000000,2024-09-04 06:53:27,3906.0,31.0,537.0,81.0,602.0,114.0,494.0,4980.0,Online machine learning in Python.,118.0,31,True,2024-07-09 19:24:30.000,0.21.2,22.0,river,conda-forge/river,,,,41668.0,602.0,549.0,https://pypi.org/project/river,2024-07-09 19:24:30.000,53.0,39812.0,https://anaconda.org/conda-forge/river,2023-10-06 14:40:00.791,76097.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +257,imutils,PyImageSearch/imutils,image,,https://github.com/PyImageSearch/imutils,https://github.com/PyImageSearch/imutils,MIT,2015-01-11 20:05:39.000,2024-06-24 13:34:47.000000,2022-01-27 13:24:16,139.0,,1026.0,152.0,116.0,162.0,79.0,4524.0,"A series of convenience functions to make basic image processing operations such as translation, rotation, resizing,..",21.0,31,False,2021-01-15 10:53:17.000,0.5.4,29.0,imutils,conda-forge/imutils,,,,1294592.0,45933.0,45505.0,https://pypi.org/project/imutils,2021-01-15 10:53:17.000,428.0,1290853.0,https://anaconda.org/conda-forge/imutils,2023-10-27 09:12:56.985,186951.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +258,hnswlib,nmslib/hnswlib,nn-search,,https://github.com/nmslib/hnswlib,https://github.com/nmslib/hnswlib,Apache-2.0,2017-07-06 13:08:46.000,2024-08-11 18:38:37.000000,2024-06-17 19:23:44,491.0,1.0,619.0,64.0,223.0,223.0,162.0,4247.0,Header-only C++/python library for fast approximate nearest neighbors.,72.0,31,True,2023-12-03 04:16:17.000,0.8.0,11.0,hnswlib,conda-forge/hnswlib,,,,862544.0,7033.0,6899.0,https://pypi.org/project/hnswlib,2023-12-03 04:16:17.000,134.0,857596.0,https://anaconda.org/conda-forge/hnswlib,2023-09-27 14:20:16.958,222693.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +259,ta,bukosabino/ta,financial-data,,https://github.com/bukosabino/ta,https://github.com/bukosabino/ta,MIT,2018-01-02 18:08:48.000,2024-07-17 04:40:56.000000,2023-11-02 13:49:44,662.0,,863.0,149.0,131.0,136.0,104.0,4233.0,Technical Analysis Library using Pandas and Numpy.,34.0,31,True,2023-11-02 13:53:35.000,0.11.0,56.0,ta,conda-forge/ta,,,,160562.0,4081.0,3978.0,https://pypi.org/project/ta,2023-11-02 13:53:35.000,103.0,159891.0,https://anaconda.org/conda-forge/ta,2023-11-02 22:03:30.766,28880.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +260,sacred,IDSIA/sacred,ml-experiments,,https://github.com/IDSIA/sacred,https://github.com/IDSIA/sacred,MIT,2014-03-31 18:05:29.000,2024-08-26 09:23:15.000000,2024-08-26 09:20:38,1348.0,4.0,380.0,68.0,371.0,102.0,460.0,4207.0,"Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.",105.0,31,True,2024-08-26 09:23:15.000,0.8.6,30.0,sacred,conda-forge/sacred,,,,30972.0,3218.0,3158.0,https://pypi.org/project/sacred,2024-08-26 09:23:15.000,60.0,30786.0,https://anaconda.org/conda-forge/sacred,2023-11-28 14:54:27.704,6343.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +261,cuML,rapidsai/cuml,gpu-utilities,,https://github.com/rapidsai/cuml,https://github.com/rapidsai/cuml,Apache-2.0,2018-10-11 15:45:35.000,2024-09-05 14:47:53.000000,2024-09-04 15:02:56,15522.0,68.0,525.0,72.0,3599.0,888.0,1600.0,4139.0,cuML - RAPIDS Machine Learning Library.,177.0,31,True,2024-08-08 02:09:42.000,24.08.00,41.0,cuml,,,,,2782.0,14.0,,https://pypi.org/project/cuml,2020-06-01 20:09:10.000,14.0,2782.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +262,nevergrad,facebookresearch/nevergrad,hyperopt,,https://github.com/facebookresearch/nevergrad,https://github.com/facebookresearch/nevergrad,MIT,2018-11-21 00:33:17.000,2024-09-03 16:41:09.000000,2024-08-28 11:41:45,1101.0,9.0,352.0,58.0,1365.0,133.0,175.0,3924.0,A Python toolbox for performing gradient-free optimization.,56.0,31,True,2024-08-16 08:31:34.000,1.0.4,49.0,nevergrad,conda-forge/nevergrad,,,,148444.0,799.0,741.0,https://pypi.org/project/nevergrad,2024-08-16 08:31:34.000,58.0,147423.0,https://anaconda.org/conda-forge/nevergrad,2024-01-09 16:02:07.312,53101.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +263,dyNET,clab/dynet,ml-frameworks,,https://github.com/clab/dynet,https://github.com/clab/dynet,Apache-2.0,2015-02-08 23:09:21.000,2023-12-01 17:10:01.000000,2023-11-08 12:40:01,3273.0,,704.0,184.0,737.0,277.0,669.0,3416.0,DyNet: The Dynamic Neural Network Toolkit.,160.0,31,True,2020-10-21 14:31:01.000,2.1.2,24.0,dyNET,,,,16929.0,248386.0,281.0,263.0,https://pypi.org/project/dyNET,2020-10-21 14:31:01.000,18.0,248208.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +264,filterpy,rlabbe/filterpy,probabilistics,,https://github.com/rlabbe/filterpy,https://github.com/rlabbe/filterpy,MIT,2014-07-15 02:15:19.000,2024-02-07 10:05:31.000000,2022-08-22 18:21:12,586.0,,616.0,76.0,78.0,73.0,162.0,3278.0,"Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman..",43.0,31,False,2021-12-15 15:49:27.374,0.0.13,49.0,filterpy,conda-forge/filterpy,,,,1773263.0,7033.0,6917.0,https://pypi.org/project/filterpy,2021-12-15 15:49:27.374,116.0,1770325.0,https://anaconda.org/conda-forge/filterpy,2023-06-16 13:24:39.196,255648.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +265,Determined,determined-ai/determined,ml-frameworks,,https://github.com/determined-ai/determined,https://github.com/determined-ai/determined,Apache-2.0,2020-04-07 16:12:29.000,2024-09-05 08:13:29.000000,2024-09-04 19:50:53,8153.0,328.0,347.0,83.0,9500.0,108.0,345.0,2980.0,"Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning,..",118.0,31,True,2024-08-23 21:25:59.000,0.36.0,584.0,determined,,https://docs.determined.ai,"['pytorch', 'tensorflow']",9621.0,30118.0,4.0,,https://pypi.org/project/determined,2024-08-23 21:49:24.000,4.0,29918.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +266,NeuralForecast,Nixtla/neuralforecast,time-series-data,,https://github.com/Nixtla/neuralforecast,https://github.com/Nixtla/neuralforecast,Apache-2.0,2021-04-26 00:15:19.000,2024-09-04 18:46:25.000000,2024-09-02 16:21:25,1179.0,30.0,332.0,35.0,519.0,111.0,423.0,2913.0,Scalable and user friendly neural forecasting algorithms.,48.0,31,True,2024-07-30 18:29:38.000,1.7.4,25.0,neuralforecast,conda-forge/neuralforecast,,,,39647.0,211.0,195.0,https://pypi.org/project/neuralforecast,2024-07-30 18:29:38.000,16.0,38936.0,https://anaconda.org/conda-forge/neuralforecast,2024-07-31 00:28:02.817,21346.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +267,bt,pmorissette/bt,financial-data,,https://github.com/pmorissette/bt,https://github.com/pmorissette/bt,MIT,2014-06-19 16:06:28.000,2024-09-01 16:40:50.000000,2024-08-06 16:26:17,551.0,30.0,412.0,88.0,115.0,77.0,264.0,2163.0,bt - flexible backtesting for Python.,34.0,31,True,2024-08-06 13:46:05.000,1.1.0,28.0,bt,conda-forge/bt,,,,8205.0,1631.0,1621.0,https://pypi.org/project/bt,2024-08-06 00:08:14.000,10.0,7213.0,https://anaconda.org/conda-forge/bt,2024-08-06 16:21:23.081,40675.0,1.0,,,,,,4.0,,,,,,,,,,,,,,,,,,, +268,evaluate,huggingface/evaluate,interpretability,,https://github.com/huggingface/evaluate,https://github.com/huggingface/evaluate,Apache-2.0,2022-03-30 15:08:26.000,2024-08-14 10:44:50.000000,2024-06-10 10:21:50,944.0,1.0,243.0,47.0,335.0,206.0,134.0,1948.0,Evaluate: A library for easily evaluating machine learning models and datasets.,128.0,31,True,2024-04-30 09:45:36.000,0.4.2,15.0,evaluate,,,,,2226920.0,12436.0,12040.0,https://pypi.org/project/evaluate,2024-04-30 09:44:17.000,396.0,2226920.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +269,lets-plot,JetBrains/lets-plot,data-viz,,https://github.com/JetBrains/lets-plot,https://github.com/JetBrains/lets-plot,MIT,2019-03-20 16:13:03.000,2024-09-04 23:29:53.000000,2024-09-04 20:43:41,4285.0,167.0,49.0,171.0,565.0,138.0,451.0,1540.0,Multiplatform plotting library based on the Grammar of Graphics.,21.0,31,True,2024-08-21 16:52:52.000,4.4.1,78.0,lets-plot,,,,931.0,18874.0,132.0,119.0,https://pypi.org/project/lets-plot,2024-08-21 16:33:28.000,13.0,18858.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +270,pyjanitor,pyjanitor-devs/pyjanitor,others,,https://github.com/pyjanitor-devs/pyjanitor,https://github.com/pyjanitor-devs/pyjanitor,MIT,2018-03-04 22:43:33.000,2024-09-03 12:01:44.000000,2024-08-20 20:52:54,1593.0,31.0,165.0,18.0,830.0,111.0,450.0,1341.0,Clean APIs for data cleaning. Python implementation of R package Janitor.,108.0,31,True,2024-08-09 10:45:17.000,0.28.1,62.0,pyjanitor,conda-forge/pyjanitor,,,,86801.0,702.0,673.0,https://pypi.org/project/pyjanitor,2024-08-09 10:45:12.000,29.0,82782.0,https://anaconda.org/conda-forge/pyjanitor,2024-08-09 15:37:31.887,208995.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +271,arch,bashtage/arch,financial-data,,https://github.com/bashtage/arch,https://github.com/bashtage/arch,,2014-08-29 15:41:28.000,2024-08-29 09:42:50.000000,2024-07-27 04:51:19,1133.0,4.0,245.0,48.0,533.0,31.0,185.0,1315.0,ARCH models in Python.,35.0,31,False,2024-04-16 17:35:41.000,7.0.0,47.0,arch,conda-forge/arch-py,,,,503094.0,1978.0,1874.0,https://pypi.org/project/arch,2024-04-16 17:35:41.000,104.0,495604.0,https://anaconda.org/conda-forge/arch-py,2024-05-17 19:52:40.969,382035.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +272,scikit-survival,sebp/scikit-survival,sklearn-utils,,https://github.com/sebp/scikit-survival,https://github.com/sebp/scikit-survival,GPL-3.0,2016-12-26 22:15:53.000,2024-08-18 09:36:59.000000,2024-08-18 09:36:04,1138.0,27.0,211.0,23.0,148.0,25.0,198.0,1111.0,Survival analysis built on top of scikit-learn.,21.0,31,False,2024-06-30 09:36:26.000,0.23.0,29.0,scikit-survival,conda-forge/scikit-survival,,['sklearn'],,111751.0,609.0,576.0,https://pypi.org/project/scikit-survival,2024-06-30 09:36:26.000,33.0,107695.0,https://anaconda.org/conda-forge/scikit-survival,2024-06-30 11:16:56.800,137930.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +273,hvPlot,holoviz/hvplot,data-viz,,https://github.com/holoviz/hvplot,https://github.com/holoviz/hvplot,BSD-3-Clause,2018-03-19 14:22:41.000,2024-08-30 00:04:01.000000,2024-08-29 05:54:49,704.0,19.0,104.0,25.0,567.0,358.0,438.0,1067.0,"A high-level plotting API for pandas, dask, xarray, and networkx built on HoloViews.",47.0,31,True,2024-05-07 03:58:11.000,0.10.0,71.0,hvplot,conda-forge/hvplot,,,,245729.0,5883.0,5697.0,https://pypi.org/project/hvplot,2024-07-23 13:19:56.000,186.0,233404.0,https://anaconda.org/conda-forge/hvplot,2024-05-07 04:39:01.018,628581.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +274,mpi4py,mpi4py/mpi4py,distributed-ml,,https://github.com/mpi4py/mpi4py,https://github.com/mpi4py/mpi4py,BSD-3-Clause,2013-09-05 14:44:25.000,2024-09-04 08:05:36.172000,2024-08-31 14:58:16,3183.0,44.0,118.0,17.0,305.0,6.0,164.0,784.0,Python bindings for MPI.,27.0,31,True,2024-07-28 09:41:14.000,4.0.0,29.0,mpi4py,conda-forge/mpi4py,,,26290.0,955633.0,728.0,,https://pypi.org/project/mpi4py,2024-07-28 09:41:14.000,728.0,894177.0,https://anaconda.org/conda-forge/mpi4py,2024-09-04 08:05:36.172,2863772.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +275,tensorflow-upstream,ROCmSoftwarePlatform/tensorflow-upstream,ml-frameworks,,https://github.com/ROCm/tensorflow-upstream,https://github.com/ROCm/tensorflow-upstream,Apache-2.0,2018-04-09 21:24:50.000,2024-09-05 13:34:50.000000,2024-08-27 04:32:10,172141.0,2156.0,93.0,51.0,2270.0,90.0,286.0,685.0,TensorFlow ROCm port.,4682.0,31,True,2022-12-06 16:42:53.965,2.9.4,100.0,tensorflow-rocm,,,['tensorflow'],23.0,3440.0,9.0,,https://pypi.org/project/tensorflow-rocm,2024-01-10 14:33:03.000,9.0,3440.0,,,,3.0,,,,,,,,ROCm/tensorflow-upstream,,,,,,,,,,,,,,,,, +276,Cython BLIS,explosion/cython-blis,others,,https://github.com/explosion/cython-blis,https://github.com/explosion/cython-blis,BSD-3-Clause,2017-10-15 09:56:16.000,2024-07-27 07:23:34.000000,2024-07-25 15:02:21,587.0,17.0,38.0,11.0,75.0,10.0,26.0,216.0,Fast matrix-multiplication as a self-contained Python library no system dependencies!.,14.0,31,False,2024-07-27 07:23:34.000,1.0.0,48.0,blis,conda-forge/cython-blis,,,55.0,10275552.0,48104.0,48004.0,https://pypi.org/project/blis,2024-07-27 07:23:34.000,100.0,10228547.0,https://anaconda.org/conda-forge/cython-blis,2023-10-01 08:59:57.840,2256242.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +277,FinRL,AI4Finance-Foundation/FinRL,reinforcement-learning,,https://github.com/AI4Finance-Foundation/FinRL,https://github.com/AI4Finance-Foundation/FinRL,MIT,2020-07-26 13:18:16.000,2024-09-04 00:44:02.000000,2024-09-04 00:43:59,2959.0,23.0,2322.0,201.0,467.0,243.0,475.0,9606.0,FinRL: Financial Reinforcement Learning.,116.0,30,True,2023-02-07 13:58:00.815,0.3.6,8.0,finrl,,,,,932.0,45.0,45.0,https://pypi.org/project/finrl,2022-01-08 13:58:14.000,,932.0,,,,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +278,Darts,unit8co/darts,time-series-data,,https://github.com/unit8co/darts,https://github.com/unit8co/darts,Apache-2.0,2018-09-13 15:17:28.000,2024-09-02 09:48:22.000000,2024-09-02 09:48:19,1237.0,33.0,847.0,59.0,1005.0,256.0,1291.0,7883.0,A python library for user-friendly forecasting and anomaly detection on time series.,124.0,30,True,2024-06-19 16:52:35.000,0.30.0,43.0,u8darts,conda-forge/u8darts-all,,,,54769.0,10.0,,https://pypi.org/project/u8darts,2024-06-19 16:52:35.000,10.0,53285.0,https://anaconda.org/conda-forge/u8darts-all,2024-06-21 14:16:42.811,56105.0,2.0,unit8/darts,https://hub.docker.com/r/unit8/darts,2024-04-17 11:31:17.149896,,629.0,,,,,,,,,,,,,,,,,,,, +279,pyfolio,quantopian/pyfolio,financial-data,,https://github.com/quantopian/pyfolio,https://github.com/quantopian/pyfolio,Apache-2.0,2015-06-01 15:31:39.000,2023-12-23 06:14:58.000000,2020-07-15 13:46:58,1184.0,,1760.0,303.0,294.0,161.0,267.0,5606.0,Portfolio and risk analytics in Python.,60.0,30,False,2019-04-15 15:00:21.000,0.9.2,22.0,pyfolio,conda-forge/pyfolio,,,,6769.0,1081.0,1067.0,https://pypi.org/project/pyfolio,2019-04-15 15:00:21.000,14.0,6595.0,https://anaconda.org/conda-forge/pyfolio,2023-06-16 16:07:59.111,13784.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +280,pandas-ta,twopirllc/pandas-ta,probabilistics,,https://github.com/twopirllc/pandas-ta,https://github.com/twopirllc/pandas-ta,MIT,2019-02-19 16:41:09.000,2024-07-28 06:06:31.000000,2024-06-24 00:50:16,586.0,1.0,1001.0,105.0,242.0,107.0,474.0,5190.0,Technical Analysis Indicators - Pandas TA is an easy to use Python 3 Pandas Extension with 150+ Indicators.,45.0,30,True,2021-07-28 20:21:21.000,0.3.14,19.0,pandas-ta,conda-forge/pandas-ta,,['pandas'],,127922.0,4231.0,4120.0,https://pypi.org/project/pandas-ta,2021-07-28 20:51:17.000,111.0,127305.0,https://anaconda.org/conda-forge/pandas-ta,2023-06-16 19:27:34.124,21625.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +281,D-Tale,man-group/dtale,data-viz,,https://github.com/man-group/dtale,https://github.com/man-group/dtale,LGPL-2.1,2019-07-15 09:34:48.000,2024-09-05 15:41:25.000000,2024-09-05 15:41:25,810.0,14.0,394.0,76.0,296.0,62.0,526.0,4693.0,Visualizer for pandas data structures.,30.0,30,True,2024-07-01 21:22:49.000,3.13.1,184.0,dtale,conda-forge/dtale,,"['pandas', 'jupyter']",,44465.0,1242.0,1199.0,https://pypi.org/project/dtale,2024-06-28 19:21:46.000,43.0,38206.0,https://anaconda.org/conda-forge/dtale,2024-06-28 19:50:28.028,325508.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +282,gpustat,wookayin/gpustat,gpu-utilities,,https://github.com/wookayin/gpustat,https://github.com/wookayin/gpustat,MIT,2016-04-24 10:46:43.000,2024-08-08 18:40:13.000000,2024-01-12 14:48:30,249.0,,280.0,45.0,51.0,28.0,97.0,3998.0,A simple command-line utility for querying and monitoring GPU status.,17.0,30,True,2023-08-22 19:40:33.000,1.1.1,15.0,gpustat,conda-forge/gpustat,,,,580721.0,6054.0,5905.0,https://pypi.org/project/gpustat,2023-08-22 19:39:06.000,149.0,574377.0,https://anaconda.org/conda-forge/gpustat,2023-08-23 10:35:25.821,291851.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +283,pytorch-forecasting,jdb78/pytorch-forecasting,time-series-data,,https://github.com/jdb78/pytorch-forecasting,https://github.com/jdb78/pytorch-forecasting,MIT,2020-07-03 13:05:24.000,2024-09-05 11:02:25.000000,2024-09-05 11:02:25,1885.0,94.0,608.0,41.0,884.0,500.0,292.0,3848.0,Time series forecasting with PyTorch.,50.0,30,True,2023-04-10 19:57:38.490,1.0.0,34.0,pytorch-forecasting,conda-forge/pytorch-forecasting,,,,63446.0,20.0,,https://pypi.org/project/pytorch-forecasting,2023-04-10 19:57:38.490,20.0,62138.0,https://anaconda.org/conda-forge/pytorch-forecasting,2023-06-16 19:21:40.268,62792.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +284,Porcupine,Picovoice/Porcupine,audio,,https://github.com/Picovoice/porcupine,https://github.com/Picovoice/porcupine,Apache-2.0,2018-03-08 01:55:25.000,2024-08-30 16:06:25.000000,2024-08-30 16:04:57,1227.0,15.0,496.0,64.0,748.0,,545.0,3671.0,On-device wake word detection powered by deep learning.,38.0,30,True,2024-08-27 00:05:29.000,3.0.3,35.0,pvporcupine,,,,,10448.0,66.0,33.0,https://pypi.org/project/pvporcupine,2024-08-27 00:05:29.000,33.0,10448.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +285,implicit,benfred/implicit,recommender-systems,,https://github.com/benfred/implicit,https://github.com/benfred/implicit,MIT,2016-04-17 03:45:23.000,2024-08-23 13:53:47.619000,2023-11-21 21:15:59,435.0,,605.0,77.0,230.0,89.0,406.0,3522.0,Fast Python Collaborative Filtering for Implicit Feedback Datasets.,35.0,30,True,2023-09-29 21:07:11.000,0.7.2,47.0,implicit,conda-forge/implicit,,,1236.0,226782.0,1471.0,1442.0,https://pypi.org/project/implicit,2023-09-29 21:07:11.000,29.0,209645.0,https://anaconda.org/conda-forge/implicit,2024-08-23 13:53:47.619,820764.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +286,NMSLIB,nmslib/nmslib,nn-search,,https://github.com/nmslib/nmslib,https://github.com/nmslib/nmslib,Apache-2.0,2013-07-10 11:06:06.000,2024-07-09 22:20:22.000000,2024-06-23 04:04:02,1559.0,2.0,447.0,93.0,126.0,91.0,348.0,3371.0,Non-Metric Space Library (NMSLIB): An efficient similarity search library and a toolkit for evaluation of k-NN methods..,48.0,30,True,2021-02-03 16:40:09.000,2.1.1,32.0,nmslib,conda-forge/nmslib,,,,184645.0,1263.0,1200.0,https://pypi.org/project/nmslib,2021-02-03 00:02:08.000,63.0,181668.0,https://anaconda.org/conda-forge/nmslib,2023-09-26 10:22:21.295,139936.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +287,TextDistance,life4/textdistance,nlp,,https://github.com/life4/textdistance,https://github.com/life4/textdistance,MIT,2017-05-05 08:46:10.000,2024-09-03 08:03:11.000000,2024-09-03 08:03:10,413.0,7.0,248.0,64.0,55.0,9.0,,3349.0,"Compute distance between sequences. 30+ algorithms, pure python implementation, common interface, optional external..",17.0,30,True,2024-07-16 09:36:19.000,4.6.3,29.0,textdistance,conda-forge/textdistance,,,1022.0,856034.0,7077.0,6978.0,https://pypi.org/project/textdistance,2024-07-16 09:34:51.000,99.0,842735.0,https://anaconda.org/conda-forge/textdistance,2024-07-17 15:04:16.210,611217.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +288,pomegranate,jmschrei/pomegranate,probabilistics,,https://github.com/jmschrei/pomegranate,https://github.com/jmschrei/pomegranate,MIT,2014-11-24 18:36:58.000,2024-07-11 06:05:21.000000,2024-07-11 06:02:00,993.0,9.0,590.0,95.0,338.0,21.0,758.0,3341.0,"Fast, flexible and easy to use probabilistic modelling in Python.",75.0,30,True,2024-07-11 06:11:27.000,1.1.0,76.0,pomegranate,conda-forge/pomegranate,,,,16461.0,1207.0,1148.0,https://pypi.org/project/pomegranate,2024-07-11 06:05:21.000,59.0,13215.0,https://anaconda.org/conda-forge/pomegranate,2023-12-10 17:04:41.093,168832.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +289,vidgear,abhiTronix/vidgear,image,,https://github.com/abhiTronix/vidgear,https://github.com/abhiTronix/vidgear,Apache-2.0,2019-03-17 02:42:42.000,2024-08-11 08:09:18.000000,2024-06-22 17:36:10,1146.0,28.0,252.0,62.0,121.0,6.0,288.0,3324.0,A High-performance cross-platform Video Processing Python framework powerpacked with unique trailblazing features.,14.0,30,True,2024-06-22 19:12:02.000,0.3.3,23.0,vidgear,,,,1559.0,21886.0,614.0,599.0,https://pypi.org/project/vidgear,2024-06-22 19:12:02.000,15.0,21863.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +290,ImageHash,JohannesBuchner/imagehash,image,,https://github.com/JohannesBuchner/imagehash,https://github.com/JohannesBuchner/imagehash,BSD-2-Clause,2013-03-02 23:32:48.000,2024-06-20 07:03:41.000000,2024-06-20 07:03:30,339.0,4.0,328.0,66.0,76.0,15.0,123.0,3112.0,A Python Perceptual Image Hashing Module.,26.0,30,True,2022-09-28 08:48:24.658,4.3.1,20.0,ImageHash,conda-forge/imagehash,,,,1359050.0,14270.0,14034.0,https://pypi.org/project/ImageHash,2022-09-28 08:48:24.658,236.0,1354887.0,https://anaconda.org/conda-forge/imagehash,2023-06-16 13:23:10.041,391335.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +291,tslearn,tslearn-team/tslearn,time-series-data,,https://github.com/tslearn-team/tslearn,https://github.com/tslearn-team/tslearn,BSD-2-Clause,2017-05-04 13:08:13.000,2024-07-26 07:25:11.554000,2024-07-01 04:53:53,1639.0,2.0,336.0,59.0,194.0,135.0,196.0,2879.0,The machine learning toolkit for time series analysis in Python.,43.0,30,True,2023-12-12 14:39:23.000,0.6.3,100.0,tslearn,conda-forge/tslearn,,['sklearn'],,407474.0,1485.0,1406.0,https://pypi.org/project/tslearn,2023-12-12 14:39:23.000,79.0,380067.0,https://anaconda.org/conda-forge/tslearn,2024-07-26 07:25:11.554,1397799.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +292,Haiku,deepmind/dm-haiku,ml-frameworks,,https://github.com/google-deepmind/dm-haiku,https://github.com/google-deepmind/dm-haiku,Apache-2.0,2020-02-18 07:14:02.000,2024-08-30 13:27:59.000000,2024-08-30 13:27:55,984.0,4.0,232.0,38.0,541.0,75.0,175.0,2859.0,JAX-based neural network library.,82.0,30,True,2024-02-28 18:11:54.000,0.0.12,15.0,dm-haiku,conda-forge/dm-haiku,,,,196798.0,2209.0,2042.0,https://pypi.org/project/dm-haiku,2024-02-28 18:11:54.000,167.0,196310.0,https://anaconda.org/conda-forge/dm-haiku,2024-02-28 22:18:23.853,20988.0,3.0,,,,,,,,google-deepmind/dm-haiku,,,,,,,,,,,,,,,,, +293,Keras Tuner,keras-team/keras-tuner,hyperopt,,https://github.com/keras-team/keras-tuner,https://github.com/keras-team/keras-tuner,Apache-2.0,2019-06-06 22:38:21.000,2024-08-01 18:13:21.000000,2024-06-24 17:09:39,1087.0,1.0,392.0,64.0,496.0,218.0,273.0,2846.0,A Hyperparameter Tuning Library for Keras.,61.0,30,True,2024-03-04 19:41:39.000,1.4.7,35.0,keras-tuner,conda-forge/keras-tuner,,['tensorflow'],,327491.0,4413.0,4298.0,https://pypi.org/project/keras-tuner,2024-03-04 19:41:39.000,115.0,326455.0,https://anaconda.org/conda-forge/keras-tuner,2024-03-05 15:33:09.039,38337.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +294,category_encoders,scikit-learn-contrib/category_encoders,sklearn-utils,,https://github.com/scikit-learn-contrib/category_encoders,https://github.com/scikit-learn-contrib/category_encoders,BSD-3-Clause,2015-11-29 19:32:37.000,2024-04-09 11:39:30.000000,2024-04-09 11:39:30,957.0,,393.0,38.0,150.0,46.0,244.0,2396.0,A library of sklearn compatible categorical variable encoders.,70.0,30,True,2023-10-29 20:29:52.000,2.6.3,32.0,category_encoders,conda-forge/category_encoders,,['sklearn'],,1285177.0,2323.0,2059.0,https://pypi.org/project/category_encoders,2023-10-29 20:29:52.000,264.0,1277234.0,https://anaconda.org/conda-forge/category_encoders,2023-10-30 01:23:52.252,278010.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +295,pygraphistry,graphistry/pygraphistry,graph,,https://github.com/graphistry/pygraphistry,https://github.com/graphistry/pygraphistry,BSD-3-Clause,2015-06-02 20:28:42.000,2024-08-09 06:42:16.000000,2024-08-03 19:13:40,1565.0,62.0,206.0,50.0,265.0,171.0,161.0,2113.0,"PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated..",44.0,30,True,2024-08-03 18:57:36.000,0.34.3,180.0,graphistry,,,['jupyter'],,3865.0,123.0,117.0,https://pypi.org/project/graphistry,2024-08-03 18:57:36.000,6.0,3865.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +296,USearch,unum-cloud/usearch,nn-search,,https://github.com/unum-cloud/usearch,https://github.com/unum-cloud/usearch,Apache-2.0,2023-02-22 09:20:20.000,2024-09-03 02:40:06.000000,2024-08-28 19:04:32,1849.0,118.0,122.0,27.0,341.0,47.0,101.0,2100.0,"Fast Open-Source Search & Clustering engine for Vectors & Strings in C++, C, Python, JavaScript, Rust, Java,..",52.0,30,True,2024-08-28 20:01:05.000,2.15.1,123.0,usearch,,,,18208.0,113055.0,141.0,113.0,https://pypi.org/project/usearch,2024-08-28 20:01:05.000,14.0,103505.0,,,,2.0,unum/usearch,https://hub.docker.com/r/unum/usearch,2024-08-28 19:11:57.156669,1.0,111.0,,,,usearch,https://www.npmjs.com/package/usearch,2024-08-28 19:12:14.604,14.0,8332.0,,,,,,,,,,,, +297,equinox,patrick-kidger/equinox,jax-utils,,https://github.com/patrick-kidger/equinox,https://github.com/patrick-kidger/equinox,Apache-2.0,2021-07-29 02:21:39.000,2024-09-03 14:53:46.000000,2024-09-03 14:53:46,929.0,28.0,134.0,23.0,414.0,146.0,274.0,2021.0,Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/.,55.0,30,True,2024-08-18 19:11:57.000,0.11.5,49.0,equinox,,,['jax'],,92338.0,842.0,694.0,https://pypi.org/project/equinox,2024-08-18 19:11:57.000,148.0,92338.0,,,,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +298,tesserocr,sirfz/tesserocr,ocr,,https://github.com/sirfz/tesserocr,https://github.com/sirfz/tesserocr,MIT,2015-12-17 23:29:36.000,2024-08-26 20:21:57.000000,2024-08-26 17:26:56,210.0,1.0,254.0,56.0,76.0,50.0,229.0,1986.0,A Python wrapper for the tesseract-ocr API.,30.0,30,True,2024-08-26 20:21:57.000,2.7.1,22.0,tesserocr,conda-forge/tesserocr,,,421.0,85210.0,1110.0,1074.0,https://pypi.org/project/tesserocr,2024-08-26 20:21:57.000,36.0,81784.0,https://anaconda.org/conda-forge/tesserocr,2024-07-30 13:52:35.216,171127.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +299,torchrec,pytorch/torchrec,recommender-systems,,https://github.com/pytorch/torchrec,https://github.com/pytorch/torchrec,BSD-3-Clause,2021-07-12 23:15:48.000,2024-09-05 11:34:59.000000,2024-09-05 04:09:34,2067.0,227.0,394.0,30.0,2196.0,300.0,114.0,1855.0,Pytorch domain library for recommendation systems.,260.0,30,True,2024-07-23 18:00:18.000,0.8.0,77.0,torchrec-nightly-cpu,,,,,715.0,129.0,129.0,https://pypi.org/project/torchrec-nightly-cpu,2022-05-12 18:55:21.000,,715.0,,,,1.0,,,,,,,,,,,,,,,,,,,,,,,,, +300,GPflow,GPflow/GPflow,probabilistics,,https://github.com/GPflow/GPflow,https://github.com/GPflow/GPflow,Apache-2.0,2016-01-14 11:29:24.000,2024-07-29 11:38:56.000000,2024-06-14 08:51:32,2450.0,2.0,435.0,75.0,1269.0,154.0,682.0,1829.0,Gaussian processes in TensorFlow.,84.0,30,True,2024-06-17 13:05:05.000,2.9.2,50.0,gpflow,conda-forge/gpflow,,['tensorflow'],,76246.0,719.0,684.0,https://pypi.org/project/gpflow,2024-06-17 13:05:05.000,35.0,75195.0,https://anaconda.org/conda-forge/gpflow,2024-06-26 16:24:01.852,32602.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +301,pyLDAvis,bmabey/pyLDAvis,interpretability,,https://github.com/bmabey/pyLDAvis,https://github.com/bmabey/pyLDAvis,BSD-3-Clause,2015-04-09 22:48:03.000,2024-07-09 19:44:03.000000,2024-04-29 20:57:51,290.0,,359.0,47.0,79.0,78.0,113.0,1802.0,Python library for interactive topic model visualization. Port of the R LDAvis package.,42.0,30,True,2023-04-23 23:55:02.142,3.4.1,26.0,pyldavis,conda-forge/pyldavis,,['jupyter'],,129880.0,6503.0,6400.0,https://pypi.org/project/pyldavis,2023-04-23 23:55:02.142,103.0,128744.0,https://anaconda.org/conda-forge/pyldavis,2023-06-16 16:08:55.034,85201.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +302,ViZDoom,mwydmuch/ViZDoom,reinforcement-learning,,https://github.com/Farama-Foundation/ViZDoom,https://github.com/Farama-Foundation/ViZDoom,MIT,2015-06-26 18:38:23.000,2024-09-03 22:56:08.000000,2024-08-20 10:36:51,1828.0,23.0,376.0,50.0,129.0,38.0,426.0,1710.0,Reinforcement Learning environments based on the 1993 game Doom.,54.0,30,True,2024-08-20 10:48:59.000,1.2.4,30.0,vizdoom,,,,11920.0,2189.0,276.0,261.0,https://pypi.org/project/vizdoom,2024-08-20 10:48:59.000,15.0,2073.0,,,,1.0,,,,,,,,Farama-Foundation/ViZDoom,,,,,,,,,,,,,,,,, +303,emcee,dfm/emcee,probabilistics,,https://github.com/dfm/emcee,https://github.com/dfm/emcee,MIT,2011-11-07 16:17:08.000,2024-09-01 04:06:27.000000,2024-07-03 00:11:45,948.0,1.0,431.0,86.0,233.0,57.0,241.0,1455.0,The Python ensemble sampling toolkit for affine-invariant MCMC.,74.0,30,True,2024-04-19 10:03:17.000,3.1.6,27.0,emcee,conda-forge/emcee,,,,185581.0,3005.0,2580.0,https://pypi.org/project/emcee,2024-04-19 10:03:17.000,425.0,176456.0,https://anaconda.org/conda-forge/emcee,2024-04-22 14:43:59.507,355887.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +304,Model Analysis,tensorflow/model-analysis,interpretability,,https://github.com/tensorflow/model-analysis,https://github.com/tensorflow/model-analysis,Apache-2.0,2018-03-23 19:08:49.000,2024-08-30 01:04:00.000000,2024-08-30 01:03:59,1482.0,47.0,274.0,73.0,107.0,33.0,55.0,1254.0,Model analysis tools for TensorFlow.,57.0,30,True,2024-04-25 08:57:36.000,0.46.0,57.0,tensorflow-model-analysis,,,"['tensorflow', 'jupyter']",,214147.0,19.0,,https://pypi.org/project/tensorflow-model-analysis,2024-04-25 08:57:36.000,19.0,214147.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +305,Geomstats,geomstats/geomstats,ml-frameworks,,https://github.com/geomstats/geomstats,https://github.com/geomstats/geomstats,MIT,2017-10-25 00:44:57.000,2024-08-30 08:50:22.000000,2024-08-30 08:50:22,10764.0,80.0,235.0,38.0,1500.0,206.0,353.0,1200.0,Computations and statistics on manifolds with geometric structures.,92.0,30,True,2023-08-30 05:36:10.000,2.7.0,32.0,geomstats,conda-forge/geomstats,https://geomstats.github.io/,,,3275.0,123.0,120.0,https://pypi.org/project/geomstats,2023-08-30 05:33:32.000,3.0,3150.0,https://anaconda.org/conda-forge/geomstats,2023-08-30 16:59:06.279,3398.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +306,skforecast,JoaquinAmatRodrigo/skforecast,time-series-data,,https://github.com/JoaquinAmatRodrigo/skforecast,https://github.com/JoaquinAmatRodrigo/skforecast,BSD-3-Clause,2021-02-10 11:40:34.000,2024-09-05 15:01:49.000000,2024-08-13 21:16:30,3511.0,294.0,123.0,10.0,612.0,18.0,150.0,1069.0,Time series forecasting with machine learning models.,14.0,30,True,2024-08-01 13:18:23.000,0.13.0,28.0,skforecast,,,['sklearn'],,79250.0,335.0,320.0,https://pypi.org/project/skforecast,2024-08-01 12:24:50.000,15.0,79250.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +307,patsy,pydata/patsy,probabilistics,,https://github.com/pydata/patsy,https://github.com/pydata/patsy,BSD-2-Clause,2012-07-10 12:30:06.000,2024-06-14 11:34:14.000000,2024-01-04 18:54:38,558.0,,103.0,33.0,61.0,72.0,82.0,941.0,Describing statistical models in Python using symbolic formulas.,19.0,30,True,2024-01-04 18:58:03.000,0.5.6,13.0,patsy,conda-forge/patsy,,,,15203931.0,104248.0,103732.0,https://pypi.org/project/patsy,2024-01-04 18:55:57.000,516.0,14873650.0,https://anaconda.org/conda-forge/patsy,2024-01-05 15:46:09.327,11890133.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +308,SALib,SALib/SALib,probabilistics,,https://github.com/SALib/SALib,https://github.com/SALib/SALib,MIT,2013-05-30 13:38:10.000,2024-08-19 20:16:48.120000,2024-07-14 11:03:35,1955.0,5.0,234.0,18.0,297.0,53.0,282.0,866.0,"Sensitivity Analysis Library in Python. Contains Sobol, Morris, FAST, and other methods.",46.0,30,True,2024-08-19 16:35:23.000,1.5.1,49.0,salib,conda-forge/salib,,,,184587.0,1361.0,1235.0,https://pypi.org/project/salib,2024-08-19 16:35:23.000,126.0,180804.0,https://anaconda.org/conda-forge/salib,2024-08-19 20:16:48.120,177807.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +309,mahotas,luispedro/mahotas,image,,https://github.com/luispedro/mahotas,https://github.com/luispedro/mahotas,MIT,2010-01-31 00:13:06.000,2024-07-18 20:23:32.152000,2024-07-17 19:01:14,1326.0,15.0,149.0,50.0,59.0,21.0,70.0,838.0,Computer Vision in Python.,35.0,30,True,2024-07-17 21:10:14.000,1.4.18,63.0,mahotas,conda-forge/mahotas,,,,31303.0,1399.0,1337.0,https://pypi.org/project/mahotas,2024-07-17 21:10:14.000,62.0,21808.0,https://anaconda.org/conda-forge/mahotas,2024-07-18 20:23:32.152,484249.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +310,snowballstemmer,snowballstem/snowball,nlp,,https://github.com/snowballstem/snowball,https://github.com/snowballstem/snowball,BSD-3-Clause,2013-02-23 07:17:42.000,2024-09-02 00:21:47.000000,2024-09-02 00:21:43,1083.0,10.0,174.0,35.0,117.0,27.0,62.0,748.0,Snowball compiler and stemming algorithms.,34.0,30,True,2021-11-16 18:38:34.000,2.2.0,10.0,snowballstemmer,conda-forge/snowballstemmer,,,,20424635.0,447.0,9.0,https://pypi.org/project/snowballstemmer,2021-11-16 18:38:34.000,438.0,20336349.0,https://anaconda.org/conda-forge/snowballstemmer,2023-06-16 13:16:49.834,8563836.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +311,TensorFlow I/O,tensorflow/io,tensorflow-utils,,https://github.com/tensorflow/io,https://github.com/tensorflow/io,Apache-2.0,2018-11-09 22:44:05.000,2024-09-03 19:40:26.000000,2024-07-01 21:47:36,1690.0,4.0,283.0,42.0,1410.0,290.0,371.0,697.0,"Dataset, streaming, and file system extensions maintained by TensorFlow SIG-IO.",109.0,30,True,2024-07-01 23:45:56.000,0.37.1,45.0,tensorflow-io,,,['tensorflow'],,1389153.0,61.0,,https://pypi.org/project/tensorflow-io,2024-07-01 23:43:17.000,61.0,1389153.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +312,Neptune.ai,neptune-ai/neptune-client,ml-experiments,,https://github.com/neptune-ai/neptune-client,https://github.com/neptune-ai/neptune-client,Apache-2.0,2019-02-11 11:25:57.000,2024-09-02 14:17:03.000000,2024-08-02 08:19:12,2094.0,18.0,63.0,19.0,1623.0,29.0,214.0,572.0,The experiment tracker for foundation model training.,54.0,30,True,2024-08-20 12:56:39.000,1.11.1,209.0,neptune-client,conda-forge/neptune-client,,,,446086.0,661.0,584.0,https://pypi.org/project/neptune-client,2024-08-20 12:56:39.000,77.0,440855.0,https://anaconda.org/conda-forge/neptune-client,2024-08-20 14:58:11.790,272059.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +313,audioread,beetbox/audioread,audio,,https://github.com/beetbox/audioread,https://github.com/beetbox/audioread,MIT,2011-11-08 19:53:18.000,2024-09-03 10:05:52.331000,2023-12-15 12:50:52,282.0,,107.0,25.0,53.0,37.0,57.0,482.0,cross-library (GStreamer + Core Audio + MAD + FFmpeg) audio decoding for Python.,25.0,30,True,2023-09-27 19:27:51.000,3.0.1,27.0,audioread,conda-forge/audioread,,,,1985088.0,23595.0,23462.0,https://pypi.org/project/audioread,2023-09-27 19:27:51.000,133.0,1966901.0,https://anaconda.org/conda-forge/audioread,2024-09-03 10:05:52.331,854792.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +314,CNTK,microsoft/CNTK,ml-frameworks,,https://github.com/microsoft/CNTK,https://github.com/microsoft/CNTK,MIT,2015-11-26 09:52:06.000,2023-03-11 07:31:35.000000,2022-09-23 14:06:50,16117.0,,4286.0,1251.0,557.0,840.0,2543.0,17499.0,"Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit.",274.0,29,False,2019-04-26 14:13:32.000,2.7,32.0,cntk,,,,14648.0,727.0,5.0,2.0,https://pypi.org/project/cntk,2020-12-09 22:21:57.000,3.0,587.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +315,baselines,openai/baselines,reinforcement-learning,,https://github.com/openai/baselines,https://github.com/openai/baselines,MIT,2017-05-24 01:58:13.000,2024-08-01 21:31:33.000000,2020-01-31 13:06:18,347.0,,4854.0,647.0,375.0,504.0,436.0,15622.0,OpenAI Baselines: high-quality implementations of reinforcement learning algorithms.,115.0,29,False,2018-02-26 17:07:07.000,0.1.5,6.0,baselines,,,,,835.0,580.0,577.0,https://pypi.org/project/baselines,2018-02-26 17:07:07.000,3.0,835.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +316,backtrader,mementum/backtrader,financial-data,,https://github.com/mementum/backtrader,https://github.com/mementum/backtrader,GPL-3.0,2015-01-10 07:14:52.000,2024-08-19 17:47:36.000000,2023-04-19 14:13:08,2404.0,,3836.0,609.0,230.0,51.0,,13943.0,Python Backtesting library for trading strategies.,56.0,29,False,,,157.0,backtrader,,,,,30692.0,2330.0,2257.0,https://pypi.org/project/backtrader,2023-04-19 14:15:00.742,73.0,30692.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +317,pretrainedmodels,Cadene/pretrained-models.pytorch,pytorch-utils,,https://github.com/Cadene/pretrained-models.pytorch,https://github.com/Cadene/pretrained-models.pytorch,BSD-3-Clause,2017-04-09 15:54:23.000,2023-06-16 19:20:12.183000,2020-04-16 08:02:22,154.0,,1834.0,215.0,46.0,101.0,94.0,9009.0,"Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.",22.0,29,False,2018-10-29 08:18:45.000,0.7.4,16.0,pretrainedmodels,conda-forge/pretrainedmodels,,['pytorch'],,151940.0,86.0,20.0,https://pypi.org/project/pretrainedmodels,2018-10-29 08:18:45.000,66.0,151147.0,https://anaconda.org/conda-forge/pretrainedmodels,2023-06-16 19:20:12.183,40451.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +318,DoWhy,py-why/dowhy,interpretability,,https://github.com/py-why/dowhy,https://github.com/py-why/dowhy,MIT,2018-05-31 13:07:04.000,2024-08-29 18:13:51.000000,2024-08-04 05:05:42,1038.0,21.0,910.0,136.0,732.0,129.0,340.0,6992.0,DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions...,92.0,29,True,2023-12-25 07:11:09.000,0.11.1,15.0,dowhy,conda-forge/dowhy,,,39.0,40830.0,422.0,415.0,https://pypi.org/project/dowhy,2023-12-25 07:11:09.000,7.0,40172.0,https://anaconda.org/conda-forge/dowhy,2024-01-26 10:57:10.385,30292.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +319,CleverHans,cleverhans-lab/cleverhans,adversarial,,https://github.com/cleverhans-lab/cleverhans,https://github.com/cleverhans-lab/cleverhans,MIT,2016-09-15 00:28:04.000,2024-04-10 13:26:10.000000,2023-01-31 19:40:04,3203.0,,1389.0,189.0,786.0,45.0,423.0,6150.0,"An adversarial example library for constructing attacks, building defenses, and benchmarking both.",132.0,29,False,2021-07-24 08:53:21.000,4.0.0,8.0,cleverhans,conda-forge/cleverhans,,['tensorflow'],,1941.0,738.0,731.0,https://pypi.org/project/cleverhans,2021-07-24 08:53:21.000,7.0,1770.0,https://anaconda.org/conda-forge/cleverhans,2023-06-16 19:20:32.486,8725.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +320,GluonCV,dmlc/gluon-cv,image,,https://github.com/dmlc/gluon-cv,https://github.com/dmlc/gluon-cv,Apache-2.0,2018-02-26 01:33:21.000,2024-04-19 02:47:07.000000,2023-01-19 00:37:33,900.0,,1212.0,153.0,951.0,58.0,789.0,5801.0,Gluon CV Toolkit.,119.0,29,False,2022-03-07 23:40:19.000,0.10.5,1535.0,gluoncv,,,['mxnet'],,64856.0,76.0,21.0,https://pypi.org/project/gluoncv,2023-02-03 18:46:00.371,55.0,64856.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +321,SynapseML,microsoft/SynapseML,distributed-ml,,https://github.com/microsoft/SynapseML,https://github.com/microsoft/SynapseML,MIT,2017-06-05 08:23:44.000,2024-08-31 18:49:56.000000,2024-08-30 02:03:46,1631.0,27.0,827.0,145.0,1552.0,367.0,401.0,5041.0,Simple and Distributed Machine Learning.,120.0,29,True,2024-08-30 02:16:51.000,1.0.5,51.0,synapseml,,,,,237594.0,5.0,,https://pypi.org/project/synapseml,2024-08-30 02:13:37.000,5.0,237594.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +322,causalml,uber/causalml,others,,https://github.com/uber/causalml,https://github.com/uber/causalml,Apache-2.0,2019-07-09 02:08:58.000,2024-08-01 13:16:45.000000,2024-08-01 13:16:45,618.0,5.0,758.0,84.0,346.0,55.0,338.0,4963.0,Uplift modeling and causal inference with machine learning algorithms.,63.0,29,True,2024-04-19 00:19:00.000,0.15.1,24.0,causalml,,,,,46665.0,218.0,217.0,https://pypi.org/project/causalml,2024-04-19 00:19:00.000,1.0,46665.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +323,lightfm,lyst/lightfm,recommender-systems,,https://github.com/lyst/lightfm,https://github.com/lyst/lightfm,Apache-2.0,2015-07-30 08:34:00.000,2024-07-24 18:48:54.000000,2023-04-30 18:36:20,483.0,,686.0,87.0,208.0,157.0,358.0,4709.0,"A Python implementation of LightFM, a hybrid recommendation algorithm.",47.0,29,False,2023-03-20 04:08:46.000,1.17,15.0,lightfm,conda-forge/lightfm,,,,412115.0,1561.0,1529.0,https://pypi.org/project/lightfm,2023-03-20 04:15:00.582,32.0,409421.0,https://anaconda.org/conda-forge/lightfm,2023-06-16 16:08:40.466,215576.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +324,GluonTS,awslabs/gluon-ts,time-series-data,,https://github.com/awslabs/gluonts,https://github.com/awslabs/gluonts,Apache-2.0,2019-05-15 17:17:29.000,2024-08-06 20:03:27.000000,2024-07-25 12:17:22,1473.0,4.0,744.0,75.0,1813.0,322.0,633.0,4529.0,Probabilistic time series modeling in Python.,117.0,29,True,2024-06-03 07:20:43.000,0.15.1,110.0,gluonts,anaconda/gluonts,,['mxnet'],,250647.0,31.0,,https://pypi.org/project/gluonts,2024-06-03 07:20:43.000,31.0,250622.0,https://anaconda.org/anaconda/gluonts,2023-12-22 09:31:03.436,899.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +325,nlpaug,makcedward/nlpaug,nlp,,https://github.com/makcedward/nlpaug,https://github.com/makcedward/nlpaug,MIT,2019-03-21 03:00:17.000,2024-06-24 09:15:15.000000,2022-07-07 05:16:43,738.0,,457.0,41.0,125.0,75.0,154.0,4399.0,Data augmentation for NLP.,33.0,29,False,2022-07-07 05:24:14.000,1.1.11,37.0,nlpaug,conda-forge/nlpaug,,,,118672.0,1410.0,1345.0,https://pypi.org/project/nlpaug,2022-07-07 05:23:07.000,65.0,118054.0,https://anaconda.org/conda-forge/nlpaug,2023-06-16 19:26:38.185,24124.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +326,Alpha Vantage,RomelTorres/alpha_vantage,financial-data,,https://github.com/RomelTorres/alpha_vantage,https://github.com/RomelTorres/alpha_vantage,MIT,2017-04-29 17:23:00.000,2024-08-09 13:30:50.391000,2024-07-18 16:46:48,557.0,32.0,735.0,175.0,90.0,1.0,288.0,4226.0,A python wrapper for Alpha Vantage API for financial data.,44.0,29,True,2024-07-18 14:29:16.000,3.0.0,35.0,alpha_vantage,conda-forge/alpha_vantage,,,,33166.0,35.0,,https://pypi.org/project/alpha_vantage,2024-07-18 14:29:16.000,35.0,33001.0,https://anaconda.org/conda-forge/alpha_vantage,2024-08-09 13:30:50.391,7289.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +327,sahi,obss/sahi,image,,https://github.com/obss/sahi,https://github.com/obss/sahi,MIT,2021-01-30 12:54:53.000,2024-08-27 11:49:25.000000,2024-08-27 11:02:25,515.0,5.0,568.0,42.0,541.0,14.0,,3934.0,Framework agnostic sliced/tiled inference + interactive ui + error analysis plots.,48.0,29,True,2024-08-27 11:49:25.000,0.11.19,103.0,sahi,conda-forge/sahi,,,26828.0,192924.0,1327.0,1301.0,https://pypi.org/project/sahi,2024-07-10 10:19:56.000,26.0,190287.0,https://anaconda.org/conda-forge/sahi,2024-07-24 03:28:58.170,70497.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +328,missingno,ResidentMario/missingno,data-viz,,https://github.com/ResidentMario/missingno,https://github.com/ResidentMario/missingno,MIT,2016-03-27 15:18:50.000,2024-05-14 18:30:13.000000,2023-02-26 20:07:33,189.0,,515.0,77.0,38.0,14.0,121.0,3890.0,Missing data visualization module for Python.,18.0,29,False,2023-02-26 20:11:59.371,0.5.2,26.0,missingno,conda-forge/missingno,,,,274981.0,17794.0,17674.0,https://pypi.org/project/missingno,2023-02-26 20:11:59.371,120.0,215379.0,https://anaconda.org/conda-forge/missingno,2024-03-02 01:06:27.711,357612.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +329,NeuralProphet,ourownstory/neural_prophet,time-series-data,,https://github.com/ourownstory/neural_prophet,https://github.com/ourownstory/neural_prophet,MIT,2020-05-04 05:12:43.000,2024-09-04 03:03:11.000000,2024-09-04 03:03:10,1461.0,37.0,469.0,54.0,819.0,58.0,494.0,3798.0,NeuralProphet: A simple forecasting package.,56.0,29,True,2024-06-21 07:42:22.000,0.9.0,36.0,neuralprophet,,,['pytorch'],,159469.0,8.0,,https://pypi.org/project/neuralprophet,2024-06-26 23:51:51.000,8.0,159469.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +330,anomalib,openvinotoolkit/anomalib,others,,https://github.com/openvinotoolkit/anomalib,https://github.com/openvinotoolkit/anomalib,Apache-2.0,2021-11-02 09:11:38.000,2024-09-03 20:22:46.000000,2024-09-03 20:21:34,675.0,28.0,638.0,39.0,940.0,122.0,761.0,3622.0,"An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-..",80.0,29,True,2024-08-12 12:57:29.000,1.1.1,32.0,anomalib,,,,13141.0,27116.0,92.0,87.0,https://pypi.org/project/anomalib,2024-08-12 12:57:52.000,5.0,26718.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +331,doctr,mindee/doctr,image,,https://github.com/mindee/doctr,https://github.com/mindee/doctr,Apache-2.0,2021-01-08 16:05:12.000,2024-08-29 02:56:49.000000,2024-08-29 02:47:33,880.0,13.0,414.0,44.0,969.0,38.0,327.0,3536.0,"docTR (Document Text Recognition) - a seamless, high-performing & accessible library for OCR-related tasks powered by..",50.0,29,True,2024-08-08 14:03:10.000,0.9.0,16.0,python-doctr,,,"['tensorflow', 'pytorch']",3601406.0,136535.0,12.0,,https://pypi.org/project/python-doctr,2024-08-08 14:03:10.000,12.0,52782.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +332,fastNLP,fastnlp/fastNLP,nlp,,https://github.com/fastnlp/fastNLP,https://github.com/fastnlp/fastNLP,Apache-2.0,2018-03-07 13:30:20.000,2023-06-05 03:00:37.000000,2022-12-13 03:52:09,2484.0,,455.0,82.0,245.0,62.0,155.0,3059.0,fastNLP: A Modularized and Extensible NLP Framework. Currently still in incubation.,61.0,29,False,2022-10-31 14:47:34.183,1.0.1,24.0,fastnlp,,,,85.0,124279.0,197.0,195.0,https://pypi.org/project/fastnlp,2022-10-31 14:47:34.183,2.0,124278.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +333,Cufflinks,santosjorge/cufflinks,data-viz,,https://github.com/santosjorge/cufflinks,https://github.com/santosjorge/cufflinks,MIT,2014-11-19 20:59:33.000,2024-07-03 14:15:42.000000,2021-02-25 05:05:09,452.0,,676.0,109.0,73.0,102.0,123.0,3016.0,Productivity Tools for Plotly + Pandas.,38.0,29,False,2020-03-01 17:42:01.000,0.17.3,28.0,cufflinks,,,['pandas'],,59754.0,11678.0,11569.0,https://pypi.org/project/cufflinks,2020-03-01 17:42:01.000,109.0,59754.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +334,hmmlearn,hmmlearn/hmmlearn,probabilistics,,https://github.com/hmmlearn/hmmlearn,https://github.com/hmmlearn/hmmlearn,BSD-3-Clause,2014-03-23 10:33:09.000,2024-05-22 19:32:05.771000,2024-04-05 20:34:01,476.0,,737.0,120.0,125.0,69.0,370.0,3014.0,"Hidden Markov Models in Python, with scikit-learn like API.",49.0,29,True,2024-03-02 03:05:38.000,0.3.2,13.0,hmmlearn,conda-forge/hmmlearn,,['sklearn'],,113569.0,2818.0,2731.0,https://pypi.org/project/hmmlearn,2024-03-02 03:05:38.000,87.0,107941.0,https://anaconda.org/conda-forge/hmmlearn,2024-05-22 19:32:05.771,270169.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +335,mljar-supervised,mljar/mljar-supervised,hyperopt,,https://github.com/mljar/mljar-supervised,https://github.com/mljar/mljar-supervised,MIT,2018-11-05 12:58:04.000,2024-09-02 13:38:40.000000,2024-09-02 13:38:40,1202.0,28.0,399.0,50.0,91.0,160.0,496.0,2996.0,"Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and..",28.0,29,True,2024-06-03 11:50:12.000,1.1.9,92.0,mljar-supervised,conda-forge/mljar-supervised,,,,5452.0,133.0,129.0,https://pypi.org/project/mljar-supervised,2024-06-03 11:50:12.000,4.0,4923.0,https://anaconda.org/conda-forge/mljar-supervised,2024-06-03 17:12:53.954,20641.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +336,TF-Agents,tensorflow/agents,reinforcement-learning,,https://github.com/tensorflow/agents,https://github.com/tensorflow/agents,Apache-2.0,2018-11-17 00:29:12.000,2024-08-22 03:23:17.000000,2024-08-22 03:22:36,2303.0,6.0,714.0,79.0,205.0,198.0,469.0,2773.0,"TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.",151.0,29,True,2023-12-14 04:07:38.000,0.19.0,51.0,tf-agents,,,['tensorflow'],,70048.0,14.0,,https://pypi.org/project/tf-agents,2023-12-14 04:07:38.000,14.0,70048.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +337,shapash,MAIF/shapash,interpretability,,https://github.com/MAIF/shapash,https://github.com/MAIF/shapash,Apache-2.0,2020-04-29 07:34:23.000,2024-09-03 13:22:10.000000,2024-09-03 13:22:10,1638.0,38.0,327.0,37.0,348.0,36.0,167.0,2712.0,Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models.,38.0,29,True,2024-07-04 10:21:38.000,2.6.0,42.0,shapash,,,['jupyter'],,7273.0,175.0,171.0,https://pypi.org/project/shapash,2024-07-04 10:21:38.000,4.0,7273.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +338,ipyparallel,ipython/ipyparallel,distributed-ml,,https://github.com/ipython/ipyparallel,https://github.com/ipython/ipyparallel,,2015-04-09 07:43:55.000,2024-09-02 22:27:25.000000,2024-07-02 07:21:59,2916.0,6.0,997.0,123.0,525.0,65.0,300.0,2575.0,IPython Parallel: Interactive Parallel Computing in Python.,113.0,29,False,2024-04-05 11:35:24.000,8.8.0,47.0,ipyparallel,conda-forge/ipyparallel,,['jupyter'],,556659.0,112.0,,https://pypi.org/project/ipyparallel,2024-04-05 11:35:24.000,112.0,533374.0,https://anaconda.org/conda-forge/ipyparallel,2024-04-05 13:21:22.787,1094416.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +339,GluonNLP,dmlc/gluon-nlp,nlp,,https://github.com/dmlc/gluon-nlp,https://github.com/dmlc/gluon-nlp,Apache-2.0,2018-04-04 20:57:13.000,2023-10-06 04:01:21.000000,2022-12-25 20:52:27,843.0,,519.0,95.0,1045.0,260.0,297.0,2554.0,"Toolkit that enables easy text preprocessing, datasets loading and neural models building to help you speed up your..",86.0,29,False,2020-08-13 19:17:42.000,0.10.0,26.0,gluonnlp,,,['mxnet'],,84220.0,1624.0,1602.0,https://pypi.org/project/gluonnlp,2020-08-13 19:17:42.000,22.0,84220.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +340,mpld3,mpld3/mpld3,data-viz,,https://github.com/mpld3/mpld3,https://github.com/mpld3/mpld3,BSD-3-Clause,2013-12-18 01:48:30.000,2024-01-11 18:01:50.000000,2023-12-23 13:05:00,887.0,,357.0,82.0,168.0,217.0,148.0,2346.0,An interactive data visualization tool which brings matplotlib graphics to the browser using D3.,52.0,29,True,2023-12-23 13:04:29.963,0.5.10,19.0,mpld3,conda-forge/mpld3,,,,328586.0,6578.0,6430.0,https://pypi.org/project/mpld3,2023-12-23 13:03:02.000,139.0,323492.0,https://anaconda.org/conda-forge/mpld3,2023-12-23 15:16:22.285,207608.0,3.0,,,,,,,,,mpld3,https://www.npmjs.com/package/mpld3,2023-12-23 13:04:29.963,9.0,1024.0,,,,,,,,,,,, +341,explainerdashboard,oegedijk/explainerdashboard,interpretability,,https://github.com/oegedijk/explainerdashboard,https://github.com/oegedijk/explainerdashboard,MIT,2019-10-30 08:26:16.000,2024-07-18 15:45:47.000000,2024-06-20 19:30:24,1373.0,1.0,324.0,22.0,49.0,35.0,203.0,2288.0,Quickly build Explainable AI dashboards that show the inner workings of so-called blackbox machine learning models.,21.0,29,True,2024-03-18 21:02:33.000,0.4.7,91.0,explainerdashboard,conda-forge/explainerdashboard,,,,91434.0,539.0,529.0,https://pypi.org/project/explainerdashboard,2024-03-18 21:02:33.000,10.0,90291.0,https://anaconda.org/conda-forge/explainerdashboard,2024-03-18 22:16:35.129,51439.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +342,alibi-detect,SeldonIO/alibi-detect,others,,https://github.com/SeldonIO/alibi-detect,https://github.com/SeldonIO/alibi-detect,Intel,2019-10-07 13:29:13.000,2024-08-05 07:13:17.000000,2024-05-21 10:49:30,727.0,,218.0,37.0,545.0,136.0,235.0,2201.0,"Algorithms for outlier, adversarial and drift detection.",23.0,29,False,2024-04-17 16:12:46.000,0.12.0,38.0,alibi-detect,,,,,64322.0,477.0,470.0,https://pypi.org/project/alibi-detect,2024-04-17 16:12:46.000,7.0,64322.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +343,ogb,snap-stanford/ogb,graph,,https://github.com/snap-stanford/ogb,https://github.com/snap-stanford/ogb,MIT,2019-11-22 22:13:57.000,2024-02-13 19:24:57.000000,2024-02-01 18:50:30,675.0,,400.0,41.0,62.0,23.0,271.0,1911.0,"Benchmark datasets, data loaders, and evaluators for graph machine learning.",32.0,29,True,2023-04-07 06:00:55.135,1.3.6,19.0,ogb,conda-forge/ogb,,,,102312.0,1915.0,1893.0,https://pypi.org/project/ogb,2022-11-02 22:00:56.960,22.0,101571.0,https://anaconda.org/conda-forge/ogb,2023-06-16 19:21:31.692,35597.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +344,ffn,pmorissette/ffn,financial-data,,https://github.com/pmorissette/ffn,https://github.com/pmorissette/ffn,MIT,2014-06-19 15:54:09.000,2024-09-01 16:40:55.000000,2024-08-06 14:00:12,485.0,34.0,282.0,61.0,121.0,23.0,103.0,1894.0,ffn - a financial function library for Python.,35.0,29,True,2024-08-06 13:45:28.000,1.1.0,37.0,ffn,conda-forge/ffn,,,,48540.0,504.0,488.0,https://pypi.org/project/ffn,2024-08-05 23:48:25.000,16.0,48261.0,https://anaconda.org/conda-forge/ffn,2024-08-06 14:03:54.464,11459.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +345,fairlearn,fairlearn/fairlearn,interpretability,,https://github.com/fairlearn/fairlearn,https://github.com/fairlearn/fairlearn,MIT,2018-05-15 01:51:35.000,2024-09-03 22:47:31.000000,2024-09-03 12:37:19,874.0,18.0,412.0,38.0,905.0,160.0,316.0,1889.0,A Python package to assess and improve fairness of machine learning models.,83.0,29,True,2023-12-19 14:14:09.000,0.10.0,20.0,fairlearn,conda-forge/fairlearn,,['sklearn'],,177842.0,58.0,3.0,https://pypi.org/project/fairlearn,2023-12-19 02:11:12.000,55.0,177070.0,https://anaconda.org/conda-forge/fairlearn,2023-12-20 11:56:56.090,35553.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +346,audiomentations,iver56/audiomentations,audio,,https://github.com/iver56/audiomentations,https://github.com/iver56/audiomentations,MIT,2019-02-12 16:36:24.000,2024-09-04 07:50:37.000000,2024-09-04 07:50:35,1215.0,22.0,186.0,20.0,162.0,47.0,136.0,1801.0,A Python library for audio data augmentation. Inspired by albumentations. Useful for machine learning.,29.0,29,True,2024-09-03 07:35:15.000,0.37.0,41.0,audiomentations,,,,,45502.0,575.0,557.0,https://pypi.org/project/audiomentations,2024-09-03 07:35:15.000,18.0,45502.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +347,PyKEEN,pykeen/pykeen,graph,,https://github.com/pykeen/pykeen,https://github.com/pykeen/pykeen,MIT,2020-02-24 07:26:03.000,2024-09-04 11:16:25.000000,2024-09-04 09:30:07,2850.0,18.0,182.0,26.0,692.0,118.0,457.0,1620.0,A Python library for learning and evaluating knowledge graph embeddings.,41.0,29,True,2024-02-19 21:29:27.000,1.10.2,47.0,pykeen,,,,200.0,6465.0,245.0,239.0,https://pypi.org/project/pykeen,2024-02-19 21:25:43.000,6.0,6462.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +348,pingouin,raphaelvallat/pingouin,probabilistics,,https://github.com/raphaelvallat/pingouin,https://github.com/raphaelvallat/pingouin,GPL-3.0,2018-04-01 01:10:22.000,2024-09-04 22:25:36.166000,2024-09-04 10:38:43,1254.0,2.0,137.0,31.0,114.0,35.0,269.0,1596.0,Statistical package in Python based on Pandas.,46.0,29,False,2024-09-04 10:48:32.000,0.5.5,41.0,pingouin,conda-forge/pingouin,,,,91497.0,2496.0,2340.0,https://pypi.org/project/pingouin,2024-09-04 10:42:50.000,156.0,88930.0,https://anaconda.org/conda-forge/pingouin,2024-09-04 22:25:36.166,130946.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +349,TabPy,tableau/TabPy,others,,https://github.com/tableau/TabPy,https://github.com/tableau/TabPy,MIT,2016-09-27 21:26:03.000,2024-09-05 15:35:38.000000,2024-09-05 15:30:47,997.0,47.0,592.0,107.0,287.0,22.0,300.0,1549.0,Execute Python code on the fly and display results in Tableau visualizations:.,51.0,29,True,2024-09-05 15:35:38.000,2.11.0,33.0,tabpy,anaconda/tabpy-client,,,,6997.0,176.0,174.0,https://pypi.org/project/tabpy,2024-09-05 15:35:38.000,2.0,6946.0,https://anaconda.org/anaconda/tabpy-client,2023-06-16 13:20:17.078,4579.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +350,spacy-transformers,explosion/spacy-transformers,nlp,,https://github.com/explosion/spacy-transformers,https://github.com/explosion/spacy-transformers,MIT,2019-07-26 19:12:34.000,2024-06-05 08:48:15.000000,2024-06-05 08:42:47,1478.0,,163.0,32.0,252.0,,,1334.0,"Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy.",22.0,29,True,2024-04-25 12:54:53.000,1.3.5,77.0,spacy-transformers,conda-forge/spacy-transformers,,['spacy'],,248246.0,1922.0,1835.0,https://pypi.org/project/spacy-transformers,2024-04-25 12:53:43.000,87.0,246514.0,https://anaconda.org/conda-forge/spacy-transformers,2023-12-19 11:34:09.090,58893.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +351,ktrain,amaiya/ktrain,ml-frameworks,,https://github.com/amaiya/ktrain,https://github.com/amaiya/ktrain,Apache-2.0,2019-02-06 17:01:39.000,2024-08-23 02:08:55.000000,2024-07-09 16:09:26,3066.0,22.0,268.0,34.0,38.0,1.0,495.0,1221.0,ktrain is a Python library that makes deep learning and AI more accessible and easier to apply.,17.0,29,True,2024-06-19 01:15:40.000,0.41.4,211.0,ktrain,,,['tensorflow'],,7697.0,552.0,548.0,https://pypi.org/project/ktrain,2024-06-19 01:15:40.000,4.0,7697.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +352,geojson,jazzband/geojson,geospatial-data,,https://github.com/jazzband/geojson,https://github.com/jazzband/geojson,BSD-3-Clause,2011-07-01 20:39:48.000,2024-08-08 16:10:29.000000,2024-08-08 16:10:29,495.0,1.0,120.0,31.0,129.0,26.0,75.0,907.0,Python bindings and utilities for GeoJSON.,56.0,29,True,2023-11-05 21:06:50.000,3.1.0,31.0,geojson,conda-forge/geojson,,,,2200632.0,18817.0,18126.0,https://pypi.org/project/geojson,2023-11-05 21:06:50.000,691.0,2156391.0,https://anaconda.org/conda-forge/geojson,2023-11-06 11:21:40.354,840590.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +353,dask-ml,dask/dask-ml,distributed-ml,,https://github.com/dask/dask-ml,https://github.com/dask/dask-ml,BSD-3-Clause,2017-06-15 15:56:06.000,2024-07-21 18:27:09.000000,2024-07-20 22:10:37,819.0,1.0,255.0,40.0,513.0,278.0,257.0,890.0,Scalable Machine Learning with Dask.,80.0,29,True,2024-04-02 02:33:18.000,2024.4.4,37.0,dask-ml,conda-forge/dask-ml,,,,250134.0,1181.0,1088.0,https://pypi.org/project/dask-ml,2024-04-02 02:33:18.000,93.0,233157.0,https://anaconda.org/conda-forge/dask-ml,2024-06-17 15:22:39.176,882840.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +354,python-soundfile,bastibe/python-soundfile,audio,,https://github.com/bastibe/python-soundfile,https://github.com/bastibe/python-soundfile,BSD-3-Clause,2013-08-27 13:36:52.000,2024-07-27 07:14:46.000000,2024-07-27 07:14:46,566.0,2.0,106.0,16.0,196.0,119.0,139.0,698.0,"SoundFile is an audio library based on libsndfile, CFFI, and NumPy.",34.0,29,True,2023-02-15 15:39:02.000,0.12.1,15.0,soundfile,anaconda/pysoundfile,,,19666.0,4569845.0,41907.0,41127.0,https://pypi.org/project/soundfile,2023-02-15 15:39:00.786,780.0,4569691.0,https://anaconda.org/anaconda/pysoundfile,,,3.0,,,,,,4.0,,,,,,,,,,,,,,,,,,, +355,GeoViews,holoviz/geoviews,geospatial-data,,https://github.com/holoviz/geoviews,https://github.com/holoviz/geoviews,BSD-3-Clause,2016-04-19 16:27:01.000,2024-08-02 07:27:48.000000,2024-08-01 18:07:01,834.0,10.0,75.0,25.0,396.0,104.0,240.0,586.0,"Simple, concise geographical visualization in Python.",32.0,29,True,2024-04-05 15:56:28.000,1.12.0,64.0,geoviews,conda-forge/geoviews,,,,18755.0,1152.0,1095.0,https://pypi.org/project/geoviews,2024-08-02 07:27:48.000,57.0,13749.0,https://anaconda.org/conda-forge/geoviews,2024-04-05 16:04:19.139,240327.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +356,PyStan,stan-dev/pystan,probabilistics,,https://github.com/stan-dev/pystan,https://github.com/stan-dev/pystan,ISC,2017-03-06 19:56:42.094,2024-07-03 17:04:15.000000,2024-07-03 17:02:18,237.0,5.0,58.0,13.0,207.0,12.0,187.0,335.0,"PyStan, a Python interface to Stan, a platform for statistical modeling. Documentation: https://pystan.readthedocs.io.",14.0,29,True,2024-07-03 17:04:15.000,3.10.0,73.0,pystan,conda-forge/pystan,,,,824052.0,10145.0,9985.0,https://pypi.org/project/pystan,2024-07-03 17:04:15.000,160.0,791939.0,https://anaconda.org/conda-forge/pystan,2023-06-16 13:14:39.735,2890192.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +357,pysc2,deepmind/pysc2,others,,https://github.com/google-deepmind/pysc2,https://github.com/google-deepmind/pysc2,Apache-2.0,2017-07-25 18:16:57.000,2024-07-23 16:54:42.000000,2023-04-19 16:47:52,581.0,,1146.0,349.0,81.0,50.0,231.0,7988.0,StarCraft II Learning Environment.,39.0,28,False,2022-07-13 12:08:43.000,4.0,8.0,pysc2,,,,31719.0,2847.0,828.0,802.0,https://pypi.org/project/pysc2,2022-07-13 12:02:04.256,26.0,2474.0,,,,2.0,,,,,,,,google-deepmind/pysc2,,,,,,,,,,,,,,,,, +358,Facets Overview,pair-code/facets,data-viz,,https://github.com/PAIR-code/facets,https://github.com/PAIR-code/facets,Apache-2.0,2017-07-07 14:03:03.000,2023-05-24 15:58:01.158000,2023-05-24 15:56:22,277.0,,886.0,267.0,98.0,82.0,81.0,7345.0,Visualizations for machine learning datasets.,31.0,28,False,2023-05-24 15:58:01.158,1.1.1,9.0,facets-overview,,,['jupyter'],,130769.0,270.0,262.0,https://pypi.org/project/facets-overview,2023-05-24 15:58:01.158,8.0,130769.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +359,Face Alignment,1adrianb/face-alignment,image,,https://github.com/1adrianb/face-alignment,https://github.com/1adrianb/face-alignment,BSD-3-Clause,2017-09-15 20:32:44.000,2024-08-30 14:19:26.000000,2024-08-30 14:19:23,221.0,1.0,1338.0,172.0,46.0,80.0,241.0,6989.0,2D and 3D Face alignment library build using pytorch.,26.0,28,True,2023-08-17 14:43:11.000,1.4.1,14.0,face-alignment,,,['pytorch'],,84431.0,31.0,21.0,https://pypi.org/project/face-alignment,2023-08-17 14:43:11.000,10.0,84431.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +360,pyAudioAnalysis,tyiannak/pyAudioAnalysis,audio,,https://github.com/tyiannak/pyAudioAnalysis,https://github.com/tyiannak/pyAudioAnalysis,Apache-2.0,2014-08-27 12:43:13.000,2024-03-31 17:27:35.000000,2023-10-22 09:33:23,779.0,,1190.0,210.0,92.0,201.0,122.0,5797.0,"Python Audio Analysis Library: Feature Extraction, Classification, Segmentation and Applications.",28.0,28,True,2022-02-07 22:36:53.000,0.3.14,23.0,pyAudioAnalysis,,,,,10443.0,513.0,501.0,https://pypi.org/project/pyAudioAnalysis,2022-02-07 22:36:53.000,12.0,10443.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +361,layout-parser,Layout-Parser/layout-parser,image,,https://github.com/Layout-Parser/layout-parser,https://github.com/Layout-Parser/layout-parser,Apache-2.0,2020-06-10 20:22:54.000,2024-08-15 06:26:34.000000,2022-08-06 21:47:18,182.0,,455.0,72.0,63.0,110.0,57.0,4760.0,A Unified Toolkit for Deep Learning Based Document Image Analysis.,8.0,28,False,2022-04-06 04:38:09.000,0.3.4,11.0,layoutparser,,,,,369566.0,2670.0,2648.0,https://pypi.org/project/layoutparser,2022-04-06 04:38:09.000,22.0,369566.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +362,ArrayFire,arrayfire/arrayfire,gpu-utilities,,https://github.com/arrayfire/arrayfire,https://github.com/arrayfire/arrayfire,BSD-3-Clause,2014-10-28 20:58:33.000,2024-09-04 23:54:45.000000,2024-09-03 19:39:21,6165.0,12.0,530.0,147.0,1937.0,338.0,1371.0,4519.0,ArrayFire: a general purpose GPU library.,92.0,28,True,2023-08-29 19:49:26.000,3.9.0,34.0,arrayfire,,,,6822.0,2244.0,10.0,,https://pypi.org/project/arrayfire,2022-02-22 21:42:15.000,10.0,2183.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +363,facenet-pytorch,timesler/facenet-pytorch,image,,https://github.com/timesler/facenet-pytorch,https://github.com/timesler/facenet-pytorch,MIT,2019-05-25 01:29:24.000,2024-08-02 08:16:49.000000,2024-08-02 08:16:49,252.0,1.0,942.0,53.0,57.0,73.0,108.0,4421.0,Pretrained Pytorch face detection (MTCNN) and facial recognition (InceptionResnet) models.,18.0,28,True,2024-04-29 17:50:14.000,2.6.0,33.0,facenet-pytorch,,,['pytorch'],1228157.0,84783.0,2206.0,2155.0,https://pypi.org/project/facenet-pytorch,2024-04-29 17:50:14.000,51.0,63608.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +364,MMOCR,open-mmlab/mmocr,ocr,,https://github.com/open-mmlab/mmocr,https://github.com/open-mmlab/mmocr,Apache-2.0,2021-04-07 13:40:21.000,2024-07-15 00:15:22.000000,2024-04-23 02:12:59,1138.0,,740.0,58.0,1015.0,187.0,741.0,4267.0,"OpenMMLab Text Detection, Recognition and Understanding Toolbox.",90.0,28,True,2023-07-04 07:12:41.567,1.0.1,20.0,mmocr,,,['pytorch'],,14045.0,162.0,158.0,https://pypi.org/project/mmocr,2022-05-05 14:21:18.000,4.0,14045.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +365,Lasagne,Lasagne/Lasagne,ml-frameworks,,https://github.com/Lasagne/Lasagne,https://github.com/Lasagne/Lasagne,MIT,2014-09-11 15:31:41.000,2022-03-26 02:58:32.000000,2019-11-20 20:28:30,1161.0,,949.0,218.0,408.0,139.0,402.0,3845.0,Lightweight library to build and train neural networks in Theano.,72.0,28,False,2015-08-13 21:00:09.000,0.1,2.0,lasagne,,,,,2358.0,1070.0,1058.0,https://pypi.org/project/lasagne,2015-08-13 21:10:53.000,12.0,2358.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +366,bqplot,bqplot/bqplot,data-viz,,https://github.com/bqplot/bqplot,https://github.com/bqplot/bqplot,Apache-2.0,2015-09-26 04:02:18.000,2024-09-03 15:35:53.000000,2024-09-03 15:35:53,3662.0,2.0,463.0,102.0,1050.0,259.0,368.0,3608.0,Plotting library for IPython/Jupyter notebooks.,65.0,28,True,2024-02-27 15:38:38.000,0.12.43,112.0,bqplot,conda-forge/bqplot,,['jupyter'],,172574.0,177.0,58.0,https://pypi.org/project/bqplot,2024-03-25 09:03:21.000,98.0,143649.0,https://anaconda.org/conda-forge/bqplot,2024-02-19 16:46:43.025,1372748.0,3.0,,,,,,,,,bqplot,https://www.npmjs.com/package/bqplot,2024-03-25 09:04:27.051,21.0,2526.0,,,,,,,,,,,, +367,Deep Checks,deepchecks/deepchecks,interpretability,,https://github.com/deepchecks/deepchecks,https://github.com/deepchecks/deepchecks,AGPL-3.0,2021-10-11 14:48:38.000,2024-07-31 19:18:48.000000,2024-02-22 12:17:17,1487.0,,249.0,19.0,1746.0,295.0,726.0,3550.0,Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all..,53.0,28,False,2024-01-31 13:08:55.000,0.18.1,60.0,deepchecks,,,,1001.0,130586.0,421.0,409.0,https://pypi.org/project/deepchecks,2024-01-31 13:08:49.000,12.0,130558.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +368,Sumy,miso-belica/sumy,nlp,,https://github.com/miso-belica/sumy,https://github.com/miso-belica/sumy,Apache-2.0,2013-02-20 12:56:48.000,2024-05-16 18:13:04.000000,2024-05-16 18:13:03,456.0,,526.0,113.0,93.0,23.0,101.0,3495.0,Module for automatic summarization of text documents and HTML pages.,32.0,28,True,2022-10-23 16:42:18.783,0.11.0,16.0,sumy,conda-forge/sumy,,,,433501.0,3062.0,3034.0,https://pypi.org/project/sumy,2022-10-23 16:42:18.783,28.0,433268.0,https://anaconda.org/conda-forge/sumy,2023-06-16 19:26:28.563,9089.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +369,Acme,deepmind/acme,reinforcement-learning,,https://github.com/google-deepmind/acme,https://github.com/google-deepmind/acme,Apache-2.0,2020-05-01 09:18:12.000,2024-08-26 16:20:21.000000,2024-08-26 16:19:18,1204.0,3.0,418.0,82.0,55.0,62.0,203.0,3466.0,A library of reinforcement learning components and agents.,86.0,28,True,2022-02-10 06:52:27.000,0.4.0,15.0,dm-acme,conda-forge/dm-acme,,['tensorflow'],,1706.0,218.0,215.0,https://pypi.org/project/dm-acme,2022-02-10 06:52:27.000,3.0,1498.0,https://anaconda.org/conda-forge/dm-acme,2023-06-16 19:23:44.096,9604.0,2.0,,,,,,,,google-deepmind/acme,,,,,,,,,,,,,,,,, +370,aubio,aubio/aubio,audio,,https://github.com/aubio/aubio,https://github.com/aubio/aubio,GPL-3.0,2009-12-04 21:07:44.000,2024-08-03 07:04:44.000000,2024-01-02 20:16:48,4161.0,,368.0,84.0,64.0,154.0,189.0,3268.0,a library for audio and music analysis.,25.0,28,False,2019-02-27 09:00:43.000,0.4.9,10.0,aubio,conda-forge/aubio,,,,13711.0,498.0,481.0,https://pypi.org/project/aubio,2019-02-08 11:21:02.000,17.0,5881.0,https://anaconda.org/conda-forge/aubio,2023-06-16 13:24:40.255,704751.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +371,Catalyst,catalyst-team/catalyst,ml-experiments,,https://github.com/catalyst-team/catalyst,https://github.com/catalyst-team/catalyst,Apache-2.0,2018-08-20 07:56:13.000,2024-03-20 16:17:12.000000,2022-04-29 04:19:24,1698.0,,387.0,45.0,1085.0,2.0,353.0,3263.0,Accelerated deep learning R&D.,104.0,28,False,2022-04-29 04:45:11.000,22.04,108.0,catalyst,,,['pytorch'],,21536.0,1211.0,1181.0,https://pypi.org/project/catalyst,2022-04-29 04:46:04.000,30.0,21536.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +372,StellarGraph,stellargraph/stellargraph,graph,,https://github.com/stellargraph/stellargraph,https://github.com/stellargraph/stellargraph,Apache-2.0,2018-04-13 07:35:51.000,2024-04-10 12:25:23.000000,2021-10-29 06:15:49,2535.0,,429.0,62.0,933.0,325.0,745.0,2932.0,StellarGraph - Machine Learning on Graphs.,37.0,28,False,2021-02-22 06:35:38.731,1.2.1,25.0,stellargraph,,,['tensorflow'],,12067.0,283.0,272.0,https://pypi.org/project/stellargraph,2021-02-22 06:35:38.731,11.0,12067.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +373,dtreeviz,parrt/dtreeviz,interpretability,,https://github.com/parrt/dtreeviz,https://github.com/parrt/dtreeviz,MIT,2018-08-13 21:45:15.000,2024-08-29 16:58:41.000000,2024-08-29 16:58:41,621.0,2.0,334.0,45.0,121.0,72.0,137.0,2922.0,A python library for decision tree visualization and model interpretation.,27.0,28,True,2023-07-13 17:23:01.507,2.2.2,41.0,dtreeviz,conda-forge/dtreeviz,,,,127117.0,1337.0,1284.0,https://pypi.org/project/dtreeviz,2022-07-07 17:18:00.886,53.0,125351.0,https://anaconda.org/conda-forge/dtreeviz,2023-07-13 20:18:43.899,81281.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +374,Essentia,MTG/essentia,audio,,https://github.com/MTG/essentia,https://github.com/MTG/essentia,AGPL-3.0,2013-06-03 14:53:47.000,2024-07-26 11:49:48.000000,2024-07-26 10:43:49,3587.0,23.0,522.0,108.0,361.0,388.0,688.0,2794.0,"C++ library for audio and music analysis, description and synthesis, including Python bindings.",81.0,28,False,2015-03-31 16:33:30.000,2.0,21.0,essentia,,,,,9887.0,772.0,752.0,https://pypi.org/project/essentia,2024-04-29 15:12:27.000,20.0,9887.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +375,pygal,Kozea/pygal,graph,,https://github.com/Kozea/pygal,https://github.com/Kozea/pygal,LGPL-3.0,2011-09-23 10:17:50.000,2024-08-13 16:15:34.495000,2024-08-12 14:54:41,1058.0,5.0,411.0,125.0,144.0,198.0,247.0,2634.0,PYthon svg GrAph plotting Library.,77.0,28,False,2024-08-12 14:55:21.000,3.0.5,81.0,pygal,conda-forge/pygal,,,,401541.0,101.0,,https://pypi.org/project/pygal,2024-08-12 14:55:21.000,101.0,398387.0,https://anaconda.org/conda-forge/pygal,2024-08-13 16:15:34.495,63083.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +376,scikit-plot,reiinakano/scikit-plot,interpretability,,https://github.com/reiinakano/scikit-plot,https://github.com/reiinakano/scikit-plot,MIT,2017-02-04 06:22:59.000,2024-08-20 05:47:39.000000,2018-08-19 12:37:47,130.0,,284.0,65.0,61.0,31.0,39.0,2427.0,An intuitive library to add plotting functionality to scikit-learn objects.,13.0,28,False,2018-08-19 12:25:39.290,0.3.7,27.0,scikit-plot,conda-forge/scikit-plot,,['sklearn'],,429598.0,5427.0,5342.0,https://pypi.org/project/scikit-plot,2018-08-19 12:25:39.290,85.0,427470.0,https://anaconda.org/conda-forge/scikit-plot,2023-06-16 13:22:21.652,183059.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +377,Alibi,SeldonIO/alibi,interpretability,,https://github.com/SeldonIO/alibi,https://github.com/SeldonIO/alibi,Intel,2019-02-26 10:10:56.000,2024-07-12 00:39:50.000000,2024-05-21 08:57:13,663.0,,249.0,54.0,659.0,147.0,225.0,2369.0,Algorithms for explaining machine learning models.,22.0,28,False,2024-04-18 15:30:25.000,0.9.6,34.0,alibi,,,,,16067.0,670.0,645.0,https://pypi.org/project/alibi,2024-04-18 15:29:10.000,25.0,16067.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +378,Spektral,danielegrattarola/spektral,graph,,https://github.com/danielegrattarola/spektral,https://github.com/danielegrattarola/spektral,MIT,2019-01-17 11:19:10.000,2024-01-21 16:47:04.000000,2024-01-21 16:46:47,1134.0,,336.0,45.0,57.0,68.0,207.0,2361.0,Graph Neural Networks with Keras and Tensorflow 2.,27.0,28,True,2024-01-21 16:17:36.000,1.3.1,35.0,spektral,,,['tensorflow'],,10685.0,330.0,323.0,https://pypi.org/project/spektral,2024-01-21 16:17:36.000,7.0,10685.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +379,langid,saffsd/langid.py,nlp,,https://github.com/saffsd/langid.py,https://github.com/saffsd/langid.py,BSD-3-Clause,2011-04-29 00:16:56.000,2020-01-01 10:49:30.000000,2017-07-15 02:49:17,242.0,,315.0,65.0,14.0,28.0,47.0,2295.0,Stand-alone language identification system.,9.0,28,False,2016-04-05 22:34:15.000,1.1.6,8.0,langid,,,,,351028.0,11686.0,11532.0,https://pypi.org/project/langid,2016-04-05 22:34:15.000,154.0,351028.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +380,SciSpacy,allenai/scispacy,nlp,,https://github.com/allenai/scispacy,https://github.com/allenai/scispacy,Apache-2.0,2018-09-24 21:45:52.000,2024-03-30 17:39:23.000000,2024-03-30 17:39:23,1059.0,,222.0,52.0,205.0,33.0,285.0,1675.0,A full spaCy pipeline and models for scientific/biomedical documents.,33.0,28,True,2024-03-08 05:58:36.000,0.5.4,15.0,scispacy,,,,,23962.0,985.0,951.0,https://pypi.org/project/scispacy,2024-03-08 05:58:36.000,34.0,23962.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +381,torchsde,google-research/torchsde,pytorch-utils,,https://github.com/google-research/torchsde,https://github.com/google-research/torchsde,Apache-2.0,2020-07-06 23:13:11.000,2024-05-25 02:57:17.000000,2023-09-26 23:11:11,163.0,,196.0,34.0,73.0,27.0,52.0,1547.0,Differentiable SDE solvers with GPU support and efficient sensitivity analysis.,8.0,28,True,2023-09-26 22:07:23.000,0.2.6,5.0,torchsde,conda-forge/torchsde,,['pytorch'],,1902041.0,3675.0,3638.0,https://pypi.org/project/torchsde,2023-09-26 21:52:19.000,37.0,1901435.0,https://anaconda.org/conda-forge/torchsde,2023-06-16 19:24:16.458,26668.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +382,TF Model Optimization,tensorflow/model-optimization,tensorflow-utils,,https://github.com/tensorflow/model-optimization,https://github.com/tensorflow/model-optimization,Apache-2.0,2018-10-31 20:34:28.000,2024-07-08 22:06:23.000000,2024-07-08 22:06:19,831.0,1.0,320.0,118.0,784.0,225.0,168.0,1487.0,"A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.",86.0,28,True,2024-02-08 02:06:46.000,0.8.0,31.0,tensorflow-model-optimization,,,['tensorflow'],,830093.0,45.0,,https://pypi.org/project/tensorflow-model-optimization,2024-02-08 01:57:17.000,45.0,830093.0,,,,2.0,,,,,,-5.0,,,,,,,,,,,,,,,,,,, +383,openTSNE,pavlin-policar/openTSNE,data-viz,,https://github.com/pavlin-policar/openTSNE,https://github.com/pavlin-policar/openTSNE,BSD-3-Clause,2018-06-08 18:42:09.000,2024-08-13 11:02:01.000000,2024-08-13 10:02:03,694.0,3.0,158.0,22.0,126.0,5.0,131.0,1441.0,"Extensible, parallel implementations of t-SNE.",12.0,28,True,2024-08-13 11:02:28.000,1.0.2,28.0,opentsne,conda-forge/opentsne,,,,44653.0,906.0,859.0,https://pypi.org/project/opentsne,2024-08-13 11:02:01.000,47.0,38473.0,https://anaconda.org/conda-forge/opentsne,2024-05-19 08:28:58.978,302826.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +384,minisom,JustGlowing/minisom,others,,https://github.com/JustGlowing/minisom,https://github.com/JustGlowing/minisom,CC-BY-3.0,2013-07-03 10:10:06.000,2024-08-28 13:05:22.000000,2024-08-28 13:05:21,610.0,18.0,417.0,31.0,51.0,16.0,128.0,1426.0,MiniSom is a minimalistic implementation of the Self Organizing Maps.,30.0,28,False,2024-08-23 12:23:48.000,2.3.3,26.0,minisom,,,,,22586.0,672.0,641.0,https://pypi.org/project/minisom,2024-08-23 12:22:45.000,31.0,22586.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +385,dstack,dstackai/dstack,others,,https://github.com/dstackai/dstack,https://github.com/dstackai/dstack,MPL-2.0,2022-01-04 10:29:46.000,2024-09-05 11:30:41.000000,2024-09-05 11:30:39,2068.0,205.0,98.0,10.0,765.0,92.0,788.0,1315.0,"A lightweight alternative to Kubernetes for AI, simplifying container orchestration on any cloud or on-premises and..",32.0,28,True,2024-09-04 12:15:41.000,0.18.12,225.0,dstack,,,,,3586.0,15.0,15.0,https://pypi.org/project/dstack,2024-09-04 11:24:25.000,,3586.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +386,empyrical,quantopian/empyrical,financial-data,,https://github.com/quantopian/empyrical,https://github.com/quantopian/empyrical,Apache-2.0,2016-03-18 10:22:52.000,2024-07-26 06:19:42.000000,2020-10-14 13:22:39,167.0,,396.0,71.0,89.0,36.0,26.0,1268.0,Common financial risk and performance metrics. Used by zipline and pyfolio.,23.0,28,False,2020-10-13 21:29:19.000,0.5.5,21.0,empyrical,conda-forge/empyrical,,,,22552.0,1508.0,1452.0,https://pypi.org/project/empyrical,2020-10-13 21:29:19.000,56.0,22189.0,https://anaconda.org/conda-forge/empyrical,2023-06-16 16:07:55.979,28736.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +387,PySwarms,ljvmiranda921/pyswarms,others,,https://github.com/ljvmiranda921/pyswarms,https://github.com/ljvmiranda921/pyswarms,MIT,2017-07-12 12:04:45.000,2024-08-06 17:18:34.000000,2023-06-06 09:46:40,415.0,,331.0,39.0,302.0,30.0,200.0,1261.0,A research toolkit for particle swarm optimization in Python.,45.0,28,False,2021-01-03 21:34:15.000,1.3.0,20.0,pyswarms,,,,,30447.0,447.0,425.0,https://pypi.org/project/pyswarms,2021-01-03 21:34:15.000,22.0,30447.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +388,Submit it,facebookincubator/submitit,distributed-ml,,https://github.com/facebookincubator/submitit,https://github.com/facebookincubator/submitit,MIT,2020-04-24 07:41:09.000,2024-08-30 21:02:45.000000,2024-07-29 16:12:37,144.0,5.0,119.0,24.0,107.0,43.0,74.0,1251.0,Python 3.8+ toolbox for submitting jobs to Slurm.,24.0,28,True,2023-11-09 17:23:02.000,1.5.1,23.0,submitit,conda-forge/submitit,,,,463843.0,3172.0,3127.0,https://pypi.org/project/submitit,2023-11-09 17:23:02.000,45.0,463029.0,https://anaconda.org/conda-forge/submitit,2023-11-24 07:58:55.401,39922.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +389,scikit-lego,koaning/scikit-lego,sklearn-utils,,https://github.com/koaning/scikit-lego,https://github.com/koaning/scikit-lego,MIT,2019-01-21 15:30:15.000,2024-08-21 11:39:17.000000,2024-08-21 11:39:14,534.0,16.0,116.0,26.0,384.0,31.0,285.0,1243.0,Extra blocks for scikit-learn pipelines.,67.0,28,True,2024-07-10 14:32:19.000,0.9.1,52.0,scikit-lego,conda-forge/scikit-lego,,['sklearn'],,28403.0,170.0,159.0,https://pypi.org/project/scikit-lego,2024-07-10 14:08:28.000,11.0,27359.0,https://anaconda.org/conda-forge/scikit-lego,2024-07-10 21:13:14.463,54308.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +390,kmodes,nicodv/kmodes,others,,https://github.com/nicodv/kmodes,https://github.com/nicodv/kmodes,MIT,2013-08-01 11:54:40.000,2024-06-19 19:59:13.000000,2024-01-17 21:03:09,532.0,,416.0,52.0,41.0,17.0,139.0,1238.0,"Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data.",22.0,28,True,2022-09-06 19:52:23.000,0.12.2,17.0,kmodes,conda-forge/kmodes,,,,243944.0,2834.0,2796.0,https://pypi.org/project/kmodes,2022-09-06 19:38:02.764,38.0,243036.0,https://anaconda.org/conda-forge/kmodes,2023-06-16 19:18:39.600,48157.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +391,Keras-Preprocessing,keras-team/keras-preprocessing,tensorflow-utils,,https://github.com/keras-team/keras-preprocessing,https://github.com/keras-team/keras-preprocessing,MIT,2018-05-30 22:43:36.000,2023-06-16 16:10:42.597000,2022-02-17 22:38:15,288.0,,444.0,43.0,176.0,93.0,102.0,1024.0,"Utilities for working with image data, text data, and sequence data.",52.0,28,False,2020-05-14 03:55:22.223,1.1.2,12.0,keras-preprocessing,conda-forge/keras-preprocessing,,['tensorflow'],,3898619.0,311.0,,https://pypi.org/project/keras-preprocessing,2020-05-14 03:55:22.223,311.0,3868046.0,https://anaconda.org/conda-forge/keras-preprocessing,2023-06-16 16:10:42.597,2293025.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +392,TensorFlow Transform,tensorflow/transform,tensorflow-utils,,https://github.com/tensorflow/transform,https://github.com/tensorflow/transform,Apache-2.0,2017-02-10 00:36:53.000,2024-08-16 06:28:21.000000,2024-04-30 20:12:21,936.0,,211.0,58.0,103.0,45.0,174.0,984.0,Input pipeline framework.,28.0,28,True,2024-04-24 22:55:08.000,1.15.0,57.0,tensorflow-transform,,,['tensorflow'],,541896.0,18.0,,https://pypi.org/project/tensorflow-transform,2024-04-24 22:55:08.000,18.0,541896.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +393,pythreejs,jupyter-widgets/pythreejs,data-viz,,https://github.com/jupyter-widgets/pythreejs,https://github.com/jupyter-widgets/pythreejs,BSD-3-Clause,2013-12-23 17:02:11.000,2024-09-03 21:38:15.000000,2023-02-20 00:24:10,1723.0,,185.0,41.0,175.0,65.0,174.0,941.0,A Jupyter - Three.js bridge.,30.0,28,False,2023-02-20 00:24:01.104,2.4.2,46.0,pythreejs,conda-forge/pythreejs,,['jupyter'],,80411.0,96.0,,https://pypi.org/project/pythreejs,2023-02-20 00:24:01.104,82.0,72749.0,https://anaconda.org/conda-forge/pythreejs,2023-06-16 13:16:30.947,588520.0,3.0,,,,,,,,,jupyter-threejs,https://www.npmjs.com/package/jupyter-threejs,2023-02-20 00:16:17.277,14.0,1777.0,,,,,,,,,,,, +394,CellProfiler,CellProfiler/CellProfiler,image,,https://github.com/CellProfiler/CellProfiler,https://github.com/CellProfiler/CellProfiler,BSD-3-Clause,2011-04-05 12:10:12.000,2024-08-30 01:23:38.000000,2024-08-30 01:23:17,16620.0,40.0,374.0,45.0,1646.0,309.0,2978.0,893.0,An open-source application for biological image analysis.,144.0,28,True,2024-07-29 23:00:49.000,4.2.7,34.0,cellprofiler,,,,7579.0,705.0,24.0,22.0,https://pypi.org/project/cellprofiler,2024-07-29 23:00:49.000,2.0,646.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +395,PyNNDescent,lmcinnes/pynndescent,nn-search,,https://github.com/lmcinnes/pynndescent,https://github.com/lmcinnes/pynndescent,BSD-2-Clause,2018-02-07 23:23:54.000,2024-06-17 19:35:33.219000,2024-06-17 15:09:18,679.0,5.0,105.0,14.0,99.0,73.0,66.0,878.0,A Python nearest neighbor descent for approximate nearest neighbors.,29.0,28,True,2024-06-17 15:48:31.000,0.5.13,32.0,pynndescent,conda-forge/pynndescent,,,,1694910.0,7747.0,7591.0,https://pypi.org/project/pynndescent,2024-06-17 15:48:31.000,156.0,1655022.0,https://anaconda.org/conda-forge/pynndescent,2024-06-17 19:35:33.219,1994437.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +396,Cornac,PreferredAI/cornac,recommender-systems,,https://github.com/PreferredAI/cornac,https://github.com/PreferredAI/cornac,Apache-2.0,2018-07-17 06:31:35.000,2024-09-04 03:39:02.000000,2024-09-04 03:39:02,1366.0,10.0,138.0,25.0,486.0,17.0,139.0,858.0,A Comparative Framework for Multimodal Recommender Systems.,22.0,28,True,2024-08-15 06:25:57.000,2.2.2,59.0,cornac,conda-forge/cornac,,,,52158.0,247.0,229.0,https://pypi.org/project/cornac,2024-08-15 06:52:10.000,18.0,41607.0,https://anaconda.org/conda-forge/cornac,2024-08-15 18:30:49.226,538145.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +397,CLTK,cltk/cltk,nlp,,https://github.com/cltk/cltk,https://github.com/cltk/cltk,MIT,2014-01-11 23:59:47.000,2024-08-18 16:23:07.000000,2024-05-12 22:59:32,3715.0,,328.0,65.0,690.0,36.0,533.0,832.0,The Classical Language Toolkit.,121.0,28,True,2024-05-13 16:48:36.000,1.2.6,217.0,cltk,,,,83.0,1570.0,286.0,271.0,https://pypi.org/project/cltk,2024-05-12 23:09:13.000,15.0,1570.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +398,Ciphey,Ciphey/Ciphey,nlp,,https://github.com/Ciphey/Ciphey,https://github.com/Ciphey/Ciphey,MIT,2019-07-16 20:20:39.000,2024-03-26 06:01:50.000000,2023-10-12 07:20:40,1894.0,,1131.0,239.0,455.0,72.0,264.0,17758.0,"Automatically decrypt encryptions without knowing the key or cipher, decode encodings, and crack hashes.",48.0,27,True,2021-06-06 17:15:00.281,5.14.0,50.0,ciphey,,,,,36595.0,,,https://pypi.org/project/ciphey,2021-06-06 17:15:00.281,,36186.0,,,,2.0,remnux/ciphey,https://hub.docker.com/r/remnux/ciphey,2023-10-14 18:53:31.974373,17.0,25404.0,,,,,,,,,,,,,,,,,,,, +399,PaddleDetection,PaddlePaddle/PaddleDetection,image,,https://github.com/PaddlePaddle/PaddleDetection,https://github.com/PaddlePaddle/PaddleDetection,Apache-2.0,2019-10-25 07:21:14.000,2024-09-04 14:27:06.000000,2024-07-11 14:30:01,2227.0,2.0,2847.0,197.0,3726.0,1237.0,4158.0,12561.0,"Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object..",160.0,27,True,2023-10-19 03:47:18.000,2.7.0,9.0,paddledet,,,['paddle'],,472.0,2.0,,https://pypi.org/project/paddledet,2022-09-19 20:42:09.271,2.0,472.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +400,Dopamine,google/dopamine,reinforcement-learning,,https://github.com/google/dopamine,https://github.com/google/dopamine,Apache-2.0,2018-07-26 09:58:36.000,2024-05-06 20:38:27.000000,2024-05-06 20:36:49,342.0,,1367.0,425.0,50.0,102.0,87.0,10442.0,Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.,15.0,27,True,2024-05-06 20:38:27.000,4.0.9,47.0,dopamine-rl,,,['tensorflow'],,32233.0,31.0,21.0,https://pypi.org/project/dopamine-rl,2024-05-06 20:38:27.000,10.0,32233.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +401,EfficientNet-PyTorch,lukemelas/EfficientNet-PyTorch,pytorch-utils,,https://github.com/lukemelas/EfficientNet-PyTorch,https://github.com/lukemelas/EfficientNet-PyTorch,Apache-2.0,2019-05-30 05:24:11.000,2022-04-08 12:30:25.000000,2021-04-15 15:16:36,162.0,,1523.0,131.0,51.0,163.0,141.0,7850.0,A PyTorch implementation of EfficientNet.,24.0,27,False,2021-04-15 15:17:23.000,0.7.1,13.0,efficientnet-pytorch,,,['pytorch'],4144590.0,246230.0,73.0,1.0,https://pypi.org/project/efficientnet-pytorch,2021-04-15 15:17:23.000,72.0,169479.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +402,TensorLayer,tensorlayer/tensorlayer,reinforcement-learning,,https://github.com/tensorlayer/TensorLayer,https://github.com/tensorlayer/TensorLayer,Apache-2.0,2016-06-07 15:55:16.000,2023-12-02 01:27:38.759000,2023-02-18 07:58:21,3353.0,,1609.0,458.0,699.0,33.0,441.0,7317.0,Deep Learning and Reinforcement Learning Library for Scientists and Engineers.,134.0,27,False,2022-02-15 02:05:47.000,2.2.5,84.0,tensorlayer,,,['tensorflow'],2349.0,2020.0,11.0,,https://pypi.org/project/tensorlayer,2022-02-15 02:05:47.000,11.0,1996.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +403,snownlp,isnowfy/snownlp,chinese-nlp,,https://github.com/isnowfy/snownlp,https://github.com/isnowfy/snownlp,MIT,2013-11-26 11:46:56.000,2020-01-19 02:39:05.000000,2020-01-19 02:39:03,57.0,,1354.0,350.0,14.0,42.0,66.0,6396.0,Python library for processing Chinese text.,8.0,27,False,2015-09-27 16:35:23.000,0.12.3,17.0,snownlp,,,,,24750.0,1420.0,1412.0,https://pypi.org/project/snownlp,2015-09-27 16:35:23.000,8.0,24750.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +404,scikit-surprise,NicolasHug/Surprise,recommender-systems,,https://github.com/NicolasHug/Surprise,https://github.com/NicolasHug/Surprise,BSD-3-Clause,2016-10-23 14:59:38.000,2024-06-16 11:25:37.000000,2024-06-14 19:31:58,659.0,1.0,1007.0,145.0,100.0,87.0,310.0,6338.0,A Python scikit for building and analyzing recommender systems.,46.0,27,True,2024-05-19 14:25:59.000,1.1.4,12.0,scikit-surprise,conda-forge/scikit-surprise,,,,87932.0,58.0,21.0,https://pypi.org/project/scikit-surprise,2024-05-19 14:25:59.000,37.0,79847.0,https://anaconda.org/conda-forge/scikit-surprise,2024-05-20 10:08:43.793,404286.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +405,NuPIC,numenta/nupic,ml-frameworks,,https://github.com/numenta/nupic-legacy,https://github.com/numenta/nupic-legacy,AGPL-3.0,2013-04-05 23:14:27.000,2023-09-01 15:42:16.000000,2023-08-31 21:49:25,6626.0,,1586.0,625.0,2111.0,453.0,1338.0,6334.0,"Numenta Platform for Intelligent Computing is an implementation of Hierarchical Temporal Memory (HTM), a theory of..",122.0,27,False,2018-06-01 15:39:25.550,1.0.5,53.0,nupic,,,,12.0,1120.0,21.0,21.0,https://pypi.org/project/nupic,2016-09-01 21:30:21.000,,1120.0,,,,3.0,,,,,,,,numenta/nupic-legacy,,,,,,,,,,,,,,,,, +406,FATE,FederatedAI/FATE,privacy-ml,,https://github.com/FederatedAI/FATE,https://github.com/FederatedAI/FATE,Apache-2.0,2019-01-24 10:32:43.000,2024-08-21 07:30:27.000000,2024-08-21 07:30:27,13839.0,64.0,1544.0,138.0,3616.0,55.0,1972.0,5639.0,An Industrial Grade Federated Learning Framework.,101.0,27,True,2024-07-31 11:47:02.000,2.2.0,51.0,ETAF,,,,,,,,https://pypi.org/project/ETAF,2020-05-06 09:35:40.000,,,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +407,flashtext,vi3k6i5/flashtext,nlp,,https://github.com/vi3k6i5/flashtext,https://github.com/vi3k6i5/flashtext,MIT,2017-08-15 18:03:01.000,2024-07-03 08:05:36.000000,2020-05-03 07:13:22,108.0,,599.0,142.0,31.0,69.0,55.0,5574.0,Extract Keywords from sentence or Replace keywords in sentences.,7.0,27,False,,,18.0,flashtext,conda-forge/flashtext,,,,1664624.0,1818.0,1762.0,https://pypi.org/project/flashtext,2018-02-16 05:24:17.000,56.0,1664234.0,https://anaconda.org/conda-forge/flashtext,2023-06-16 19:20:49.106,19505.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +408,keras-rl,keras-rl/keras-rl,reinforcement-learning,,https://github.com/keras-rl/keras-rl,https://github.com/keras-rl/keras-rl,MIT,2016-07-02 15:53:12.000,2023-09-17 12:33:41.000000,2019-11-11 22:14:54,308.0,,1362.0,200.0,158.0,49.0,227.0,5511.0,Deep Reinforcement Learning for Keras.,41.0,27,False,2018-06-01 07:52:24.000,0.4.2,8.0,keras-rl,,,['tensorflow'],,904.0,789.0,783.0,https://pypi.org/project/keras-rl,2018-06-01 07:52:24.000,6.0,904.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +409,Edward,blei-lab/edward,probabilistics,,https://github.com/blei-lab/edward,https://github.com/blei-lab/edward,Apache-2.0,2016-02-10 20:06:05.000,2024-03-18 16:23:03.000000,2018-07-25 01:28:08,1796.0,,780.0,272.0,438.0,221.0,329.0,4832.0,"A probabilistic programming language in TensorFlow. Deep generative models, variational inference.",87.0,27,False,2018-01-22 06:03:37.000,1.3.5,28.0,edward,,,['tensorflow'],24.0,544.0,330.0,328.0,https://pypi.org/project/edward,2018-01-22 06:03:05.000,2.0,544.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +410,VisualDL,PaddlePaddle/VisualDL,ml-experiments,,https://github.com/PaddlePaddle/VisualDL,https://github.com/PaddlePaddle/VisualDL,Apache-2.0,2017-12-20 12:34:31.000,2023-09-20 11:21:28.000000,2023-09-20 11:21:28,918.0,,634.0,147.0,789.0,141.0,356.0,4760.0,Deep Learning Visualization Toolkit.,33.0,27,True,2023-06-05 07:21:00.910,2.5.3,43.0,visualdl,,,['paddle'],430.0,154442.0,84.0,2.0,https://pypi.org/project/visualdl,2023-06-05 07:21:00.910,82.0,154434.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +411,vaderSentiment,cjhutto/vaderSentiment,nlp,,https://github.com/cjhutto/vaderSentiment,https://github.com/cjhutto/vaderSentiment,MIT,2014-11-17 16:31:45.000,2024-03-16 11:54:12.000000,2022-04-01 13:57:36,131.0,,999.0,147.0,31.0,52.0,77.0,4377.0,VADER Sentiment Analysis. VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based..,11.0,27,False,2020-05-22 15:07:00.000,3.3.2,15.0,vadersentiment,conda-forge/vadersentiment,,,,324160.0,9159.0,9064.0,https://pypi.org/project/vadersentiment,2020-05-22 15:07:00.000,95.0,323814.0,https://anaconda.org/conda-forge/vadersentiment,2023-06-16 19:25:16.902,14566.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +412,pytorch-summary,sksq96/pytorch-summary,pytorch-utils,,https://github.com/sksq96/pytorch-summary,https://github.com/sksq96/pytorch-summary,MIT,2018-04-23 13:58:04.000,2024-03-02 15:10:25.000000,2021-05-10 18:34:53,57.0,,412.0,37.0,56.0,138.0,43.0,3997.0,Model summary in PyTorch similar to `model.summary()` in Keras.,11.0,27,False,2018-09-26 05:07:28.000,1.5.1,12.0,torchsummary,,,['pytorch'],,206808.0,15780.0,15645.0,https://pypi.org/project/torchsummary,2018-09-26 05:07:28.000,135.0,206808.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +413,TensorFlowOnSpark,yahoo/TensorFlowOnSpark,distributed-ml,,https://github.com/yahoo/TensorFlowOnSpark,https://github.com/yahoo/TensorFlowOnSpark,Apache-2.0,2017-01-20 18:15:57.000,2023-07-10 10:34:11.000000,2023-04-27 20:08:56,632.0,,964.0,282.0,226.0,12.0,356.0,3871.0,TensorFlowOnSpark brings TensorFlow programs to Apache Spark clusters.,34.0,27,False,2022-04-21 20:41:22.000,2.2.5,32.0,tensorflowonspark,conda-forge/tensorflowonspark,,"['tensorflow', 'spark']",,662536.0,5.0,,https://pypi.org/project/tensorflowonspark,2022-04-21 20:05:56.000,5.0,662119.0,https://anaconda.org/conda-forge/tensorflowonspark,2023-06-16 16:19:28.736,23816.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +414,DeepKE,zjunlp/deepke,nlp,,https://github.com/zjunlp/DeepKE,https://github.com/zjunlp/DeepKE,MIT,2018-08-01 01:54:52.000,2024-09-04 09:06:07.000000,2024-09-04 09:06:06,1663.0,19.0,670.0,42.0,28.0,9.0,548.0,3374.0,[EMNLP 2022] An Open Toolkit for Knowledge Graph Extraction and Construction.,31.0,27,True,2023-09-21 04:12:03.000,2.2.7,111.0,deepke,,,['pytorch'],,1391.0,23.0,23.0,https://pypi.org/project/deepke,2023-09-21 04:12:03.000,,1391.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +415,Alphalens,quantopian/alphalens,financial-data,,https://github.com/quantopian/alphalens,https://github.com/quantopian/alphalens,Apache-2.0,2016-06-03 21:49:15.000,2024-02-12 06:44:22.000000,2020-04-27 18:40:41,522.0,,1130.0,167.0,215.0,49.0,146.0,3259.0,Performance analysis of predictive (alpha) stock factors.,26.0,27,False,2020-04-30 15:42:52.000,0.4.0,10.0,alphalens,conda-forge/alphalens,,,,1618.0,713.0,708.0,https://pypi.org/project/alphalens,2020-04-27 21:03:10.000,5.0,1342.0,https://anaconda.org/conda-forge/alphalens,2023-06-16 16:09:06.563,21805.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +416,Sweetviz,fbdesignpro/sweetviz,data-viz,,https://github.com/fbdesignpro/sweetviz,https://github.com/fbdesignpro/sweetviz,MIT,2020-05-09 15:25:47.000,2024-08-06 11:36:13.000000,2023-11-29 13:26:08,135.0,,272.0,52.0,20.0,41.0,97.0,2892.0,"Visualize and compare datasets, target values and associations, with one line of code.",11.0,27,True,2023-11-29 13:30:45.000,2.3.1,35.0,sweetviz,conda-forge/sweetviz,,,,72195.0,2478.0,2448.0,https://pypi.org/project/sweetviz,2023-11-29 13:27:52.000,30.0,71421.0,https://anaconda.org/conda-forge/sweetviz,2023-12-04 12:10:57.449,33291.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +417,TextAttack,QData/TextAttack,adversarial,,https://github.com/QData/TextAttack,https://github.com/QData/TextAttack,MIT,2019-10-15 00:51:44.000,2024-07-25 18:53:58.000000,2024-07-25 18:53:58,2707.0,2.0,381.0,38.0,521.0,58.0,217.0,2886.0,"TextAttack is a Python framework for adversarial attacks, data augmentation, and model training in NLP..",66.0,27,True,2024-03-11 02:20:29.000,0.3.10,47.0,textattack,conda-forge/textattack,,,,3888.0,298.0,287.0,https://pypi.org/project/textattack,2024-03-11 02:20:29.000,11.0,3716.0,https://anaconda.org/conda-forge/textattack,2023-06-16 19:22:50.186,8279.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +418,IB-insync,erdewit/ib_insync,financial-data,,https://github.com/erdewit/ib_insync,https://github.com/erdewit/ib_insync,BSD-2-Clause,2017-07-12 12:09:24.000,2024-03-14 19:50:06.000000,2024-03-14 19:50:06,769.0,,740.0,180.0,75.0,21.0,565.0,2800.0,Python sync/async framework for Interactive Brokers API.,36.0,27,True,2023-07-02 12:44:10.283,0.9.86,111.0,ib_insync,conda-forge/ib-insync,,,,33054.0,44.0,,https://pypi.org/project/ib_insync,2022-11-21 09:32:01.715,44.0,32316.0,https://anaconda.org/conda-forge/ib-insync,2023-06-16 16:16:07.159,45761.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +419,Neural Network Libraries,sony/nnabla,ml-frameworks,,https://github.com/sony/nnabla,https://github.com/sony/nnabla,Apache-2.0,2017-06-26 01:07:10.000,2024-06-20 23:39:09.000000,2024-06-20 23:39:05,3544.0,3.0,333.0,153.0,1179.0,35.0,60.0,2720.0,Neural Network Libraries.,76.0,27,True,2024-05-29 05:14:17.000,1.39.0,79.0,nnabla,,,,923.0,2975.0,44.0,,https://pypi.org/project/nnabla,2024-05-29 02:51:02.000,44.0,2965.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +420,Foolbox,bethgelab/foolbox,adversarial,,https://github.com/bethgelab/foolbox,https://github.com/bethgelab/foolbox,MIT,2017-06-14 13:05:48.000,2024-04-03 16:17:05.000000,2024-03-04 15:46:26,1711.0,,421.0,45.0,365.0,22.0,350.0,2713.0,"A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX.",35.0,27,True,2024-03-04 20:59:17.000,3.3.4,71.0,foolbox,conda-forge/foolbox,,,,3442.0,634.0,620.0,https://pypi.org/project/foolbox,2024-03-04 20:59:17.000,14.0,3152.0,https://anaconda.org/conda-forge/foolbox,2023-06-16 19:20:41.396,14533.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +421,EvaDB,georgia-tech-db/eva,ml-frameworks,,https://github.com/georgia-tech-db/evadb,https://github.com/georgia-tech-db/evadb,Apache-2.0,2018-09-10 02:26:03.000,2024-05-17 16:33:06.000000,2023-12-03 09:09:14,2415.0,,256.0,27.0,1132.0,77.0,224.0,2622.0,Database system for AI-powered apps.,73.0,27,True,2023-11-19 16:35:30.000,0.3.9,45.0,evadb,,,['pytorch'],414528.0,16482.0,147.0,147.0,https://pypi.org/project/evadb,2023-11-19 16:35:24.000,,539.0,,,,3.0,,,,,,,,georgia-tech-db/evadb,,,,,,,,,,,,,,,,, +422,adapter-transformers,Adapter-Hub/adapter-transformers,others,,https://github.com/adapter-hub/adapters,https://github.com/adapter-hub/adapters,Apache-2.0,2020-04-21 16:21:43.000,2024-08-22 18:44:14.000000,2024-08-22 18:30:45,140.0,29.0,336.0,31.0,325.0,41.0,340.0,2516.0,A Unified Library for Parameter-Efficient and Modular Transfer Learning.,13.0,27,True,2024-08-10 15:47:41.000,1.0.0,21.0,adapter-transformers,,,['huggingface'],,20882.0,108.0,96.0,https://pypi.org/project/adapter-transformers,2024-07-07 11:49:43.000,12.0,20882.0,,,,3.0,,,,,,,,adapter-hub/adapters,,,,,,,,,,,,,,,,, +423,Fairness 360,Trusted-AI/AIF360,interpretability,,https://github.com/Trusted-AI/AIF360,https://github.com/Trusted-AI/AIF360,Apache-2.0,2018-08-22 20:47:15.000,2024-07-05 14:45:32.000000,2024-07-05 14:45:32,437.0,1.0,827.0,89.0,286.0,199.0,103.0,2401.0,"A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and..",73.0,27,True,2024-04-08 20:03:12.000,0.6.1,12.0,aif360,conda-forge/aif360,,,,33018.0,504.0,472.0,https://pypi.org/project/aif360,2024-04-08 20:03:12.000,32.0,32730.0,https://anaconda.org/conda-forge/aif360,2024-04-09 06:44:48.814,13868.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +424,textacy,chartbeat-labs/textacy,nlp,,https://github.com/chartbeat-labs/textacy,https://github.com/chartbeat-labs/textacy,,2016-02-03 16:52:45.000,2023-09-22 23:38:28.000000,2023-04-03 00:19:55,1816.0,,255.0,87.0,124.0,33.0,230.0,2201.0,"NLP, before and after spaCy.",35.0,27,False,2023-04-02 23:06:15.139,0.13.0,32.0,textacy,conda-forge/textacy,,,,28033.0,1921.0,1855.0,https://pypi.org/project/textacy,2023-04-02 23:06:15.139,66.0,26224.0,https://anaconda.org/conda-forge/textacy,2023-06-16 13:22:44.862,159230.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +425,modAL,modAL-python/modAL,others,,https://github.com/modAL-python/modAL,https://github.com/modAL-python/modAL,MIT,2017-11-14 14:01:15.000,2024-09-05 15:01:30.000000,2023-06-01 12:18:23,739.0,,316.0,43.0,44.0,99.0,56.0,2191.0,A modular active learning framework for Python.,20.0,27,False,2024-09-05 15:01:30.000,0.64.84,1208.0,modAL,,,['sklearn'],39.0,328774.0,53.0,,https://pypi.org/project/modAL,2024-09-05 15:01:30.000,53.0,328774.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +426,mtcnn,ipazc/mtcnn,image,,https://github.com/ipazc/mtcnn,https://github.com/ipazc/mtcnn,MIT,2018-01-05 04:08:32.000,2024-04-26 00:01:37.000000,2021-07-09 11:06:18,56.0,,523.0,43.0,25.0,74.0,38.0,2182.0,"MTCNN face detection implementation for TensorFlow, as a PIP package.",15.0,27,False,2021-07-09 11:16:39.000,0.1.1,11.0,mtcnn,conda-forge/mtcnn,,['tensorflow'],,110145.0,5982.0,5911.0,https://pypi.org/project/mtcnn,2021-07-09 11:16:39.000,71.0,109911.0,https://anaconda.org/conda-forge/mtcnn,2023-06-16 19:18:00.316,12873.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +427,Hyperas,maxpumperla/hyperas,hyperopt,,https://github.com/maxpumperla/hyperas,https://github.com/maxpumperla/hyperas,MIT,2016-02-19 14:45:10.000,2023-01-05 06:02:49.000000,2023-01-05 06:02:49,213.0,,317.0,63.0,38.0,97.0,160.0,2176.0,Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization.,22.0,27,False,2019-02-28 09:16:54.000,0.4.1,9.0,hyperas,,,['tensorflow'],,12292.0,378.0,372.0,https://pypi.org/project/hyperas,2019-02-28 09:16:54.000,6.0,12292.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +428,Pillow-SIMD,uploadcare/pillow-simd,image,,https://github.com/uploadcare/pillow-simd,https://github.com/uploadcare/pillow-simd,PIL,2014-11-12 15:33:02.000,2024-09-04 21:04:43.000000,2024-08-23 09:42:27,14659.0,12.0,84.0,42.0,53.0,15.0,78.0,2139.0,The friendly PIL fork.,435.0,27,False,,,66.0,pillow-simd,,,,,27287.0,65.0,,https://pypi.org/project/pillow-simd,2024-08-23 09:48:44.000,65.0,27287.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +429,Labml,labmlai/labml,ml-experiments,,https://github.com/labmlai/labml,https://github.com/labmlai/labml,MIT,2018-11-16 09:34:48.000,2024-09-03 12:39:56.000000,2024-09-03 12:39:51,2211.0,143.0,132.0,28.0,244.0,5.0,42.0,1986.0,Monitor deep learning model training and hardware usage from your mobile phone.,9.0,27,True,2024-05-23 20:28:44.000,0.5.2,146.0,labml,,,,,3204.0,180.0,166.0,https://pypi.org/project/labml,2024-05-23 20:28:44.000,14.0,3204.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +430,petastorm,uber/petastorm,distributed-ml,,https://github.com/uber/petastorm,https://github.com/uber/petastorm,Apache-2.0,2018-06-15 23:15:29.000,2023-12-02 05:11:31.000000,2023-12-02 05:11:31,691.0,,279.0,40.0,495.0,172.0,151.0,1778.0,Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets..,50.0,27,True,2022-12-16 20:54:02.878,0.12.1,86.0,petastorm,,,,478.0,148181.0,186.0,178.0,https://pypi.org/project/petastorm,2023-02-03 00:33:00.499,8.0,148175.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +431,lightning-flash,Lightning-AI/lightning-flash,pytorch-utils,,https://github.com/Lightning-Universe/lightning-flash,https://github.com/Lightning-Universe/lightning-flash,Apache-2.0,2021-01-28 18:47:16.000,2023-10-08 14:28:44.000000,2023-10-08 14:28:43,1157.0,,213.0,36.0,1081.0,25.0,496.0,1737.0,Your PyTorch AI Factory - Flash enables you to easily configure and run complex AI recipes for over 15 tasks across 7..,87.0,27,True,2023-06-30 13:37:19.283,0.8.2,40.0,lightning-flash,conda-forge/lightning-flash,,['pytorch'],,1955.0,298.0,293.0,https://pypi.org/project/lightning-flash,2022-05-11 18:17:54.000,5.0,1374.0,https://anaconda.org/conda-forge/lightning-flash,2023-07-04 02:12:18.993,21518.0,2.0,,,,,,,,Lightning-Universe/lightning-flash,,,,,,,,,,,,,,,,, +432,cuGraph,rapidsai/cugraph,gpu-utilities,,https://github.com/rapidsai/cugraph,https://github.com/rapidsai/cugraph,Apache-2.0,2018-11-15 18:07:11.000,2024-09-05 14:40:14.000000,2024-09-03 18:03:22,6569.0,112.0,297.0,45.0,2883.0,178.0,1560.0,1668.0,cuGraph - RAPIDS Graph Analytics Library.,115.0,27,True,2024-08-08 02:37:35.000,24.08.00,39.0,cugraph,conda-forge/libcugraph,,,,760.0,4.0,,https://pypi.org/project/cugraph,2020-06-01 20:09:06.000,4.0,206.0,https://anaconda.org/conda-forge/libcugraph,2023-06-16 19:25:39.870,22745.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +433,chainercv,chainer/chainercv,image,,https://github.com/chainer/chainercv,https://github.com/chainer/chainercv,MIT,2017-02-13 04:15:10.000,2021-07-01 16:54:50.000000,2020-01-07 11:48:31,4930.0,,312.0,73.0,742.0,58.0,168.0,1482.0,ChainerCV: a Library for Deep Learning in Computer Vision.,39.0,27,False,2019-06-12 11:55:40.000,0.13.1,25.0,chainercv,,,,,1463.0,408.0,406.0,https://pypi.org/project/chainercv,2019-06-12 11:55:40.000,2.0,1463.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +434,keras-ocr,faustomorales/keras-ocr,ocr,,https://github.com/faustomorales/keras-ocr,https://github.com/faustomorales/keras-ocr,MIT,2019-09-20 23:08:50.000,2024-08-01 05:16:36.000000,2023-11-06 15:20:05,206.0,,330.0,50.0,44.0,99.0,114.0,1383.0,A packaged and flexible version of the CRAFT text detector and Keras CRNN recognition model.,18.0,27,True,2023-11-06 16:35:44.000,0.9.3,33.0,keras-ocr,anaconda/keras-ocr,,['tensorflow'],1637405.0,68867.0,557.0,549.0,https://pypi.org/project/keras-ocr,2023-11-06 16:35:44.000,8.0,34748.0,https://anaconda.org/anaconda/keras-ocr,2023-06-16 19:23:39.693,327.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +435,underthesea,undertheseanlp/underthesea,nlp,,https://github.com/undertheseanlp/underthesea,https://github.com/undertheseanlp/underthesea,GPL-3.0,2017-03-01 10:24:26.000,2024-06-22 10:18:00.000000,2024-06-22 10:17:04,858.0,7.0,270.0,77.0,487.0,53.0,202.0,1370.0,Underthesea - Vietnamese NLP Toolkit.,19.0,27,False,2024-06-22 10:18:00.000,6.8.4,127.0,underthesea,,,,6885.0,21759.0,1192.0,1181.0,https://pypi.org/project/underthesea,2024-06-22 10:18:00.000,11.0,21681.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +436,responsible-ai-widgets,microsoft/responsible-ai-toolbox,interpretability,,https://github.com/microsoft/responsible-ai-toolbox,https://github.com/microsoft/responsible-ai-toolbox,MIT,2020-07-06 20:46:53.000,2024-08-09 14:16:22.000000,2024-08-07 01:34:48,1970.0,6.0,343.0,31.0,2278.0,86.0,229.0,1325.0,Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and..,43.0,27,True,2024-07-08 18:03:34.000,0.36.0,57.0,raiwidgets,,,"['pytorch', 'tensorflow', 'jupyter']",,10455.0,6.0,,https://pypi.org/project/raiwidgets,2024-07-08 16:42:42.000,6.0,10455.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +437,Madmom,CPJKU/madmom,audio,,https://github.com/CPJKU/madmom,https://github.com/CPJKU/madmom,BSD-3-Clause,2015-09-08 08:19:06.000,2024-08-25 11:43:40.000000,2024-08-25 11:43:40,1753.0,1.0,202.0,43.0,258.0,68.0,213.0,1302.0,Python audio and music signal processing library.,24.0,27,True,2018-11-14 14:57:41.000,0.16.1,11.0,madmom,,,,,1980.0,458.0,431.0,https://pypi.org/project/madmom,2018-11-14 14:56:22.000,27.0,1980.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +438,fancyimpute,iskandr/fancyimpute,sklearn-utils,,https://github.com/iskandr/fancyimpute,https://github.com/iskandr/fancyimpute,Apache-2.0,2015-11-05 23:39:34.000,2023-10-25 17:26:07.000000,2021-10-21 17:45:17,202.0,,174.0,25.0,36.0,1.0,116.0,1245.0,Multivariate imputation and matrix completion algorithms implemented in Python.,11.0,27,False,2021-10-21 17:50:40.000,0.7.0,29.0,fancyimpute,,,['sklearn'],,79584.0,1679.0,1658.0,https://pypi.org/project/fancyimpute,2021-10-21 17:50:40.000,21.0,79584.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +439,pyclustering,annoviko/pyclustering,others,,https://github.com/annoviko/pyclustering,https://github.com/annoviko/pyclustering,BSD-3-Clause,2014-02-25 18:59:03.000,2024-02-25 11:40:08.000000,2024-02-08 16:58:25,2080.0,,250.0,41.0,39.0,76.0,591.0,1158.0,"pyclustering is a Python, C++ data mining library.",26.0,27,True,2020-11-25 22:33:07.000,0.10.1.2,46.0,pyclustering,conda-forge/pyclustering,,,581.0,25194.0,752.0,720.0,https://pypi.org/project/pyclustering,2020-11-25 22:41:20.000,32.0,23503.0,https://anaconda.org/conda-forge/pyclustering,2023-11-16 19:00:50.847,84263.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +440,bambi,bambinos/bambi,probabilistics,,https://github.com/bambinos/bambi,https://github.com/bambinos/bambi,MIT,2016-05-16 03:21:00.000,2024-09-05 14:13:02.000000,2024-09-05 14:11:35,820.0,11.0,121.0,31.0,422.0,79.0,330.0,1060.0,BAyesian Model-Building Interface (Bambi) in Python.,39.0,27,True,2024-07-10 09:48:04.000,0.14.0,29.0,bambi,conda-forge/bambi,,,,29242.0,151.0,141.0,https://pypi.org/project/bambi,2024-07-10 09:48:04.000,10.0,28439.0,https://anaconda.org/conda-forge/bambi,2024-07-10 16:37:21.380,36170.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +441,pyRiemann,pyRiemann/pyRiemann,ml-frameworks,,https://github.com/pyRiemann/pyRiemann,https://github.com/pyRiemann/pyRiemann,BSD-3-Clause,2015-04-19 16:01:44.000,2024-08-26 20:12:53.000000,2024-08-26 20:12:53,623.0,12.0,162.0,31.0,215.0,4.0,103.0,623.0,Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python.,34.0,27,True,2024-04-10 11:45:27.000,0.6,12.0,pyriemann,conda-forge/pyriemann,https://pyriemann.readthedocs.io/en/latest/,['sklearn'],,31673.0,410.0,382.0,https://pypi.org/project/pyriemann,2024-04-10 11:46:01.000,28.0,31392.0,https://anaconda.org/conda-forge/pyriemann,2024-04-10 14:21:44.720,7590.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +442,sklearn-crfsuite,TeamHG-Memex/sklearn-crfsuite,sklearn-utils,,https://github.com/TeamHG-Memex/sklearn-crfsuite,https://github.com/TeamHG-Memex/sklearn-crfsuite,MIT,2015-11-26 21:15:41.000,2024-06-18 11:08:22.000000,2019-12-05 08:17:22,46.0,,217.0,22.0,17.0,46.0,23.0,426.0,scikit-learn inspired API for CRFsuite.,6.0,27,False,2024-06-18 11:08:22.000,0.5.0,11.0,sklearn-crfsuite,conda-forge/sklearn-crfsuite,,['sklearn'],,218487.0,7980.0,7843.0,https://pypi.org/project/sklearn-crfsuite,2024-06-18 11:08:22.000,137.0,217721.0,https://anaconda.org/conda-forge/sklearn-crfsuite,2023-06-16 19:18:37.991,40648.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +443,english-words,dwyl/english-words,nlp,,https://github.com/dwyl/english-words,https://github.com/dwyl/english-words,Unlicense,2014-07-13 22:20:45.000,2024-06-16 11:20:30.000000,2024-06-16 11:20:30,100.0,1.0,1815.0,206.0,73.0,113.0,37.0,10449.0,A text file containing 479k English words for all your dictionary/word-based projects e.g: auto-completion /..,32.0,26,True,2023-05-24 15:11:00.531,2.0.1,9.0,english-words,,,,,64121.0,16.0,2.0,https://pypi.org/project/english-words,2023-05-24 15:11:00.531,14.0,64121.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +444,TTS,mozilla/TTS,audio,,https://github.com/mozilla/TTS,https://github.com/mozilla/TTS,MPL-2.0,2018-01-23 14:22:06.000,2023-11-09 15:37:59.000000,2021-02-12 10:36:31,2184.0,,1203.0,186.0,213.0,28.0,534.0,9210.0,Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts).,56.0,26,False,2021-01-29 00:03:56.000,0.0.9,1.0,,,,,12287.0,279.0,21.0,21.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +445,Trax,google/trax,others,,https://github.com/google/trax,https://github.com/google/trax,Apache-2.0,2019-10-05 15:09:14.000,2024-08-21 22:24:55.000000,2024-08-21 22:24:50,1623.0,4.0,814.0,144.0,1568.0,122.0,125.0,8031.0,Trax Deep Learning with Clear Code and Speed.,80.0,26,True,2021-10-26 20:29:38.000,1.4.1,24.0,trax,,,,,4064.0,169.0,168.0,https://pypi.org/project/trax,2021-10-26 20:29:00.538,1.0,4064.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +446,yellowbrick,DistrictDataLabs/yellowbrick,interpretability,,https://github.com/DistrictDataLabs/yellowbrick,https://github.com/DistrictDataLabs/yellowbrick,Apache-2.0,2016-05-18 14:12:17.000,2023-07-29 21:28:21.000000,2023-07-05 18:14:28,901.0,,554.0,104.0,617.0,98.0,607.0,4262.0,Visual analysis and diagnostic tools to facilitate machine learning model selection.,113.0,26,False,2022-08-21 12:49:43.000,1.5,24.0,yellowbrick,conda-forge/yellowbrick,,['sklearn'],,383420.0,104.0,,https://pypi.org/project/yellowbrick,2022-08-21 16:11:55.287,104.0,381733.0,https://anaconda.org/conda-forge/yellowbrick,2023-06-16 19:21:13.554,82694.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +447,LIT,PAIR-code/lit,interpretability,,https://github.com/PAIR-code/lit,https://github.com/PAIR-code/lit,Apache-2.0,2020-07-28 13:07:26.000,2024-09-05 14:19:47.000000,2024-06-26 19:01:50,1492.0,36.0,353.0,67.0,1417.0,109.0,85.0,3454.0,The Learning Interpretability Tool: Interactively analyze ML models to understand their behavior in an extensible and..,38.0,26,True,2024-06-26 16:33:42.000,1.2,17.0,lit-nlp,conda-forge/lit-nlp,,,,5983.0,41.0,38.0,https://pypi.org/project/lit-nlp,2024-06-26 16:32:34.000,3.0,4187.0,https://anaconda.org/conda-forge/lit-nlp,2023-06-16 19:21:41.530,86218.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +448,TensorForce,tensorforce/tensorforce,reinforcement-learning,,https://github.com/tensorforce/tensorforce,https://github.com/tensorforce/tensorforce,Apache-2.0,2017-03-19 16:24:22.000,2024-07-31 20:26:54.000000,2024-07-31 20:26:47,2116.0,2.0,532.0,141.0,240.0,42.0,635.0,3293.0,Tensorforce: a TensorFlow library for applied reinforcement learning.,85.0,26,True,2021-08-30 20:20:58.000,0.6.5,24.0,tensorforce,,,['tensorflow'],,656.0,455.0,451.0,https://pypi.org/project/tensorforce,2021-08-30 20:13:45.000,4.0,656.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +449,SHOGUN,shogun-toolbox/shogun,ml-frameworks,,https://github.com/shogun-toolbox/shogun,https://github.com/shogun-toolbox/shogun,BSD-3-Clause,2011-04-01 10:44:32.000,2023-12-19 18:37:18.000000,2023-12-19 18:37:18,17589.0,,1050.0,216.0,3649.0,429.0,1111.0,3025.0,Unified and efficient Machine Learning.,248.0,26,True,2019-07-05 10:23:31.000,shogun_6.1.4,10.0,,conda-forge/shogun,,,,1674.0,,,,,,,https://anaconda.org/conda-forge/shogun,2023-06-16 13:22:38.816,143244.0,3.0,shogun/shogun,https://hub.docker.com/r/shogun/shogun,2019-01-31 13:45:10.435327,1.0,1513.0,,,,,,,,,shogun,,,,,,,,,,, +450,pytorch-optimizer,jettify/pytorch-optimizer,pytorch-utils,,https://github.com/jettify/pytorch-optimizer,https://github.com/jettify/pytorch-optimizer,Apache-2.0,2020-01-03 03:16:39.000,2024-03-22 11:10:03.000000,2023-06-20 03:14:12,435.0,,295.0,33.0,476.0,54.0,30.0,3010.0,torch-optimizer -- collection of optimizers for Pytorch.,26.0,26,False,2021-10-31 03:00:19.000,0.3.0,21.0,torch_optimizer,conda-forge/torch-optimizer,,['pytorch'],,147684.0,86.0,,https://pypi.org/project/torch_optimizer,2021-10-31 03:00:19.000,86.0,147409.0,https://anaconda.org/conda-forge/torch-optimizer,2023-06-16 19:25:40.043,11304.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +451,lazypredict,shankarpandala/lazypredict,hyperopt,,https://github.com/shankarpandala/lazypredict,https://github.com/shankarpandala/lazypredict,MIT,2019-11-16 09:56:35.000,2024-06-02 15:40:01.000000,2024-06-02 15:40:01,251.0,,326.0,30.0,321.0,81.0,39.0,2863.0,Lazy Predict help build a lot of basic models without much code and helps understand which models works better without..,18.0,26,True,2022-09-28 08:51:19.531,0.2.12,12.0,lazypredict,conda-forge/lazypredict,,['sklearn'],,17192.0,1050.0,1049.0,https://pypi.org/project/lazypredict,2022-09-28 08:51:19.531,1.0,17100.0,https://anaconda.org/conda-forge/lazypredict,2023-06-16 19:27:14.287,3413.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +452,knockknock,huggingface/knockknock,ml-experiments,,https://github.com/huggingface/knockknock,https://github.com/huggingface/knockknock,MIT,2019-03-20 13:08:55.000,2023-06-23 10:52:46.000000,2020-03-16 04:26:47,75.0,,223.0,64.0,42.0,17.0,24.0,2778.0,Knock Knock: Get notified when your training ends with only two additional lines of code.,20.0,26,False,2020-03-04 04:15:47.000,0.1.8,10.0,knockknock,conda-forge/knockknock,,,,85758.0,1112.0,1107.0,https://pypi.org/project/knockknock,2020-03-16 14:30:23.000,5.0,85490.0,https://anaconda.org/conda-forge/knockknock,2023-06-16 16:18:44.705,15843.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +453,m2cgen,BayesWitnesses/m2cgen,model-serialisation,,https://github.com/BayesWitnesses/m2cgen,https://github.com/BayesWitnesses/m2cgen,MIT,2019-01-13 02:32:55.000,2024-08-03 17:30:36.000000,2022-10-05 16:26:03,376.0,,234.0,51.0,482.0,45.0,70.0,2778.0,"Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart,..",14.0,26,False,2022-04-26 01:24:34.000,0.10.0,13.0,m2cgen,,,,75.0,27233.0,255.0,252.0,https://pypi.org/project/m2cgen,2022-04-26 01:24:34.000,3.0,27232.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +454,eli5,TeamHG-Memex/eli5,interpretability,,https://github.com/TeamHG-Memex/eli5,https://github.com/TeamHG-Memex/eli5,MIT,2016-09-15 01:04:57.000,2023-06-16 13:18:29.838000,2020-01-22 07:39:36,1198.0,,329.0,67.0,167.0,164.0,113.0,2752.0,A library for debugging/inspecting machine learning classifiers and explaining their predictions.,14.0,26,False,2022-05-11 09:37:12.000,0.13.0,30.0,eli5,conda-forge/eli5,,,,235172.0,60.0,,https://pypi.org/project/eli5,2022-05-11 09:37:12.000,60.0,233335.0,https://anaconda.org/conda-forge/eli5,2023-06-16 13:18:29.838,161708.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +455,TF Ranking,tensorflow/ranking,recommender-systems,,https://github.com/tensorflow/ranking,https://github.com/tensorflow/ranking,Apache-2.0,2018-12-03 20:48:57.000,2024-03-18 21:00:38.000000,2024-03-18 20:31:55,556.0,,473.0,97.0,43.0,89.0,240.0,2736.0,Learning to Rank in TensorFlow.,34.0,26,True,2024-03-18 21:00:38.000,0.5.5,23.0,tensorflow_ranking,,,['tensorflow'],,99151.0,15.0,,https://pypi.org/project/tensorflow_ranking,2024-03-18 21:00:38.000,15.0,99151.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +456,TabNet,dreamquark-ai/tabnet,pytorch-utils,,https://github.com/dreamquark-ai/tabnet,https://github.com/dreamquark-ai/tabnet,MIT,2019-10-17 11:17:32.000,2024-08-30 08:05:48.000000,2023-07-23 14:42:27,191.0,,481.0,38.0,248.0,52.0,287.0,2589.0,PyTorch implementation of TabNet paper : https://arxiv.org/pdf/1908.07442.pdf.,21.0,26,False,2023-07-23 13:34:05.000,4.1.0,19.0,pytorch-tabnet,conda-forge/pytorch-tabnet,,['pytorch'],,40114.0,11.0,,https://pypi.org/project/pytorch-tabnet,2023-07-23 13:26:57.000,11.0,39876.0,https://anaconda.org/conda-forge/pytorch-tabnet,2023-12-20 04:10:30.919,7879.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +457,Enigma Catalyst,scrtlabs/catalyst,financial-data,,https://github.com/scrtlabs/catalyst,https://github.com/scrtlabs/catalyst,Apache-2.0,2017-06-13 22:31:34.000,2022-11-26 14:07:55.000000,2021-09-22 15:31:55,6364.0,,719.0,166.0,94.0,136.0,358.0,2485.0,An Algorithmic Trading Library for Crypto-Assets in Python.,152.0,26,False,2018-11-11 16:46:28.000,0.5.21,52.0,enigma-catalyst,,,,,465.0,28.0,26.0,https://pypi.org/project/enigma-catalyst,2018-11-11 16:46:28.000,2.0,465.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +458,Norfair,tryolabs/norfair,image,,https://github.com/tryolabs/norfair,https://github.com/tryolabs/norfair,BSD-3-Clause,2020-07-01 20:15:44.000,2024-07-27 16:14:52.000000,2024-07-27 16:14:15,696.0,1.0,238.0,35.0,147.0,24.0,145.0,2369.0,Lightweight Python library for adding real-time multi-object tracking to any detector.,31.0,26,True,2023-01-04 21:42:02.301,2.2.0,19.0,norfair,,,,325.0,19590.0,225.0,218.0,https://pypi.org/project/norfair,2022-05-30 21:14:58.000,7.0,19584.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +459,polyglot,aboSamoor/polyglot,nlp,,https://github.com/aboSamoor/polyglot,https://github.com/aboSamoor/polyglot,GPL-3.0,2014-06-30 02:07:45.000,2023-11-10 03:06:08.000000,2020-09-22 22:35:28,271.0,,337.0,77.0,55.0,169.0,68.0,2300.0,Multilingual text (NLP) processing toolkit.,26.0,26,False,2021-12-15 16:11:38.716,15.5.1,9.0,polyglot,,,,,44018.0,1394.0,1345.0,https://pypi.org/project/polyglot,2021-12-15 16:11:38.716,49.0,44018.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +460,PyTextRank,DerwenAI/pytextrank,nlp,,https://github.com/DerwenAI/pytextrank,https://github.com/DerwenAI/pytextrank,MIT,2016-10-02 18:39:12.000,2024-07-16 08:39:07.000000,2024-05-21 15:42:46,481.0,,336.0,64.0,160.0,13.0,92.0,2130.0,Python implementation of TextRank algorithms (textgraphs) for phrase extraction.,19.0,26,True,2024-02-21 23:17:37.000,3.3.0,22.0,pytextrank,,,,,50503.0,723.0,704.0,https://pypi.org/project/pytextrank,2024-02-21 23:17:37.000,19.0,50503.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +461,efficientnet,qubvel/efficientnet,tensorflow-utils,,https://github.com/qubvel/efficientnet,https://github.com/qubvel/efficientnet,Apache-2.0,2019-05-30 20:21:09.000,2024-04-08 21:03:52.579000,2021-07-16 09:03:20,66.0,,463.0,38.0,43.0,64.0,58.0,2066.0,Implementation of EfficientNet model. Keras and TensorFlow Keras.,10.0,26,False,2020-09-15 16:26:00.000,1.1.1,9.0,efficientnet,anaconda/efficientnet,,['tensorflow'],259869.0,95354.0,2260.0,2246.0,https://pypi.org/project/efficientnet,2020-09-15 16:26:00.000,14.0,91283.0,https://anaconda.org/anaconda/efficientnet,2024-04-08 21:03:52.579,513.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +462,TensorFlow Privacy,tensorflow/privacy,privacy-ml,,https://github.com/tensorflow/privacy,https://github.com/tensorflow/privacy,Apache-2.0,2018-12-21 18:46:46.000,2024-09-04 19:43:13.000000,2024-09-04 19:42:12,887.0,17.0,444.0,60.0,356.0,117.0,92.0,1915.0,Library for training machine learning models with privacy for training data.,59.0,26,True,2024-02-14 19:18:00.000,0.9.0,31.0,tensorflow-privacy,,,['tensorflow'],168.0,19817.0,21.0,,https://pypi.org/project/tensorflow-privacy,2024-02-14 19:08:50.000,21.0,19815.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +463,Feature Engine,solegalli/feature_engine,others,,https://github.com/solegalli/feature_engine,https://github.com/solegalli/feature_engine,BSD-3-Clause,2020-08-06 19:43:35.639,2024-09-04 08:38:12.000000,2024-08-31 13:01:11,360.0,23.0,307.0,1.0,1.0,1.0,,1841.0,Feature engineering package with sklearn like functionality.,49.0,26,True,2024-08-31 13:22:28.000,1.8.1,41.0,feature_engine,conda-forge/feature_engine,,,,146745.0,159.0,,https://pypi.org/project/feature_engine,2024-08-31 13:22:28.000,159.0,145608.0,https://anaconda.org/conda-forge/feature_engine,2024-09-01 13:51:20.563,55745.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +464,pyts,johannfaouzi/pyts,time-series-data,,https://github.com/johannfaouzi/pyts,https://github.com/johannfaouzi/pyts,BSD-3-Clause,2017-07-31 09:23:16.000,2023-09-11 22:28:27.000000,2023-06-20 13:16:50,391.0,,161.0,25.0,81.0,46.0,35.0,1750.0,A Python package for time series classification.,14.0,26,False,2023-06-18 12:36:11.801,0.13.0,19.0,pyts,conda-forge/pyts,,,,139829.0,713.0,668.0,https://pypi.org/project/pyts,2023-06-18 12:36:11.801,45.0,139073.0,https://anaconda.org/conda-forge/pyts,2023-06-18 16:28:23.633,26466.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +465,avalanche,ContinualAI/avalanche,others,,https://github.com/ContinualAI/avalanche,https://github.com/ContinualAI/avalanche,MIT,2020-03-05 11:32:13.000,2024-06-21 10:56:28.000000,2024-06-03 08:29:10,3912.0,,284.0,29.0,578.0,91.0,721.0,1744.0,Avalanche: an End-to-End Library for Continual Learning based on PyTorch.,78.0,26,True,2024-02-27 17:02:40.000,0.5.0,8.0,avalanche-lib,,,,27.0,1605.0,104.0,101.0,https://pypi.org/project/avalanche-lib,2024-02-27 16:52:08.000,3.0,1605.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +466,FARM,deepset-ai/FARM,nlp,,https://github.com/deepset-ai/FARM,https://github.com/deepset-ai/FARM,Apache-2.0,2019-07-17 14:51:12.000,2023-12-20 21:18:02.000000,2022-08-31 09:45:24,594.0,,245.0,53.0,446.0,6.0,402.0,1733.0,Fast & easy transfer learning for NLP. Harvesting language models for the industry. Focus on Question Answering.,37.0,26,False,2023-03-07 23:47:39.075,0.7.1,25.0,farm,conda-forge/farm,,['pytorch'],,1250.0,231.0,228.0,https://pypi.org/project/farm,2020-09-14 15:23:01.000,3.0,1158.0,https://anaconda.org/conda-forge/farm,2023-06-16 19:25:45.236,3811.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +467,TNT,pytorch/tnt,ml-experiments,,https://github.com/pytorch/tnt,https://github.com/pytorch/tnt,BSD-3-Clause,2016-12-10 11:49:58.000,2024-08-30 21:18:04.000000,2024-08-30 21:14:50,983.0,44.0,266.0,45.0,822.0,79.0,66.0,1654.0,A lightweight library for PyTorch training tools and utilities.,132.0,26,True,2018-07-29 23:16:03.000,0.0.4,3.0,torchnet,,,['pytorch'],,4784.0,24.0,,https://pypi.org/project/torchnet,2018-07-29 23:16:03.000,24.0,4784.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +468,Talos,autonomio/talos,hyperopt,,https://github.com/autonomio/talos,https://github.com/autonomio/talos,MIT,2018-05-04 20:36:41.000,2024-04-22 10:30:49.000000,2024-04-22 10:30:48,671.0,,269.0,27.0,187.0,10.0,390.0,1618.0,Hyperparameter Experiments with TensorFlow and Keras.,23.0,26,True,2024-04-21 09:02:06.000,1.4,18.0,talos,,,['tensorflow'],,1817.0,194.0,186.0,https://pypi.org/project/talos,2024-04-21 09:02:29.000,8.0,1817.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +469,gplearn,trevorstephens/gplearn,others,,https://github.com/trevorstephens/gplearn,https://github.com/trevorstephens/gplearn,BSD-3-Clause,2015-03-26 01:01:14.000,2023-11-29 15:04:03.000000,2023-08-12 06:34:27,161.0,,273.0,51.0,87.0,22.0,191.0,1584.0,"Genetic Programming in Python, with a scikit-learn inspired API.",11.0,26,False,2022-05-03 10:56:08.000,0.4.2,7.0,gplearn,conda-forge/gplearn,,['sklearn'],,14574.0,654.0,635.0,https://pypi.org/project/gplearn,2022-05-03 10:47:30.000,19.0,14425.0,https://anaconda.org/conda-forge/gplearn,2023-06-16 19:20:25.471,7642.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +470,Paddle Graph Learning,PaddlePaddle/PGL,graph,,https://github.com/PaddlePaddle/PGL,https://github.com/PaddlePaddle/PGL,Apache-2.0,2019-06-11 03:23:28.000,2023-12-11 05:15:14.000000,2023-09-26 07:34:28,1378.0,,309.0,27.0,379.0,56.0,155.0,1568.0,Paddle Graph Learning (PGL) is an efficient and flexible graph learning framework based on PaddlePaddle.,31.0,26,True,2023-09-26 07:49:38.000,2.2.6,21.0,pgl,,,['paddle'],,1189.0,61.0,60.0,https://pypi.org/project/pgl,2023-09-26 07:49:38.000,1.0,1189.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +471,pycm,sepandhaghighi/pycm,others,,https://github.com/sepandhaghighi/pycm,https://github.com/sepandhaghighi/pycm,MIT,2018-01-22 19:46:54.000,2024-08-19 01:12:36.000000,2023-06-07 07:35:59,3033.0,,121.0,35.0,355.0,14.0,187.0,1442.0,Multi-class confusion matrix library in Python.,17.0,26,False,2023-06-07 14:06:28.000,4.0,44.0,pycm,,,,,42439.0,354.0,330.0,https://pypi.org/project/pycm,2023-06-07 14:08:01.991,24.0,42439.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +472,DALEX,ModelOriented/DALEX,interpretability,,https://github.com/ModelOriented/DALEX,https://github.com/ModelOriented/DALEX,GPL-3.0,2018-02-18 03:24:12.000,2024-09-04 08:57:04.000000,2024-06-07 09:11:54,678.0,,165.0,48.0,163.0,24.0,383.0,1361.0,moDel Agnostic Language for Exploration and eXplanation.,25.0,26,False,2024-02-28 20:54:37.000,1.7.0,27.0,dalex,conda-forge/dalex,,,,21478.0,188.0,181.0,https://pypi.org/project/dalex,2024-02-28 20:54:37.000,7.0,21121.0,https://anaconda.org/conda-forge/dalex,2024-02-29 10:49:59.696,15730.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +473,imodels,csinva/imodels,interpretability,,https://github.com/csinva/imodels,https://github.com/csinva/imodels,MIT,2019-07-04 15:38:48.000,2024-08-16 07:37:12.000000,2024-08-16 07:37:10,1060.0,6.0,119.0,23.0,116.0,36.0,56.0,1359.0,"Interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compatible).",24.0,26,True,2024-07-02 18:00:43.000,1.4.6,49.0,imodels,,,,,32044.0,104.0,95.0,https://pypi.org/project/imodels,2024-07-02 18:00:43.000,9.0,32044.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +474,Streamz,python-streamz/streamz,time-series-data,,https://github.com/python-streamz/streamz,https://github.com/python-streamz/streamz,BSD-3-Clause,2017-04-04 21:45:49.000,2024-06-18 04:54:15.000000,2022-12-22 14:52:10,805.0,,147.0,34.0,215.0,118.0,152.0,1235.0,Real-time stream processing for python.,48.0,26,False,2022-07-27 18:09:03.803,0.6.4,17.0,streamz,conda-forge/streamz,,,,35230.0,545.0,488.0,https://pypi.org/project/streamz,2022-07-27 18:09:03.803,57.0,23600.0,https://anaconda.org/conda-forge/streamz,2023-06-16 13:22:22.238,976975.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +475,hls4ml,fastmachinelearning/hls4ml,model-serialisation,,https://github.com/fastmachinelearning/hls4ml,https://github.com/fastmachinelearning/hls4ml,Apache-2.0,2017-10-25 21:43:56.000,2024-09-04 00:23:21.000000,2024-09-03 12:30:52,2112.0,93.0,388.0,55.0,535.0,176.0,255.0,1218.0,Machine learning on FPGAs using HLS.,62.0,26,True,2023-12-19 21:00:58.000,0.8.1,16.0,hls4ml,conda-forge/hls4ml,,"['tensorflow', 'pytorch']",,1164.0,,,https://pypi.org/project/hls4ml,2023-12-19 21:00:58.000,,988.0,https://anaconda.org/conda-forge/hls4ml,2023-06-16 19:22:51.232,8475.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +476,metricflow,transform-data/metricflow,others,,https://github.com/dbt-labs/metricflow,https://github.com/dbt-labs/metricflow,,2022-04-04 18:33:06.000,2024-09-05 04:53:57.000000,2024-09-05 04:53:56,2496.0,97.0,92.0,19.0,1071.0,78.0,231.0,1122.0,"MetricFlow allows you to define, build, and maintain metrics in code.",45.0,26,False,2024-06-11 22:06:04.000,0.206.0,88.0,metricflow,,,,,20066.0,28.0,24.0,https://pypi.org/project/metricflow,2024-07-09 00:14:45.000,4.0,20066.0,,,,3.0,,,,,,,,dbt-labs/metricflow,,,,,,,,,,,,,,,,, +477,Sentinelsat,sentinelsat/sentinelsat,geospatial-data,,https://github.com/sentinelsat/sentinelsat,https://github.com/sentinelsat/sentinelsat,GPL-3.0,2015-05-22 20:32:26.000,2024-02-29 13:41:12.000000,2024-02-29 13:41:11,1144.0,,236.0,61.0,246.0,22.0,367.0,972.0,Search and download Copernicus Sentinel satellite images.,44.0,26,False,2023-03-10 17:53:00.587,1.2.1,41.0,sentinelsat,conda-forge/sentinelsat,,,294.0,21249.0,608.0,574.0,https://pypi.org/project/sentinelsat,2017-03-06 02:33:09.000,34.0,20571.0,https://anaconda.org/conda-forge/sentinelsat,2023-06-16 19:22:55.678,31765.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +478,GPyOpt,SheffieldML/GPyOpt,hyperopt,,https://github.com/SheffieldML/GPyOpt,https://github.com/SheffieldML/GPyOpt,BSD-3-Clause,2014-08-13 09:58:25.000,2023-01-17 18:04:41.000000,2023-01-17 18:04:41,515.0,,261.0,44.0,72.0,104.0,188.0,927.0,Gaussian Process Optimization using GPy.,50.0,26,False,2020-03-19 21:21:18.000,1.2.6,11.0,gpyopt,,,,,20948.0,566.0,529.0,https://pypi.org/project/gpyopt,2020-03-19 11:37:45.000,37.0,20948.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +479,scikit-multilearn,scikit-multilearn/scikit-multilearn,sklearn-utils,,https://github.com/scikit-multilearn/scikit-multilearn,https://github.com/scikit-multilearn/scikit-multilearn,BSD-2-Clause,2014-04-30 13:05:44.000,2024-02-01 04:40:03.000000,2023-04-19 21:43:19,547.0,,174.0,33.0,86.0,88.0,123.0,916.0,A scikit-learn based module for multi-label et. al. classification.,28.0,26,False,2018-12-10 16:24:47.000,0.2.0,7.0,scikit-multilearn,,,['sklearn'],,49867.0,1759.0,1734.0,https://pypi.org/project/scikit-multilearn,2018-12-10 16:24:47.000,25.0,49867.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +480,pySBD,nipunsadvilkar/pySBD,nlp,,https://github.com/nipunsadvilkar/pySBD,https://github.com/nipunsadvilkar/pySBD,MIT,2017-06-11 06:15:20.000,2024-08-20 16:20:38.000000,2021-02-11 16:40:18,279.0,,80.0,12.0,49.0,22.0,53.0,781.0,pySBD (Python Sentence Boundary Disambiguation) is a rule-based sentence boundary detection that works out-of-the-box.,7.0,26,False,2021-02-11 16:42:37.000,0.3.4,15.0,pysbd,conda-forge/pysbd,,,,838611.0,3550.0,3473.0,https://pypi.org/project/pysbd,2021-02-11 16:36:33.000,77.0,838425.0,https://anaconda.org/conda-forge/pysbd,2023-06-16 19:27:37.870,6539.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +481,data-validation,tensorflow/data-validation,data-viz,,https://github.com/tensorflow/data-validation,https://github.com/tensorflow/data-validation,Apache-2.0,2018-07-02 15:47:02.000,2024-09-04 21:14:38.000000,2024-09-04 21:14:37,967.0,4.0,168.0,47.0,85.0,37.0,144.0,757.0,Library for exploring and validating machine learning data.,26.0,26,True,2024-04-24 23:26:22.000,1.15.1,46.0,tensorflow-data-validation,,,"['tensorflow', 'jupyter']",759.0,206477.0,31.0,,https://pypi.org/project/tensorflow-data-validation,2024-04-24 23:54:11.000,31.0,206467.0,,,,3.0,,,,,,-4.0,,,,,,,,,,,,,,,,,,, +482,quinn,MrPowers/quinn,ml-experiments,,https://github.com/mrpowers-io/quinn,https://github.com/mrpowers-io/quinn,Apache-2.0,2017-09-15 13:02:42.000,2024-08-29 19:53:11.000000,2024-08-29 19:51:59,354.0,25.0,95.0,20.0,140.0,36.0,94.0,619.0,pyspark methods to enhance developer productivity.,31.0,26,True,2024-02-13 12:31:37.000,0.10.3,16.0,quinn,,,['spark'],32.0,656720.0,90.0,83.0,https://pypi.org/project/quinn,2024-02-13 12:31:37.000,7.0,656720.0,,,,3.0,,,,,,,,mrpowers-io/quinn,,,,,,,,,,,,,,,,, +483,ml-metadata,google/ml-metadata,ml-experiments,,https://github.com/google/ml-metadata,https://github.com/google/ml-metadata,Apache-2.0,2019-01-15 21:02:09.000,2024-08-30 00:51:12.000000,2024-08-30 00:51:11,848.0,3.0,140.0,28.0,91.0,43.0,75.0,611.0,For recording and retrieving metadata associated with ML developer and data scientist workflows.,19.0,26,True,2024-04-23 05:17:11.000,1.15.0,43.0,ml-metadata,,,,2431.0,73070.0,581.0,550.0,https://pypi.org/project/ml-metadata,2024-04-23 05:17:11.000,31.0,73034.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +484,EarthPy,earthlab/earthpy,geospatial-data,,https://github.com/earthlab/earthpy,https://github.com/earthlab/earthpy,BSD-3-Clause,2018-02-20 03:02:42.000,2024-06-05 18:36:28.000000,2023-08-23 17:20:54,1241.0,,153.0,18.0,717.0,26.0,208.0,494.0,A package built to support working with spatial data using open source python.,44.0,26,False,2021-10-01 22:51:04.000,0.9.4,23.0,earthpy,conda-forge/earthpy,,,,8887.0,380.0,363.0,https://pypi.org/project/earthpy,2021-10-01 22:51:04.000,17.0,7644.0,https://anaconda.org/conda-forge/earthpy,2023-06-16 16:14:50.280,80799.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +485,miceforest,AnotherSamWilson/miceforest,tabular,,https://github.com/AnotherSamWilson/miceforest,https://github.com/AnotherSamWilson/miceforest,MIT,2020-08-22 00:00:22.000,2024-08-02 00:43:48.000000,2024-08-02 00:21:15,339.0,79.0,30.0,9.0,6.0,7.0,77.0,332.0,Multiple Imputation with LightGBM in Python.,8.0,26,True,2024-08-02 00:43:48.000,6.0.3,48.0,miceforest,conda-forge/miceforest,,,,63361.0,162.0,153.0,https://pypi.org/project/miceforest,2024-08-02 00:43:48.000,9.0,62977.0,https://anaconda.org/conda-forge/miceforest,2023-06-16 19:26:58.237,14627.0,1.0,,,,,,4.0,,,,,,,,,,,,,,,,,,, +486,mmdnn,Microsoft/MMdnn,model-serialisation,,https://github.com/microsoft/MMdnn,https://github.com/microsoft/MMdnn,MIT,2017-08-16 08:03:52.000,2024-05-29 15:42:28.000000,2022-09-22 23:59:07,1084.0,,966.0,181.0,328.0,338.0,294.0,5787.0,MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion..,86.0,25,False,2020-07-24 06:34:39.000,0.3.1,12.0,mmdnn,,,,3804.0,624.0,134.0,134.0,https://pypi.org/project/mmdnn,2020-07-24 06:34:39.000,,578.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +487,scikit-opt,guofei9987/scikit-opt,sklearn-utils,,https://github.com/guofei9987/scikit-opt,https://github.com/guofei9987/scikit-opt,MIT,2017-12-05 10:20:41.000,2024-06-23 12:28:48.000000,2024-06-23 12:28:48,343.0,5.0,974.0,47.0,34.0,64.0,112.0,5165.0,"Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization Algorithm,Immune..",24.0,25,True,2022-01-14 08:49:08.000,0.6.6,23.0,scikit-opt,,,['sklearn'],,4266.0,237.0,222.0,https://pypi.org/project/scikit-opt,2022-01-14 08:49:08.000,15.0,4266.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +488,Image Deduplicator,idealo/imagededup,image,,https://github.com/idealo/imagededup,https://github.com/idealo/imagededup,Apache-2.0,2019-04-05 12:10:54.000,2024-07-03 14:09:40.000000,2023-04-28 16:55:30,521.0,,449.0,63.0,94.0,36.0,88.0,5073.0,Finding duplicate images made easy!.,15.0,25,False,2023-04-28 17:29:01.612,0.3.2,12.0,imagededup,,,['tensorflow'],,40266.0,145.0,140.0,https://pypi.org/project/imagededup,2023-04-28 17:29:01.612,5.0,40266.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +489,Augmentor,mdbloice/Augmentor,image,,https://github.com/mdbloice/Augmentor,https://github.com/mdbloice/Augmentor,MIT,2016-03-01 18:29:55.000,2024-03-21 14:27:34.000000,2023-03-29 07:02:37,553.0,,867.0,123.0,64.0,136.0,74.0,5055.0,Image augmentation library in Python for machine learning.,23.0,25,False,2023-03-29 07:06:01.465,0.2.12,24.0,Augmentor,,,,,6649.0,825.0,813.0,https://pypi.org/project/Augmentor,2022-04-27 09:29:23.000,12.0,6649.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +490,DALI,NVIDIA/DALI,gpu-utilities,,https://github.com/NVIDIA/DALI,https://github.com/NVIDIA/DALI,Apache-2.0,2018-06-01 22:18:01.000,2024-09-05 10:04:13.000000,2024-09-05 10:04:13,3665.0,80.0,615.0,90.0,4023.0,228.0,1397.0,5054.0,A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to..,93.0,25,True,2024-08-29 19:14:26.000,1.41.0,82.0,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +491,Lucid,tensorflow/lucid,interpretability,,https://github.com/tensorflow/lucid,https://github.com/tensorflow/lucid,Apache-2.0,2018-01-25 17:41:44.000,2023-02-06 16:41:16.000000,2021-03-19 15:48:33,667.0,,658.0,158.0,130.0,83.0,101.0,4649.0,A collection of infrastructure and tools for research in neural network interpretability.,40.0,25,False,2021-03-19 16:01:00.000,0.3.10,17.0,lucid,,,['tensorflow'],,512.0,787.0,781.0,https://pypi.org/project/lucid,2021-03-19 16:01:00.000,6.0,512.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +492,PyAlgoTrade,gbeced/pyalgotrade,financial-data,,https://github.com/gbeced/pyalgotrade,https://github.com/gbeced/pyalgotrade,Apache-2.0,2012-03-07 01:09:54.000,2023-11-13 07:16:00.000000,2023-03-05 22:07:59,1158.0,,1385.0,352.0,59.0,51.0,,4377.0,Python Algorithmic Trading Library.,11.0,25,False,,,8.0,pyalgotrade,,,,,1138.0,191.0,191.0,https://pypi.org/project/pyalgotrade,2018-08-21 01:48:25.000,,1138.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +493,OpenPrompt,thunlp/OpenPrompt,nlp,,https://github.com/thunlp/OpenPrompt,https://github.com/thunlp/OpenPrompt,Apache-2.0,2021-09-30 09:38:45.000,2024-07-16 03:48:08.000000,2023-05-06 14:09:10,264.0,,437.0,43.0,54.0,88.0,174.0,4290.0,An Open-Source Framework for Prompt-Learning.,22.0,25,False,2022-07-06 14:27:42.000,1.0.1,5.0,openprompt,,,,,600.0,146.0,143.0,https://pypi.org/project/openprompt,2022-07-06 14:27:42.000,3.0,600.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +494,MatchZoo,NTMC-Community/MatchZoo,nlp,,https://github.com/NTMC-Community/MatchZoo,https://github.com/NTMC-Community/MatchZoo,Apache-2.0,2017-06-08 08:55:22.000,2024-08-02 16:23:45.000000,2021-06-02 17:38:16,1810.0,,917.0,176.0,386.0,33.0,430.0,3834.0,"Facilitating the design, comparison and sharing of deep text matching models.",37.0,25,False,2019-10-24 13:09:11.000,2.2.0,5.0,matchzoo,,,['tensorflow'],,98.0,17.0,17.0,https://pypi.org/project/matchzoo,2019-10-24 13:09:11.000,,98.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +495,Apache Singa,apache/singa,distributed-ml,,https://github.com/apache/singa,https://github.com/apache/singa,Apache-2.0,2015-04-02 07:00:05.000,2024-08-30 13:40:38.000000,2024-08-17 14:22:50,2847.0,65.0,1220.0,134.0,1108.0,52.0,76.0,3340.0,a distributed deep learning platform.,91.0,25,True,2020-04-21 08:01:08.000,3.0.0,16.0,,nusdbsystem/singa,,,,77.0,4.0,4.0,,,,,https://anaconda.org/nusdbsystem/singa,2023-06-16 13:23:56.805,769.0,3.0,apache/singa,https://hub.docker.com/r/apache/singa,2022-05-31 15:24:19.649658,4.0,7895.0,,,,,,,,,,,,,,,,,,,, +496,RecBole,RUCAIBox/RecBole,recommender-systems,,https://github.com/RUCAIBox/RecBole,https://github.com/RUCAIBox/RecBole,MIT,2020-06-11 15:18:11.000,2024-09-05 04:03:54.000000,2024-09-05 04:03:53,4353.0,8.0,599.0,40.0,1007.0,283.0,706.0,3321.0,"A unified, comprehensive and efficient recommendation library.",74.0,25,True,2023-11-04 11:23:19.000,1.2.0,10.0,recbole,aibox/recbole,,['pytorch'],,54520.0,2.0,,https://pypi.org/project/recbole,2023-10-31 12:52:34.000,2.0,54396.0,https://anaconda.org/aibox/recbole,2023-11-01 15:53:42.380,5718.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +497,pytorchvideo,facebookresearch/pytorchvideo,image,,https://github.com/facebookresearch/pytorchvideo,https://github.com/facebookresearch/pytorchvideo,Apache-2.0,2021-03-09 20:39:13.000,2024-08-13 17:52:35.000000,2024-08-13 17:16:53,181.0,1.0,401.0,156.0,85.0,105.0,101.0,3273.0,A deep learning library for video understanding research.,56.0,25,True,2022-01-20 00:16:35.000,0.1.5,9.0,pytorchvideo,,,['pytorch'],,16415.0,24.0,,https://pypi.org/project/pytorchvideo,2022-01-20 00:16:35.000,24.0,16415.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +498,keras-vis,raghakot/keras-vis,interpretability,,https://github.com/raghakot/keras-vis,https://github.com/raghakot/keras-vis,MIT,2016-11-11 23:27:34.000,2022-02-07 16:06:07.000000,2020-04-20 01:03:12,195.0,,664.0,71.0,25.0,117.0,101.0,2975.0,Neural network visualization toolkit for keras.,10.0,25,False,2017-07-06 05:11:22.255,0.4.1,11.0,keras-vis,,,['tensorflow'],,1353.0,2968.0,2967.0,https://pypi.org/project/keras-vis,2017-07-06 05:11:22.255,1.0,1353.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +499,neuralcoref,huggingface/neuralcoref,nlp,,https://github.com/huggingface/neuralcoref,https://github.com/huggingface/neuralcoref,MIT,2017-07-03 13:04:16.000,2023-06-16 19:17:56.088000,2021-06-22 10:51:48,116.0,,475.0,97.0,49.0,65.0,254.0,2846.0,Fast Coreference Resolution in spaCy with Neural Networks.,21.0,25,False,2019-04-08 11:28:27.000,4.0.0,5.0,neuralcoref,conda-forge/neuralcoref,,,1062.0,2738.0,742.0,721.0,https://pypi.org/project/neuralcoref,2019-04-08 09:56:00.000,21.0,2400.0,https://anaconda.org/conda-forge/neuralcoref,2023-06-16 19:17:56.088,17973.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +500,scattertext,JasonKessler/scattertext,nlp,,https://github.com/JasonKessler/scattertext,https://github.com/JasonKessler/scattertext,Apache-2.0,2016-07-21 01:47:12.000,2024-03-06 06:56:13.000000,2024-03-06 06:55:14,388.0,,289.0,55.0,14.0,22.0,80.0,2231.0,Beautiful visualizations of how language differs among document types.,14.0,25,True,2024-03-06 06:56:13.000,0.2.1,150.0,scattertext,conda-forge/scattertext,,,,17915.0,619.0,614.0,https://pypi.org/project/scattertext,2024-03-06 06:56:13.000,5.0,16780.0,https://anaconda.org/conda-forge/scattertext,2023-06-16 13:23:09.869,96525.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +501,pytorch-nlp,PetrochukM/PyTorch-NLP,nlp,,https://github.com/PetrochukM/PyTorch-NLP,https://github.com/PetrochukM/PyTorch-NLP,BSD-3-Clause,2018-02-25 05:00:36.000,2023-07-04 21:11:26.000000,2023-07-04 21:11:26,451.0,,252.0,55.0,56.0,19.0,50.0,2208.0,Basic Utilities for PyTorch Natural Language Processing (NLP).,18.0,25,False,2019-11-04 05:16:00.000,0.5.0,19.0,pytorch-nlp,,,['pytorch'],,8480.0,729.0,710.0,https://pypi.org/project/pytorch-nlp,2019-11-04 04:35:18.000,19.0,8480.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +502,AmpliGraph,Accenture/AmpliGraph,graph,,https://github.com/Accenture/AmpliGraph,https://github.com/Accenture/AmpliGraph,Apache-2.0,2019-01-09 14:52:05.000,2024-04-25 09:54:03.000000,2024-02-28 15:45:58,1631.0,,251.0,66.0,63.0,41.0,187.0,2136.0,Python library for Representation Learning on Knowledge Graphs https://docs.ampligraph.org.,21.0,25,True,2024-02-28 15:44:03.000,2.1.0,15.0,ampligraph,,,['tensorflow'],,898.0,57.0,55.0,https://pypi.org/project/ampligraph,2024-02-26 17:12:26.000,2.0,898.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +503,PyFlux,RJT1990/pyflux,time-series-data,,https://github.com/RJT1990/pyflux,https://github.com/RJT1990/pyflux,BSD-3-Clause,2016-02-16 20:12:02.000,2023-10-24 16:13:23.000000,2018-12-16 15:30:13,118.0,,240.0,70.0,21.0,93.0,66.0,2107.0,Open source time series library for Python.,6.0,25,False,2017-11-21 16:27:06.000,0.4.16,36.0,pyflux,,,,,270855.0,277.0,273.0,https://pypi.org/project/pyflux,2017-11-21 16:27:06.000,4.0,270855.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +504,garage,rlworkgroup/garage,reinforcement-learning,,https://github.com/rlworkgroup/garage,https://github.com/rlworkgroup/garage,MIT,2018-06-10 21:31:23.000,2023-05-04 14:44:22.000000,2023-01-04 06:06:27,1221.0,,310.0,56.0,1313.0,234.0,810.0,1853.0,A toolkit for reproducible reinforcement learning research.,79.0,25,False,2021-03-23 22:18:36.000,2021.3.0,21.0,garage,,,['tensorflow'],,507.0,116.0,112.0,https://pypi.org/project/garage,2021-03-23 22:18:36.000,4.0,507.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +505,Orbit,uber/orbit,probabilistics,,https://github.com/uber/orbit,https://github.com/uber/orbit,Apache-2.0,2020-01-07 18:20:37.000,2024-07-10 23:00:12.000000,2024-07-10 23:00:11,927.0,8.0,135.0,34.0,446.0,50.0,354.0,1853.0,A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.,20.0,25,True,2024-04-01 00:44:51.000,1.1.4.9,36.0,orbit-ml,,,,,18857.0,62.0,61.0,https://pypi.org/project/orbit-ml,2024-04-01 00:45:19.000,1.0,18857.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +506,uber/orbit,uber/orbit,time-series-data,,https://github.com/uber/orbit,https://github.com/uber/orbit,Apache-2.0,2020-01-07 18:20:37.000,2024-07-10 23:00:12.000000,2024-07-10 23:00:11,927.0,8.0,135.0,34.0,446.0,50.0,354.0,1853.0,A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.,20.0,25,True,2024-04-01 00:44:51.000,1.1.4.9,36.0,orbit-ml,conda-forge/orbit-ml,,,,19264.0,62.0,61.0,https://pypi.org/project/orbit-ml,2024-04-01 00:45:19.000,1.0,18857.0,https://anaconda.org/conda-forge/orbit-ml,2024-04-01 02:54:47.033,13048.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +507,HyperTools,ContextLab/hypertools,data-viz,,https://github.com/ContextLab/hypertools,https://github.com/ContextLab/hypertools,MIT,2016-09-27 21:31:25.000,2024-03-19 21:59:57.000000,2024-03-19 21:59:57,1652.0,,160.0,60.0,68.0,66.0,130.0,1817.0,A Python toolbox for gaining geometric insights into high-dimensional data.,22.0,25,True,2022-02-12 03:29:55.000,0.8.0,21.0,hypertools,,,,41.0,649.0,469.0,467.0,https://pypi.org/project/hypertools,2022-02-12 02:43:24.000,2.0,649.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +508,AutoViz,AutoViML/AutoViz,data-viz,,https://github.com/AutoViML/AutoViz,https://github.com/AutoViML/AutoViz,Apache-2.0,2019-07-17 17:14:06.000,2024-06-10 12:09:16.000000,2024-06-10 12:07:33,223.0,1.0,196.0,32.0,20.0,3.0,91.0,1702.0,"Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators..",17.0,25,True,2024-06-10 12:09:16.000,0.1.905,90.0,autoviz,conda-forge/autoviz,,,,59132.0,750.0,739.0,https://pypi.org/project/autoviz,2024-06-10 12:09:16.000,11.0,57464.0,https://anaconda.org/conda-forge/autoviz,2024-04-26 17:50:17.078,61723.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +509,Explainability 360,Trusted-AI/AIX360,interpretability,,https://github.com/Trusted-AI/AIX360,https://github.com/Trusted-AI/AIX360,Apache-2.0,2019-07-11 07:17:48.000,2024-07-16 05:54:41.000000,2024-07-16 05:54:41,602.0,15.0,302.0,55.0,116.0,54.0,31.0,1603.0,Interpretability and explainability of data and machine learning models.,41.0,25,True,2023-07-31 18:54:38.000,0.3.0,5.0,aix360,,,,,469.0,99.0,98.0,https://pypi.org/project/aix360,2023-07-31 18:54:38.000,1.0,469.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +510,Elephas,maxpumperla/elephas,distributed-ml,,https://github.com/maxpumperla/elephas,https://github.com/maxpumperla/elephas,MIT,2015-08-13 12:09:19.000,2024-08-04 13:39:34.000000,2022-08-31 01:52:51,509.0,,308.0,102.0,49.0,8.0,151.0,1573.0,Distributed Deep learning with Keras & Spark.,27.0,25,False,2024-08-04 13:39:34.000,6.1.0,44.0,elephas,conda-forge/elephas,,"['keras', 'spark']",,37649.0,,,https://pypi.org/project/elephas,2024-08-04 13:39:34.000,,37405.0,https://anaconda.org/conda-forge/elephas,2023-06-16 16:16:35.554,14944.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +511,torch-scatter,rusty1s/pytorch_scatter,pytorch-utils,,https://github.com/rusty1s/pytorch_scatter,https://github.com/rusty1s/pytorch_scatter,MIT,2017-12-16 16:34:23.000,2024-08-24 06:55:52.306000,2024-08-15 08:12:47,1036.0,1.0,179.0,17.0,74.0,30.0,356.0,1535.0,PyTorch Extension Library of Optimized Scatter Operations.,30.0,25,True,2023-10-06 08:49:07.000,2.1.2,32.0,torch-scatter,conda-forge/pytorch_scatter,,['pytorch'],,43039.0,152.0,,https://pypi.org/project/torch-scatter,2023-10-06 08:49:07.000,152.0,34259.0,https://anaconda.org/conda-forge/pytorch_scatter,2024-08-24 06:55:52.306,447819.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +512,CrypTen,facebookresearch/CrypTen,privacy-ml,,https://github.com/facebookresearch/CrypTen,https://github.com/facebookresearch/CrypTen,MIT,2019-08-15 00:00:31.000,2024-07-18 17:36:15.000000,2024-07-18 17:32:59,357.0,3.0,269.0,44.0,255.0,77.0,197.0,1517.0,A framework for Privacy Preserving Machine Learning.,38.0,25,True,2022-12-08 22:11:59.883,0.4.1,3.0,crypten,,,['pytorch'],,427.0,43.0,42.0,https://pypi.org/project/crypten,2022-12-08 22:11:59.883,1.0,427.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +513,metric-learn,scikit-learn-contrib/metric-learn,others,,https://github.com/scikit-learn-contrib/metric-learn,https://github.com/scikit-learn-contrib/metric-learn,MIT,2013-11-02 08:29:47.000,2024-08-03 19:34:12.000000,2024-08-03 19:34:12,297.0,2.0,231.0,46.0,186.0,53.0,121.0,1391.0,Metric learning algorithms in Python.,23.0,25,True,2023-10-09 04:53:59.000,0.7.0,11.0,metric-learn,conda-forge/metric-learn,,['sklearn'],,6650.0,406.0,399.0,https://pypi.org/project/metric-learn,2023-10-09 04:53:59.000,7.0,6394.0,https://anaconda.org/conda-forge/metric-learn,2023-10-09 05:53:11.819,12825.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +514,NiftyNet,NifTK/NiftyNet,medical-data,,https://github.com/NifTK/NiftyNet,https://github.com/NifTK/NiftyNet,Apache-2.0,2017-08-30 07:55:43.000,2020-04-21 19:54:52.000000,2020-04-21 19:54:51,3284.0,,404.0,90.0,165.0,103.0,224.0,1364.0,[unmaintained] An open-source convolutional neural networks platform for research in medical image analysis and image-..,61.0,25,False,2019-10-10 10:59:33.000,0.6.0,11.0,niftynet,,,['tensorflow'],,168.0,45.0,45.0,https://pypi.org/project/niftynet,2019-10-10 10:59:33.000,,168.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +515,livelossplot,stared/livelossplot,ml-experiments,,https://github.com/stared/livelossplot,https://github.com/stared/livelossplot,MIT,2018-03-10 17:51:43.000,2022-07-15 12:45:07.000000,2022-04-04 16:13:36,330.0,,143.0,28.0,63.0,9.0,70.0,1295.0,"Live training loss plot in Jupyter Notebook for Keras, PyTorch and others.",17.0,25,False,2022-04-04 16:14:08.000,0.5.5,25.0,livelossplot,,,['jupyter'],,15744.0,1656.0,1640.0,https://pypi.org/project/livelossplot,2022-04-04 16:14:08.000,16.0,15744.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +516,iNNvestigate,albermax/innvestigate,interpretability,,https://github.com/albermax/innvestigate,https://github.com/albermax/innvestigate,BSD-2-Clause,2017-12-13 18:11:20.000,2023-12-20 21:48:32.000000,2023-10-12 14:56:47,1107.0,,235.0,35.0,68.0,57.0,206.0,1253.0,A toolbox to iNNvestigate neural networks predictions!.,22.0,25,True,2023-10-12 14:58:48.000,2.1.2,8.0,innvestigate,,,['tensorflow'],132.0,711.0,139.0,137.0,https://pypi.org/project/innvestigate,2023-10-12 14:55:59.000,2.0,706.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +517,Prince,MaxHalford/prince,others,,https://github.com/MaxHalford/prince,https://github.com/MaxHalford/prince,MIT,2016-10-22 12:36:06.000,2024-06-10 09:07:10.000000,2024-06-10 09:07:08,398.0,2.0,177.0,26.0,33.0,4.0,129.0,1246.0,"Multivariate exploratory data analysis in Python PCA, CA, MCA, MFA, FAMD, GPA.",16.0,25,True,2023-10-11 22:35:06.000,0.13.0,59.0,prince,conda-forge/prince-factor-analysis,,['sklearn'],,153813.0,614.0,596.0,https://pypi.org/project/prince,2023-10-11 22:35:06.000,18.0,153465.0,https://anaconda.org/conda-forge/prince-factor-analysis,2023-06-16 16:19:02.748,20202.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +518,Node2Vec,eliorc/node2vec,graph,,https://github.com/eliorc/node2vec,https://github.com/eliorc/node2vec,MIT,2017-12-08 13:30:06.000,2024-08-02 11:14:24.000000,2024-08-02 11:14:21,90.0,3.0,245.0,20.0,23.0,5.0,88.0,1209.0,Implementation of the node2vec algorithm.,16.0,25,True,2024-08-02 11:13:59.000,0.5.0,19.0,node2vec,conda-forge/node2vec,,,,17143.0,703.0,672.0,https://pypi.org/project/node2vec,2024-08-02 11:12:23.000,31.0,16746.0,https://anaconda.org/conda-forge/node2vec,2023-06-16 16:13:35.056,30246.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +519,GPUtil,anderskm/gputil,gpu-utilities,,https://github.com/anderskm/gputil,https://github.com/anderskm/gputil,MIT,2017-01-16 11:57:43.000,2024-04-13 14:07:28.000000,2019-08-16 09:00:15,140.0,,119.0,11.0,23.0,28.0,15.0,1115.0,A Python module for getting the GPU status from NVIDA GPUs using nvidia-smi programmically in Python.,14.0,25,False,2018-12-18 09:12:13.000,1.4.0,8.0,gputil,,,,,505577.0,6390.0,5928.0,https://pypi.org/project/gputil,2018-12-18 09:12:13.000,462.0,505577.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +520,SMAC3,automl/SMAC3,hyperopt,,https://github.com/automl/SMAC3,https://github.com/automl/SMAC3,BSD-1-Clause,2016-08-17 10:58:05.000,2024-08-26 14:27:38.000000,2024-07-24 14:36:04,2074.0,2.0,218.0,42.0,604.0,101.0,440.0,1061.0,SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization.,41.0,25,False,2024-07-24 14:42:30.000,2.2.0,49.0,smac,conda-forge/smac,,,,18981.0,39.0,,https://pypi.org/project/smac,2024-07-24 14:42:30.000,39.0,18423.0,https://anaconda.org/conda-forge/smac,2024-05-16 20:20:11.437,23441.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +521,BioPandas,rasbt/biopandas,others,,https://github.com/BioPandas/biopandas,https://github.com/BioPandas/biopandas,BSD-3-Clause,2015-11-21 00:00:14.000,2024-08-02 05:29:18.056000,2024-08-01 17:33:11,360.0,5.0,118.0,17.0,84.0,21.0,38.0,706.0,Working with molecular structures in pandas DataFrames.,18.0,25,True,2024-08-01 17:35:04.000,0.5.1,21.0,biopandas,conda-forge/biopandas,,['pandas'],,69288.0,316.0,278.0,https://pypi.org/project/biopandas,2024-08-01 17:35:04.000,38.0,66006.0,https://anaconda.org/conda-forge/biopandas,2024-08-02 05:29:18.056,160860.0,3.0,,,,,,,,BioPandas/biopandas,,,,,,,,,,,,,,,,, +522,tinytag,devsnd/tinytag,audio,,https://github.com/tinytag/tinytag,https://github.com/tinytag/tinytag,MIT,2014-01-27 15:27:01.000,2024-08-29 13:38:23.000000,2024-08-29 13:37:57,573.0,13.0,101.0,23.0,102.0,15.0,110.0,687.0,Python library for reading audio file metadata.,27.0,25,True,2023-10-26 19:30:36.000,1.10.1,41.0,tinytag,,,,,25262.0,113.0,,https://pypi.org/project/tinytag,2023-10-26 19:30:36.000,113.0,25262.0,,,,3.0,,,,,,,,tinytag/tinytag,,,,,,,,,,,,,,,,, +523,FEDOT,nccr-itmo/FEDOT,hyperopt,,https://github.com/aimclub/FEDOT,https://github.com/aimclub/FEDOT,BSD-3-Clause,2020-01-13 12:48:37.000,2024-09-04 20:33:29.000000,2024-09-04 20:33:24,894.0,20.0,86.0,10.0,760.0,97.0,448.0,630.0,Automated modeling and machine learning framework FEDOT.,34.0,25,True,2024-08-28 11:07:57.000,0.7.4,23.0,fedot,,,,,1134.0,57.0,52.0,https://pypi.org/project/fedot,2024-08-28 10:34:09.000,5.0,1134.0,,,,2.0,,,,,,,,aimclub/FEDOT,,,,,,,,,,,,,,,,, +524,pyvips,libvips/pyvips,image,,https://github.com/libvips/pyvips,https://github.com/libvips/pyvips,MIT,2017-07-28 16:39:43.000,2024-08-26 11:19:41.000000,2024-08-26 11:19:41,478.0,1.0,49.0,9.0,61.0,187.0,251.0,627.0,python binding for libvips using cffi.,16.0,25,True,2024-04-28 11:19:58.000,2.2.3,26.0,pyvips,conda-forge/pyvips,,,,56048.0,865.0,788.0,https://pypi.org/project/pyvips,2024-04-28 11:19:58.000,77.0,53498.0,https://anaconda.org/conda-forge/pyvips,2024-04-28 16:46:16.622,119856.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +525,MedPy,loli/medpy,medical-data,,https://github.com/loli/medpy,https://github.com/loli/medpy,GPL-3.0,2012-05-11 10:57:34.000,2024-09-03 23:00:22.000000,2024-07-23 14:46:53,413.0,6.0,137.0,21.0,49.0,1.0,87.0,567.0,Medical image processing in Python.,20.0,25,False,2024-07-23 14:23:57.000,0.5.2,11.0,MedPy,conda-forge/medpy,,,,31691.0,2219.0,2166.0,https://pypi.org/project/MedPy,2024-07-23 14:23:57.000,53.0,30337.0,https://anaconda.org/conda-forge/medpy,2024-08-18 07:02:58.905,52836.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +526,whoosh,mchaput/whoosh,nlp,,https://github.com/mchaput/whoosh,https://github.com/mchaput/whoosh,BSD-1-Clause,2015-04-17 19:34:47.000,2024-09-03 08:52:17.073000,2022-01-15 18:08:37,1718.0,,67.0,15.0,13.0,35.0,7.0,566.0,Pure-Python full-text search library.,42.0,25,False,2016-04-04 01:19:40.000,2.7.4,141.0,whoosh,conda-forge/whoosh,,,,961333.0,230.0,,https://pypi.org/project/whoosh,2016-04-04 01:19:40.000,230.0,953588.0,https://anaconda.org/conda-forge/whoosh,2024-09-03 08:52:17.073,309839.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +527,Hyperactive,SimonBlanke/Hyperactive,hyperopt,,https://github.com/SimonBlanke/Hyperactive,https://github.com/SimonBlanke/Hyperactive,MIT,2018-11-01 08:53:30.000,2024-09-02 18:09:15.000000,2024-08-30 12:42:13,2350.0,63.0,41.0,12.0,15.0,12.0,61.0,502.0,An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.,8.0,25,True,2024-08-14 15:06:05.000,4.8.0,80.0,hyperactive,,,,208.0,3324.0,47.0,34.0,https://pypi.org/project/hyperactive,2024-08-15 14:23:15.000,13.0,3321.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +528,NIPY,nipy/nipy,medical-data,,https://github.com/nipy/nipy,https://github.com/nipy/nipy,,2010-05-02 10:00:33.000,2024-07-28 17:27:34.085000,2024-07-25 12:35:52,6718.0,9.0,144.0,36.0,400.0,38.0,138.0,382.0,Neuroimaging in Python FMRI analysis package.,69.0,25,False,2023-12-21 16:45:52.000,0.6.0,8.0,nipy,conda-forge/nipy,,,,63102.0,257.0,233.0,https://pypi.org/project/nipy,2023-12-21 16:45:52.000,24.0,2357.0,https://anaconda.org/conda-forge/nipy,2024-07-28 17:27:34.085,121491.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +529,gokart,m3dev/gokart,ml-experiments,,https://github.com/m3dev/gokart,https://github.com/m3dev/gokart,MIT,2018-12-23 07:40:27.000,2024-09-05 08:22:12.000000,2024-09-04 05:30:28,562.0,12.0,57.0,41.0,315.0,23.0,61.0,304.0,"Gokart solves reproducibility, task dependencies, constraints of good code, and ease of use for Machine Learning..",41.0,25,True,2024-09-04 06:00:45.000,1.5.0,82.0,gokart,,,,,3956.0,88.0,80.0,https://pypi.org/project/gokart,2024-09-04 06:00:45.000,8.0,3956.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +530,lkpy,lenskit/lkpy,recommender-systems,,https://github.com/lenskit/lkpy,https://github.com/lenskit/lkpy,MIT,2018-06-08 21:05:10.000,2024-08-28 19:06:36.000000,2024-08-28 19:06:31,3583.0,589.0,60.0,7.0,322.0,46.0,102.0,264.0,Python recommendation toolkit.,14.0,25,False,2024-02-16 21:04:30.000,0.14.4,25.0,lenskit,conda-forge/lenskit,,,,2617.0,120.0,114.0,https://pypi.org/project/lenskit,2024-02-16 21:03:49.000,6.0,1911.0,https://anaconda.org/conda-forge/lenskit,2024-04-18 13:51:51.378,32480.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +531,prettymaps,marceloprates/prettymaps,geospatial-data,,https://github.com/marceloprates/prettymaps,https://github.com/marceloprates/prettymaps,AGPL-3.0,2021-03-05 12:22:05.000,2024-07-06 13:17:45.000000,2024-07-02 22:54:35,200.0,4.0,521.0,81.0,39.0,63.0,27.0,11101.0,"A small set of Python functions to draw pretty maps from OpenStreetMap data. Based on osmnx, matplotlib and shapely..",16.0,24,False,2024-07-02 22:56:31.000,1.3.0,13.0,prettymaps,conda-forge/prettymaps,,,,932.0,54.0,54.0,https://pypi.org/project/prettymaps,2024-07-02 22:56:31.000,,830.0,https://anaconda.org/conda-forge/prettymaps,2024-07-03 13:55:21.192,3265.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +532,PyText,facebookresearch/pytext,nlp,,https://github.com/facebookresearch/pytext,https://github.com/facebookresearch/pytext,BSD-3-Clause,2018-07-31 23:40:46.000,2022-10-17 19:55:31.000000,2022-10-17 19:51:05,1735.0,,801.0,168.0,1588.0,145.0,74.0,6341.0,A natural language modeling framework based on PyTorch.,234.0,24,False,2020-06-08 23:30:58.000,0.3.3,13.0,pytext-nlp,,,['pytorch'],387.0,136.0,21.0,21.0,https://pypi.org/project/pytext-nlp,2020-06-08 22:49:33.000,,131.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +533,MMF,facebookresearch/mmf,image,,https://github.com/facebookresearch/mmf,https://github.com/facebookresearch/mmf,BSD-3-Clause,2018-06-27 04:52:40.000,2024-05-25 03:02:04.000000,2024-05-25 02:46:48,1097.0,,924.0,114.0,675.0,146.0,543.0,5472.0,A modular framework for vision & language multimodal research from Facebook AI Research (FAIR).,118.0,24,True,2019-08-26 19:04:21.000,0.3.1,12.0,mmf,,,['pytorch'],,408.0,21.0,20.0,https://pypi.org/project/mmf,2020-06-12 22:15:02.000,1.0,408.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +534,textgenrnn,minimaxir/textgenrnn,nlp,,https://github.com/minimaxir/textgenrnn,https://github.com/minimaxir/textgenrnn,MIT,2017-08-07 02:13:37.000,2022-07-17 19:07:49.000000,2020-07-14 02:41:10,174.0,,749.0,136.0,43.0,141.0,98.0,4943.0,Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines..,19.0,24,False,2020-02-03 01:07:00.000,2.0.0,14.0,textgenrnn,,,['tensorflow'],943.0,811.0,1143.0,1127.0,https://pypi.org/project/textgenrnn,2020-02-02 21:16:15.000,16.0,799.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +535,AugLy,facebookresearch/AugLy,others,,https://github.com/facebookresearch/AugLy,https://github.com/facebookresearch/AugLy,MIT,2021-06-09 17:57:28.000,2024-08-23 15:25:36.000000,2024-08-23 14:49:22,219.0,1.0,296.0,77.0,179.0,24.0,54.0,4937.0,"A data augmentations library for audio, image, text, and video.",35.0,24,True,2023-12-05 20:52:12.000,1.0.1,18.0,augly,,,,,2939.0,142.0,138.0,https://pypi.org/project/augly,2023-12-05 20:52:12.000,4.0,2939.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +536,segmentation_models,qubvel/segmentation_models,image,,https://github.com/qubvel/segmentation_models,https://github.com/qubvel/segmentation_models,MIT,2018-06-05 13:27:56.000,2024-08-21 11:16:16.000000,2024-08-21 11:16:16,206.0,1.0,1015.0,92.0,64.0,257.0,270.0,4701.0,Segmentation models with pretrained backbones. Keras and TensorFlow Keras.,15.0,24,True,2020-01-10 11:36:02.000,1.0.1,8.0,segmentation_models,,,['tensorflow'],,31024.0,28.0,,https://pypi.org/project/segmentation_models,2020-01-10 11:36:02.000,28.0,31024.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +537,TensorTrade,tensortrade-org/tensortrade,financial-data,,https://github.com/tensortrade-org/tensortrade,https://github.com/tensortrade-org/tensortrade,Apache-2.0,2019-07-30 21:28:32.000,2024-06-09 21:29:46.000000,2024-06-09 21:29:43,1062.0,2.0,982.0,242.0,217.0,51.0,203.0,4497.0,"An open source reinforcement learning framework for training, evaluating, and deploying robust trading agents.",61.0,24,True,2021-05-10 18:04:30.000,1.0.3,27.0,tensortrade,conda-forge/tensortrade,,,,798.0,61.0,60.0,https://pypi.org/project/tensortrade,2021-05-10 18:00:35.000,1.0,704.0,https://anaconda.org/conda-forge/tensortrade,2023-06-16 19:25:40.006,3877.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +538,Stable Baselines,hill-a/stable-baselines,reinforcement-learning,,https://github.com/hill-a/stable-baselines,https://github.com/hill-a/stable-baselines,MIT,2018-07-02 14:28:59.000,2022-09-04 14:04:44.000000,2022-09-04 14:04:44,839.0,,727.0,62.0,247.0,130.0,824.0,4122.0,"A fork of OpenAI Baselines, implementations of reinforcement learning algorithms.",114.0,24,False,2021-04-06 12:38:10.521,2.10.2,31.0,stable-baselines,,,,,5315.0,21.0,,https://pypi.org/project/stable-baselines,2021-04-06 12:38:10.521,21.0,5315.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +539,Snips NLU,snipsco/snips-nlu,nlp,,https://github.com/snipsco/snips-nlu,https://github.com/snipsco/snips-nlu,Apache-2.0,2017-02-08 16:16:36.000,2023-05-22 16:10:15.000000,2021-05-03 12:18:31,2154.0,,511.0,133.0,649.0,65.0,198.0,3886.0,Snips Python library to extract meaning from text.,22.0,24,False,2020-01-15 10:13:17.000,0.20.2,58.0,snips-nlu,,,,,972.0,13.0,,https://pypi.org/project/snips-nlu,2020-01-15 10:13:17.000,13.0,972.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +540,Chartify,spotify/chartify,data-viz,,https://github.com/spotify/chartify,https://github.com/spotify/chartify,Apache-2.0,2018-09-17 14:12:05.000,2024-03-20 17:23:36.000000,2023-10-12 08:57:51,209.0,,324.0,86.0,95.0,51.0,32.0,3512.0,Python library that makes it easy for data scientists to create charts.,25.0,24,True,2023-10-12 09:02:25.000,4.0.5,25.0,chartify,conda-forge/chartify,,,,2708.0,87.0,78.0,https://pypi.org/project/chartify,2023-10-12 09:02:25.000,9.0,2245.0,https://anaconda.org/conda-forge/chartify,2023-06-16 16:11:58.064,32474.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +541,AdaNet,tensorflow/adanet,hyperopt,,https://github.com/tensorflow/adanet,https://github.com/tensorflow/adanet,Apache-2.0,2018-06-28 20:20:24.000,2023-11-30 16:30:21.000000,2021-08-30 19:33:24,440.0,,527.0,173.0,50.0,67.0,49.0,3470.0,Fast and flexible AutoML with learning guarantees.,27.0,24,False,2020-07-09 21:03:28.000,0.9.0,13.0,adanet,,,['tensorflow'],,214.0,61.0,59.0,https://pypi.org/project/adanet,2020-07-09 21:03:28.000,2.0,214.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +542,PyTorch-BigGraph,facebookresearch/PyTorch-BigGraph,graph,,https://github.com/facebookresearch/PyTorch-BigGraph,https://github.com/facebookresearch/PyTorch-BigGraph,BSD-3-Clause,2018-10-01 20:41:16.000,2024-03-03 01:42:05.000000,2024-03-03 01:31:19,175.0,,447.0,89.0,78.0,67.0,137.0,3363.0,Generate embeddings from large-scale graph-structured data.,32.0,24,True,2019-10-14 16:45:11.000,1.0.0,4.0,torchbiggraph,,,['pytorch'],200.0,454582.0,2.0,,https://pypi.org/project/torchbiggraph,2019-10-14 16:44:41.000,2.0,454579.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +543,Hummingbird,microsoft/hummingbird,model-serialisation,,https://github.com/microsoft/hummingbird,https://github.com/microsoft/hummingbird,MIT,2020-03-12 20:27:03.000,2024-08-23 09:06:37.000000,2024-08-12 16:29:55,476.0,7.0,276.0,50.0,474.0,70.0,259.0,3331.0,Hummingbird compiles trained ML models into tensor computation for faster inference.,40.0,24,True,2024-03-08 20:24:53.000,0.4.11,24.0,hummingbird-ml,conda-forge/hummingbird-ml,,,627.0,4992.0,7.0,,https://pypi.org/project/hummingbird-ml,2024-03-08 20:21:40.000,7.0,3867.0,https://anaconda.org/conda-forge/hummingbird-ml,2024-03-08 22:15:29.532,46751.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +544,PARL,PaddlePaddle/PARL,reinforcement-learning,,https://github.com/PaddlePaddle/PARL,https://github.com/PaddlePaddle/PARL,Apache-2.0,2018-04-25 17:54:22.000,2024-07-30 10:50:08.000000,2024-07-09 09:34:16,515.0,1.0,814.0,62.0,642.0,133.0,404.0,3240.0,A high-performance distributed training framework for Reinforcement Learning.,45.0,24,True,2023-03-14 02:03:08.557,2.2.1,29.0,parl,,,['paddle'],,754.0,130.0,129.0,https://pypi.org/project/parl,2022-05-13 04:46:41.000,1.0,754.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +545,DeepVariant,google/deepvariant,medical-data,,https://github.com/google/deepvariant,https://github.com/google/deepvariant,BSD-3-Clause,2017-11-23 01:56:22.000,2024-08-27 16:46:19.000000,2024-03-18 19:51:35,2374.0,,712.0,158.0,61.0,6.0,808.0,3162.0,DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA..,30.0,24,True,2024-03-19 19:20:10.000,1.6.1,21.0,,bioconda/deepvariant,,['tensorflow'],4751.0,911.0,,,,,,,https://anaconda.org/bioconda/deepvariant,2023-06-16 16:08:50.013,68277.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +546,Towhee,towhee-io/towhee,ml-frameworks,,https://github.com/towhee-io/towhee,https://github.com/towhee-io/towhee,Apache-2.0,2021-07-13 08:28:50.000,2024-01-20 00:01:11.000000,2024-01-20 00:01:11,1576.0,,246.0,31.0,2015.0,3.0,654.0,3152.0,Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.,35.0,24,True,2023-12-05 02:33:36.000,1.1.3,26.0,towhee,,,,2683.0,29643.0,,,https://pypi.org/project/towhee,2023-12-04 07:25:10.000,,29562.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +547,xLearn,aksnzhy/xlearn,ml-frameworks,,https://github.com/aksnzhy/xlearn,https://github.com/aksnzhy/xlearn,Apache-2.0,2017-06-10 08:09:31.000,2023-08-28 05:14:10.000000,2022-06-05 10:44:18,1342.0,,528.0,110.0,73.0,193.0,117.0,3082.0,"High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization..",30.0,24,False,2019-04-25 02:10:05.000,0.4.4,15.0,xlearn,,,,4659.0,1045.0,162.0,150.0,https://pypi.org/project/xlearn,2018-12-04 11:05:06.000,12.0,986.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +548,ffcv,libffcv/ffcv,image,,https://github.com/libffcv/ffcv,https://github.com/libffcv/ffcv,Apache-2.0,2021-10-13 17:03:39.000,2024-06-16 15:59:22.000000,2024-05-06 14:20:38,944.0,,171.0,20.0,78.0,102.0,177.0,2821.0,FFCV: Fast Forward Computer Vision (and other ML workloads!).,31.0,24,True,2023-03-05 05:44:00.314,1.0.2,7.0,ffcv,,,,,1205.0,54.0,53.0,https://pypi.org/project/ffcv,2022-01-28 20:40:22.000,1.0,1205.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +549,tensorflow-graphics,tensorflow/graphics,image,,https://github.com/tensorflow/graphics,https://github.com/tensorflow/graphics,Apache-2.0,2019-01-08 10:39:44.000,2024-08-01 02:26:29.000000,2024-08-01 02:26:24,769.0,2.0,361.0,90.0,550.0,143.0,92.0,2749.0,TensorFlow Graphics: Differentiable Graphics Layers for TensorFlow.,39.0,24,True,2021-12-03 22:33:39.000,2021.12.3,25.0,tensorflow-graphics,,,['tensorflow'],,12950.0,11.0,,https://pypi.org/project/tensorflow-graphics,2021-12-03 22:33:39.000,11.0,12950.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +550,HiPlot,facebookresearch/hiplot,data-viz,,https://github.com/facebookresearch/hiplot,https://github.com/facebookresearch/hiplot,MIT,2019-11-08 13:06:41.000,2024-01-10 07:43:27.000000,2023-07-19 07:40:10,212.0,,137.0,28.0,200.0,20.0,73.0,2738.0,HiPlot makes understanding high dimensional data easy.,9.0,24,False,2022-05-31 09:00:35.000,0.1.33,113.0,hiplot,conda-forge/hiplot,,,,47623.0,458.0,432.0,https://pypi.org/project/hiplot,2022-07-05 08:51:12.000,26.0,43937.0,https://anaconda.org/conda-forge/hiplot,2023-06-16 19:18:10.488,202762.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +551,Mars,mars-project/mars,others,,https://github.com/mars-project/mars,https://github.com/mars-project/mars,Apache-2.0,2018-12-05 16:04:03.000,2024-01-02 10:00:14.000000,2023-11-02 03:13:52,1297.0,,325.0,92.0,2157.0,214.0,982.0,2692.0,"Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and..",53.0,24,True,2023-02-03 19:04:11.785,0.8.1,118.0,pymars,,,,,14258.0,2.0,,https://pypi.org/project/pymars,2022-06-12 11:43:21.000,2.0,14258.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +552,promptsource,bigscience-workshop/promptsource,nlp,,https://github.com/bigscience-workshop/promptsource,https://github.com/bigscience-workshop/promptsource,Apache-2.0,2021-05-19 15:26:25.000,2023-10-23 17:59:41.000000,2023-10-23 17:59:40,755.0,,345.0,32.0,695.0,43.0,151.0,2640.0,"Toolkit for creating, sharing and using natural language prompts.",65.0,24,True,2022-07-02 17:57:17.000,0.2.3,5.0,promptsource,,,,,357.0,111.0,107.0,https://pypi.org/project/promptsource,2022-04-18 22:31:03.000,4.0,357.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +553,pytorch_geometric_temporal,benedekrozemberczki/pytorch_geometric_temporal,graph,,https://github.com/benedekrozemberczki/pytorch_geometric_temporal,https://github.com/benedekrozemberczki/pytorch_geometric_temporal,MIT,2020-06-27 01:11:33.000,2024-06-18 18:31:40.000000,2023-07-01 21:40:58,1936.0,,366.0,39.0,91.0,41.0,158.0,2611.0,PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021).,28.0,24,False,2022-09-04 16:37:07.000,0.54.0,46.0,torch-geometric-temporal,,,['pytorch'],,1568.0,7.0,,https://pypi.org/project/torch-geometric-temporal,2022-09-04 16:10:00.738,7.0,1568.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +554,Kashgari,BrikerMan/Kashgari,nlp,,https://github.com/BrikerMan/Kashgari,https://github.com/BrikerMan/Kashgari,Apache-2.0,2019-01-19 01:53:28.000,2024-09-03 21:05:29.000000,2021-07-09 03:57:16,955.0,,439.0,64.0,123.0,32.0,350.0,2386.0,Kashgari is a production-level NLP Transfer learning framework built on top of tf.keras for text-labeling and text-..,21.0,24,False,2021-07-04 10:44:36.000,2.0.2,24.0,kashgari-tf,,,['tensorflow'],,135.0,71.0,69.0,https://pypi.org/project/kashgari-tf,2019-10-18 07:57:55.000,2.0,135.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +555,python_speech_features,jameslyons/python_speech_features,audio,,https://github.com/jameslyons/python_speech_features,https://github.com/jameslyons/python_speech_features,MIT,2013-10-31 02:42:08.000,2021-10-20 10:08:48.000000,2020-12-31 13:27:01,120.0,,618.0,88.0,29.0,25.0,52.0,2360.0,This library provides common speech features for ASR including MFCCs and filterbank energies.,19.0,24,False,2020-01-14 14:12:10.000,0.6.1,6.0,python_speech_features,,,,,23634.0,742.0,689.0,https://pypi.org/project/python_speech_features,2017-08-16 01:46:13.000,53.0,23634.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +556,Neural Tangents,google/neural-tangents,ml-frameworks,,https://github.com/google/neural-tangents,https://github.com/google/neural-tangents,Apache-2.0,2019-04-08 16:48:48.000,2024-03-01 17:17:03.000000,2024-03-01 17:16:56,650.0,,236.0,63.0,32.0,60.0,95.0,2262.0,Fast and Easy Infinite Neural Networks in Python.,29.0,24,True,2023-12-11 14:10:12.000,0.6.5,31.0,neural-tangents,,,,457.0,2366.0,112.0,111.0,https://pypi.org/project/neural-tangents,2023-12-11 14:00:20.000,1.0,2358.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +557,CausalNex,quantumblacklabs/causalnex,interpretability,,https://github.com/mckinsey/causalnex,https://github.com/mckinsey/causalnex,Apache-2.0,2019-12-12 15:26:09.000,2024-06-26 08:22:56.000000,2024-02-10 10:17:50,226.0,,255.0,49.0,98.0,23.0,116.0,2210.0,A Python library that helps data scientists to infer causation rather than observing correlation.,40.0,24,True,2023-06-22 13:11:59.629,0.12.1,20.0,causalnex,,,"['pytorch', 'sklearn']",,3228.0,131.0,127.0,https://pypi.org/project/causalnex,2023-06-22 13:11:59.629,4.0,3228.0,,,,3.0,,,,,,,,mckinsey/causalnex,,,,,,,,,,,,,,,,, +558,Karate Club,benedekrozemberczki/karateclub,graph,,https://github.com/benedekrozemberczki/karateclub,https://github.com/benedekrozemberczki/karateclub,GPL-3.0,2019-12-05 17:35:56.000,2024-07-17 19:00:35.000000,2024-07-17 19:00:21,2319.0,5.0,244.0,38.0,39.0,7.0,114.0,2134.0,Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020).,20.0,24,False,2022-12-04 19:04:05.000,_10304,107.0,karateclub,conda-forge/karateclub,,,,5829.0,273.0,260.0,https://pypi.org/project/karateclub,2022-10-22 13:31:38.000,13.0,5311.0,https://anaconda.org/conda-forge/karateclub,2023-06-16 19:21:04.092,25911.0,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +559,FinTA,peerchemist/finta,financial-data,,https://github.com/peerchemist/finta,https://github.com/peerchemist/finta,LGPL-3.0,2016-09-01 21:02:46.000,2022-07-24 08:40:51.000000,2022-07-24 08:40:51,394.0,,669.0,84.0,48.0,24.0,64.0,2109.0,Common financial technical indicators implemented in Pandas.,28.0,24,False,2021-04-03 08:51:49.000,1.3,19.0,finta,,,,,8551.0,543.0,531.0,https://pypi.org/project/finta,2020-10-21 11:39:44.000,12.0,8551.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +560,checklist,marcotcr/checklist,interpretability,,https://github.com/marcotcr/checklist,https://github.com/marcotcr/checklist,MIT,2020-03-09 17:18:49.000,2024-01-09 01:46:07.000000,2023-09-26 17:27:56,255.0,,203.0,29.0,65.0,11.0,83.0,1995.0,Beyond Accuracy: Behavioral Testing of NLP models with CheckList.,15.0,24,True,2021-05-24 16:45:59.000,0.0.11,10.0,checklist,conda-forge/checklist,,['jupyter'],,1264.0,368.0,360.0,https://pypi.org/project/checklist,2021-05-24 16:45:59.000,8.0,1087.0,https://anaconda.org/conda-forge/checklist,2023-06-16 19:24:18.549,7798.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +561,Hivemind,learning-at-home/hivemind,distributed-ml,,https://github.com/learning-at-home/hivemind,https://github.com/learning-at-home/hivemind,MIT,2020-02-27 13:50:19.000,2024-07-16 07:33:35.000000,2024-07-15 22:10:03,578.0,7.0,154.0,56.0,463.0,74.0,103.0,1991.0,Decentralized deep learning in PyTorch. Built to train models on thousands of volunteers across the world.,32.0,24,True,2023-08-31 20:07:52.000,1.1.10,27.0,hivemind,,,,,920.0,120.0,110.0,https://pypi.org/project/hivemind,2023-08-31 20:07:10.000,10.0,920.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +562,TF Recommenders,tensorflow/recommenders,recommender-systems,,https://github.com/tensorflow/recommenders,https://github.com/tensorflow/recommenders,Apache-2.0,2020-06-26 21:38:01.000,2024-08-16 19:10:13.000000,2024-08-16 19:10:08,367.0,2.0,272.0,49.0,320.0,262.0,184.0,1815.0,TensorFlow Recommenders is a library for building recommender system models using TensorFlow.,43.0,24,True,2023-02-03 02:17:00.422,0.7.3,16.0,tensorflow-recommenders,,,['tensorflow'],,380964.0,2.0,,https://pypi.org/project/tensorflow-recommenders,2023-02-03 02:17:00.422,2.0,380964.0,,,,3.0,,,,,,-6.0,,,,,,,,,,,,,,,,,,, +563,sense2vec,explosion/sense2vec,nlp,,https://github.com/explosion/sense2vec,https://github.com/explosion/sense2vec,MIT,2016-01-23 22:15:49.000,2024-03-17 06:23:46.000000,2023-04-20 14:53:46,460.0,,238.0,49.0,49.0,23.0,91.0,1615.0,Contextually-keyed word vectors.,19.0,24,False,2023-04-17 14:14:02.218,2.0.2,24.0,sense2vec,conda-forge/sense2vec,,,67393.0,4857.0,412.0,399.0,https://pypi.org/project/sense2vec,2021-04-19 07:05:28.000,13.0,2787.0,https://anaconda.org/conda-forge/sense2vec,2023-09-22 07:25:32.800,45423.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +564,Higher,facebookresearch/higher,pytorch-utils,,https://github.com/facebookresearch/higher,https://github.com/facebookresearch/higher,Apache-2.0,2019-09-06 18:58:36.000,2022-03-25 15:56:51.000000,2021-10-26 07:08:33,31.0,,121.0,28.0,31.0,63.0,50.0,1578.0,higher is a pytorch library allowing users to obtain higher order gradients over losses spanning training loops rather..,9.0,24,False,2020-07-14 12:20:32.000,0.2.1,2.0,higher,,,['pytorch'],,254739.0,523.0,516.0,https://pypi.org/project/higher,2020-07-14 12:20:32.000,7.0,254739.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +565,EfficientNets,rwightman/gen-efficientnet-pytorch,pytorch-utils,,https://github.com/rwightman/gen-efficientnet-pytorch,https://github.com/rwightman/gen-efficientnet-pytorch,Apache-2.0,2019-05-11 19:35:56.000,2024-06-13 23:15:42.000000,2024-06-13 23:15:42,109.0,1.0,214.0,43.0,12.0,4.0,51.0,1568.0,"Pretrained EfficientNet, EfficientNet-Lite, MixNet, MobileNetV3 / V2, MNASNet A1 and B1, FBNet, Single-Path NAS.",5.0,24,True,2021-07-08 19:05:05.000,1.0.2,10.0,geffnet,,,['pytorch'],,182087.0,250.0,246.0,https://pypi.org/project/geffnet,2021-07-08 19:05:05.000,4.0,182087.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +566,fklearn,nubank/fklearn,ml-frameworks,,https://github.com/nubank/fklearn,https://github.com/nubank/fklearn,Apache-2.0,2019-02-27 14:32:57.000,2024-08-14 21:07:18.000000,2024-08-14 20:38:00,159.0,2.0,163.0,103.0,189.0,40.0,25.0,1499.0,fklearn: Functional Machine Learning.,56.0,24,True,2024-08-14 21:07:18.000,4.0.0,34.0,fklearn,,,,,1614.0,14.0,14.0,https://pypi.org/project/fklearn,2024-08-14 21:07:18.000,,1614.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +567,stockstats,jealous/stockstats,financial-data,,https://github.com/jealous/stockstats,https://github.com/jealous/stockstats,BSD-3-Clause,2016-06-05 15:21:22.000,2024-01-05 18:00:58.000000,2024-01-05 18:00:58,67.0,,296.0,55.0,63.0,16.0,110.0,1277.0,Supply a wrapper ``StockDataFrame`` based on the ``pandas.DataFrame`` with inline stock statistics/indicators support.,10.0,24,True,2023-07-30 07:07:37.000,0.6.2,24.0,stockstats,,,,,7978.0,1101.0,1090.0,https://pypi.org/project/stockstats,2023-07-30 07:07:37.000,11.0,7978.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +568,RLax,deepmind/rlax,reinforcement-learning,,https://github.com/google-deepmind/rlax,https://github.com/google-deepmind/rlax,Apache-2.0,2020-02-18 07:14:59.000,2024-05-24 12:07:23.000000,2024-05-24 12:07:18,209.0,,85.0,34.0,110.0,8.0,18.0,1232.0,A library of reinforcement learning building blocks in JAX.,21.0,24,True,2023-06-29 15:05:00.621,0.1.6,10.0,rlax,,,['jax'],,19846.0,276.0,265.0,https://pypi.org/project/rlax,2023-01-09 22:29:35.947,11.0,19846.0,,,,3.0,,,,,,,,google-deepmind/rlax,,,,,,,,,,,,,,,,, +569,TFEncrypted,tf-encrypted/tf-encrypted,privacy-ml,,https://github.com/tf-encrypted/tf-encrypted,https://github.com/tf-encrypted/tf-encrypted,Apache-2.0,2018-03-21 18:22:13.000,2023-10-19 08:20:16.000000,2023-02-08 02:25:50,604.0,,206.0,53.0,460.0,144.0,294.0,1201.0,A Framework for Encrypted Machine Learning in TensorFlow.,29.0,24,False,2023-02-08 02:53:00.720,0.9.1,41.0,tf-encrypted,,,['tensorflow'],,448.0,76.0,67.0,https://pypi.org/project/tf-encrypted,2022-11-16 09:12:55.841,9.0,448.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +570,ChainerRL,chainer/chainerrl,reinforcement-learning,,https://github.com/chainer/chainerrl,https://github.com/chainer/chainerrl,MIT,2017-01-30 04:58:15.000,2021-08-10 18:25:48.000000,2021-04-17 06:02:30,3471.0,,221.0,70.0,415.0,75.0,147.0,1163.0,ChainerRL is a deep reinforcement learning library built on top of Chainer.,28.0,24,False,2020-02-14 05:35:56.000,0.8.0,10.0,chainerrl,,,,,421.0,175.0,170.0,https://pypi.org/project/chainerrl,2020-02-14 05:35:56.000,5.0,421.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +571,keract,philipperemy/keract,interpretability,,https://github.com/philipperemy/keract,https://github.com/philipperemy/keract,MIT,2017-05-17 04:50:57.000,2024-08-14 00:01:42.000000,2023-11-17 10:59:26,412.0,,184.0,33.0,74.0,3.0,86.0,1039.0,Layers Outputs and Gradients in Keras. Made easy.,16.0,24,True,2022-09-25 14:40:40.377,4.5.1,39.0,keract,,,['tensorflow'],,5197.0,233.0,224.0,https://pypi.org/project/keract,2022-09-25 14:40:40.377,9.0,5197.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +572,Plotly-Resampler,predict-idlab/plotly-resampler,data-viz,,https://github.com/predict-idlab/plotly-resampler,https://github.com/predict-idlab/plotly-resampler,MIT,2021-11-20 10:51:56.000,2024-08-30 07:29:10.000000,2024-08-24 15:16:00,781.0,1.0,67.0,14.0,129.0,51.0,117.0,1003.0,Visualize large time series data with plotly.py.,12.0,24,True,2024-03-27 07:58:10.000,0.10.0,62.0,plotly-resampler,conda-forge/plotly-resampler,,,,329928.0,1379.0,1355.0,https://pypi.org/project/plotly-resampler,2024-03-27 07:54:02.000,24.0,327958.0,https://anaconda.org/conda-forge/plotly-resampler,2024-03-29 13:25:52.761,63051.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +573,scikit-cuda,lebedov/scikit-cuda,gpu-utilities,,https://github.com/lebedov/scikit-cuda,https://github.com/lebedov/scikit-cuda,BSD-3-Clause,2010-09-27 02:02:07.000,2023-10-15 05:57:46.000000,2023-10-15 05:57:46,1036.0,,175.0,48.0,114.0,53.0,170.0,981.0,Python interface to GPU-powered libraries.,44.0,24,True,2019-05-27 00:29:00.000,0.5.3,7.0,scikit-cuda,,,,,803.0,327.0,304.0,https://pypi.org/project/scikit-cuda,2019-05-27 00:29:00.000,23.0,803.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +574,Neural Structured Learning,tensorflow/neural-structured-learning,tensorflow-utils,,https://github.com/tensorflow/neural-structured-learning,https://github.com/tensorflow/neural-structured-learning,Apache-2.0,2019-08-27 21:48:16.000,2024-06-18 13:19:37.000000,2024-06-18 13:19:34,568.0,1.0,191.0,48.0,61.0,1.0,68.0,980.0,Training neural models with structured signals.,38.0,24,True,2022-07-29 21:05:16.715,1.4.0,8.0,neural-structured-learning,,,['tensorflow'],,8452.0,478.0,475.0,https://pypi.org/project/neural-structured-learning,2022-07-29 21:05:16.715,3.0,8452.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +575,Runhouse,run-house/runhouse,ml-frameworks,,https://github.com/run-house/runhouse,https://github.com/run-house/runhouse,Apache-2.0,2022-05-10 14:10:51.000,2024-09-05 14:46:49.000000,2024-09-05 14:46:47,1718.0,291.0,35.0,9.0,1180.0,9.0,42.0,956.0,"Orchestrate heterogeneous ML workloads in Python, like PyTorch for ML infra. Iterable, debuggable, multi-cloud,..",15.0,24,True,2024-09-04 17:42:13.000,0.0.33,41.0,runhouse,,,,31.0,26421.0,1.0,,https://pypi.org/project/runhouse,2024-09-04 16:41:42.000,1.0,26420.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,,True +576,TSFEL,fraunhoferportugal/tsfel,time-series-data,,https://github.com/fraunhoferportugal/tsfel,https://github.com/fraunhoferportugal/tsfel,BSD-3-Clause,2019-01-09 16:41:30.000,2024-09-05 15:05:49.000000,2024-08-27 12:49:30,410.0,38.0,143.0,19.0,84.0,6.0,66.0,901.0,An intuitive library to extract features from time series.,20.0,24,True,2024-08-27 13:19:18.000,0.1.8,12.0,tsfel,,,,,25191.0,152.0,145.0,https://pypi.org/project/tsfel,2024-08-27 13:07:53.000,7.0,25191.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +577,NeuPy,itdxer/neupy,ml-frameworks,,https://github.com/itdxer/neupy,https://github.com/itdxer/neupy,MIT,2015-08-24 19:45:11.000,2023-01-03 21:24:56.000000,2023-01-03 21:24:56,1146.0,,158.0,33.0,25.0,34.0,236.0,742.0,NeuPy is a Tensorflow based python library for prototyping and building neural networks.,8.0,24,False,2019-04-04 19:44:59.000,0.8.2,34.0,neupy,,,,,2019.0,180.0,176.0,https://pypi.org/project/neupy,2019-04-04 19:43:06.000,4.0,2019.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +578,aequitas,dssg/aequitas,interpretability,,https://github.com/dssg/aequitas,https://github.com/dssg/aequitas,MIT,2018-02-13 19:40:30.000,2024-09-03 13:49:16.000000,2024-08-28 13:16:20,919.0,8.0,111.0,43.0,117.0,51.0,47.0,665.0,Bias Auditing & Fair ML Toolkit.,22.0,24,True,2024-01-30 12:03:19.000,1.0.0,18.0,aequitas,,,,,20623.0,176.0,168.0,https://pypi.org/project/aequitas,2024-01-30 12:03:19.000,8.0,20623.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +579,Mapbox GL,mapbox/mapboxgl-jupyter,geospatial-data,,https://github.com/mapbox/mapboxgl-jupyter,https://github.com/mapbox/mapboxgl-jupyter,MIT,2017-08-08 15:10:51.000,2022-01-11 05:18:07.000000,2021-04-19 05:00:36,221.0,,136.0,130.0,91.0,42.0,67.0,661.0,Use Mapbox GL JS to visualize data in a Python Jupyter notebook.,22.0,24,False,2019-06-03 21:24:10.000,0.10.2,20.0,mapboxgl,,,['jupyter'],,14522.0,223.0,211.0,https://pypi.org/project/mapboxgl,2019-06-02 16:02:54.380,12.0,14522.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +580,SKLL,EducationalTestingService/skll,ml-experiments,,https://github.com/EducationalTestingService/skll,https://github.com/EducationalTestingService/skll,BSD-1-Clause,2013-08-02 14:31:46.000,2024-07-30 17:53:48.000000,2024-07-30 17:53:48,3762.0,11.0,69.0,46.0,358.0,21.0,397.0,552.0,SciKit-Learn Laboratory (SKLL) makes it easy to run machine learning experiments.,37.0,24,False,2024-03-08 20:13:23.000,5.0.1,71.0,skll,conda-forge/skll,,['sklearn'],14.0,1080.0,46.0,44.0,https://pypi.org/project/skll,2024-03-08 20:01:40.000,2.0,601.0,https://anaconda.org/conda-forge/skll,2024-03-09 00:32:37.185,16314.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +581,findspark,minrk/findspark,others,,https://github.com/minrk/findspark,https://github.com/minrk/findspark,BSD-3-Clause,2015-06-12 21:34:06.000,2023-06-16 13:16:45.065000,2022-02-11 07:59:35,77.0,,72.0,8.0,17.0,11.0,12.0,510.0,Find pyspark to make it importable.,15.0,24,False,2022-02-11 08:02:06.000,2.0.1,14.0,findspark,conda-forge/findspark,,['spark'],,2473567.0,4834.0,4731.0,https://pypi.org/project/findspark,2022-02-11 08:02:06.000,103.0,2464275.0,https://anaconda.org/conda-forge/findspark,2023-06-16 13:16:45.065,919937.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +582,scikit-posthocs,maximtrp/scikit-posthocs,probabilistics,,https://github.com/maximtrp/scikit-posthocs,https://github.com/maximtrp/scikit-posthocs,MIT,2017-06-22 19:41:37.000,2024-07-08 15:42:44.119000,2024-06-26 08:01:19,535.0,3.0,40.0,5.0,16.0,7.0,51.0,331.0,Multiple Pairwise Comparisons (Post Hoc) Tests in Python.,15.0,24,True,2024-02-18 18:57:32.000,0.9.0,25.0,scikit-posthocs,conda-forge/scikit-posthocs,,['sklearn'],57.0,121760.0,851.0,803.0,https://pypi.org/project/scikit-posthocs,2024-02-18 18:57:32.000,48.0,101274.0,https://anaconda.org/conda-forge/scikit-posthocs,2024-07-08 15:42:44.119,962878.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +583,pandas-ai,gventuri/pandas-ai,others,,https://github.com/Sinaptik-AI/pandas-ai,https://github.com/Sinaptik-AI/pandas-ai,,2023-04-22 12:58:01.000,2024-08-31 15:20:57.000000,2024-08-31 15:20:52,1052.0,70.0,1187.0,103.0,505.0,100.0,585.0,12503.0,"Chat with your database (SQL, CSV, pandas, polars, mongodb, noSQL, etc). PandasAI makes data analysis conversational..",88.0,23,False,2024-08-06 09:48:26.000,2.2.14,100.0,pandas-ai,,,,,,,,https://pypi.org/project/pandas-ai,,,,,,,3.0,,,,,,-4.0,,Sinaptik-AI/pandas-ai,,,,,,,,,,,,,,,,, +584,Dejavu,worldveil/dejavu,audio,,https://github.com/worldveil/dejavu,https://github.com/worldveil/dejavu,MIT,2013-11-19 02:50:35.000,2024-04-22 19:23:00.000000,2020-06-03 05:58:03,146.0,,1379.0,262.0,69.0,115.0,136.0,6397.0,Audio fingerprinting and recognition in Python.,23.0,23,False,2015-04-19 21:20:16.000,0.1.3,4.0,PyDejavu,,,,,168.0,21.0,21.0,https://pypi.org/project/PyDejavu,2015-04-19 21:20:16.000,,168.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +585,T5,google-research/text-to-text-transfer-transformer,nlp,,https://github.com/google-research/text-to-text-transfer-transformer,https://github.com/google-research/text-to-text-transfer-transformer,Apache-2.0,2019-10-17 21:45:14.000,2024-06-28 18:04:33.000000,2024-06-28 18:04:28,599.0,1.0,745.0,105.0,590.0,107.0,345.0,6099.0,Code for the paper Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer.,59.0,23,True,2023-03-30 16:55:07.154,0.9.4,29.0,t5,,,['tensorflow'],,66860.0,2.0,,https://pypi.org/project/t5,2021-10-18 13:55:26.000,2.0,66860.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +586,Backtesting.py,kernc/backtesting.py,financial-data,,https://github.com/kernc/backtesting.py,https://github.com/kernc/backtesting.py,AGPL-3.0,2019-01-02 03:11:32.000,2024-08-06 12:05:27.000000,2023-01-15 11:37:16,279.0,,1033.0,117.0,105.0,172.0,355.0,5292.0,Backtest trading strategies in Python.,19.0,23,False,2021-12-13 01:36:44.000,0.3.3,21.0,backtesting,,,,,15142.0,5.0,,https://pypi.org/project/backtesting,2021-12-13 01:36:44.000,5.0,15142.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +587,Crypto Signals,CryptoSignal/crypto-signal,financial-data,,https://github.com/CryptoSignal/Crypto-Signal,https://github.com/CryptoSignal/Crypto-Signal,MIT,2017-09-16 23:49:24.000,2024-07-07 15:33:11.000000,2022-08-09 13:26:32,565.0,,1253.0,307.0,210.0,66.0,211.0,4842.0,"Github.com/CryptoSignal - Trading & Technical Analysis Bot - 4,100+ stars, 1,100+ forks.",28.0,23,False,,,,,,,,,1709.0,,,,,,,,,,3.0,shadowreaver/crypto-signal,https://hub.docker.com/r/shadowreaver/crypto-signal,2020-09-03 13:00:35.801133,8.0,143568.0,,,,,,,,,,,,,,,,,,,, +588,neon,NervanaSystems/neon,ml-frameworks,,https://github.com/NervanaSystems/neon,https://github.com/NervanaSystems/neon,Apache-2.0,2014-10-16 01:00:17.000,2024-08-13 17:48:41.449000,2019-05-22 18:27:54,1118.0,,811.0,326.0,89.0,91.0,306.0,3870.0,Intel Nervana reference deep learning framework committed to best performance on all hardware.,108.0,23,False,2018-01-05 23:25:04.000,2.6.0,32.0,nervananeon,anaconda/neon,,,398.0,135.0,,,https://pypi.org/project/nervananeon,2018-01-05 23:25:04.000,,115.0,https://anaconda.org/anaconda/neon,2024-08-13 17:48:41.449,1711.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +589,PandasGUI,adamerose/pandasgui,data-viz,,https://github.com/adamerose/PandasGUI,https://github.com/adamerose/PandasGUI,MIT-0,2019-06-12 02:19:42.000,2023-12-07 20:40:17.000000,2023-12-07 20:40:17,720.0,,229.0,54.0,36.0,75.0,125.0,3172.0,A GUI for Pandas DataFrames.,14.0,23,False,2023-02-11 20:04:00.783,0.2.14,44.0,pandasgui,conda-forge/pandasgui,,['pandas'],,4488.0,430.0,416.0,https://pypi.org/project/pandasgui,2021-08-14 09:14:51.000,14.0,3890.0,https://anaconda.org/conda-forge/pandasgui,2023-06-16 19:24:31.206,26322.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +590,DDSP,magenta/ddsp,audio,,https://github.com/magenta/ddsp,https://github.com/magenta/ddsp,Apache-2.0,2020-01-14 18:38:27.000,2024-06-17 16:48:21.000000,2024-06-17 16:48:16,471.0,1.0,322.0,67.0,318.0,50.0,124.0,2852.0,DDSP: Differentiable Digital Signal Processing.,32.0,23,True,2023-05-25 02:30:41.654,3.7.0,55.0,ddsp,conda-forge/ddsp,,['tensorflow'],,1788.0,59.0,58.0,https://pypi.org/project/ddsp,2022-05-25 17:42:19.000,1.0,1443.0,https://anaconda.org/conda-forge/ddsp,2023-06-16 19:19:34.916,17612.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +591,Luminoth,tryolabs/luminoth,image,,https://github.com/tryolabs/luminoth,https://github.com/tryolabs/luminoth,BSD-3-Clause,2017-02-16 15:07:46.000,2023-03-24 23:52:00.000000,2020-01-07 20:53:25,838.0,,413.0,130.0,136.0,60.0,128.0,2402.0,Deep Learning toolkit for Computer Vision.,15.0,23,False,2018-11-09 21:35:17.000,0.2.3,10.0,luminoth,,,['tensorflow'],12871.0,3602.0,67.0,65.0,https://pypi.org/project/luminoth,2018-11-09 21:35:17.000,2.0,3447.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +592,SRU,asappresearch/sru,pytorch-utils,,https://github.com/asappresearch/sru,https://github.com/asappresearch/sru,MIT,2017-08-28 20:37:41.000,2022-01-04 21:17:53.000000,2021-05-19 15:52:48,400.0,,300.0,64.0,78.0,65.0,68.0,2103.0,Training RNNs as Fast as CNNs (https://arxiv.org/abs/1709.02755).,21.0,23,False,2021-05-18 16:13:10.000,2.6.0,32.0,sru,,,['pytorch'],,2034.0,33.0,30.0,https://pypi.org/project/sru,2021-06-17 23:33:37.000,3.0,2034.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +593,Torchmeta,tristandeleu/pytorch-meta,pytorch-utils,,https://github.com/tristandeleu/pytorch-meta,https://github.com/tristandeleu/pytorch-meta,MIT,2018-12-04 23:36:45.000,2023-07-17 16:05:00.000000,2021-09-20 16:03:46,382.0,,246.0,44.0,33.0,51.0,90.0,1965.0,A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch.,12.0,23,False,2021-09-20 16:06:33.000,1.8.0,28.0,torchmeta,,,['pytorch'],,3995.0,178.0,178.0,https://pypi.org/project/torchmeta,2021-09-20 16:06:33.000,,3995.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +594,Vulkan Kompute,KomputeProject/kompute,gpu-utilities,,https://github.com/KomputeProject/kompute,https://github.com/KomputeProject/kompute,Apache-2.0,2020-07-29 05:23:33.000,2024-09-05 10:37:12.000000,2024-09-05 10:37:12,1286.0,26.0,137.0,33.0,177.0,71.0,149.0,1938.0,"General purpose GPU compute framework built on Vulkan to support 1000s of cross vendor graphics cards (AMD, Qualcomm,..",27.0,23,True,2024-01-20 15:39:17.000,0.9.0,14.0,kp,,,,558.0,161.0,,,https://pypi.org/project/kp,2024-01-20 15:33:09.000,,150.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +595,Multicore-TSNE,DmitryUlyanov/Multicore-TSNE,data-viz,,https://github.com/DmitryUlyanov/Multicore-TSNE,https://github.com/DmitryUlyanov/Multicore-TSNE,BSD-3-Clause,2016-10-19 05:46:52.000,2024-02-06 10:59:55.000000,2024-02-06 10:59:47,125.0,,228.0,42.0,36.0,45.0,24.0,1876.0,Parallel t-SNE implementation with Python and Torch wrappers.,18.0,23,True,2017-11-08 13:32:20.000,0.0.1,3.0,MulticoreTSNE,conda-forge/multicore-tsne,,['pytorch'],,3048.0,484.0,462.0,https://pypi.org/project/MulticoreTSNE,2019-01-09 07:23:04.000,22.0,1876.0,https://anaconda.org/conda-forge/multicore-tsne,2023-10-11 19:12:48.654,48088.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +596,Mesh,tensorflow/mesh,distributed-ml,,https://github.com/tensorflow/mesh,https://github.com/tensorflow/mesh,Apache-2.0,2018-09-20 20:23:34.000,2023-11-17 19:39:54.000000,2023-11-17 19:39:45,658.0,,254.0,51.0,312.0,98.0,18.0,1581.0,Mesh TensorFlow: Model Parallelism Made Easier.,50.0,23,True,2022-05-15 21:06:13.000,0.1.21,27.0,mesh-tensorflow,,,['tensorflow'],,72029.0,3.0,,https://pypi.org/project/mesh-tensorflow,2022-05-15 21:06:13.000,3.0,72029.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +597,Pytorch Toolbelt,BloodAxe/pytorch-toolbelt,pytorch-utils,,https://github.com/BloodAxe/pytorch-toolbelt,https://github.com/BloodAxe/pytorch-toolbelt,MIT,2019-03-15 16:02:49.000,2024-09-01 10:23:29.000000,2024-09-01 10:27:11,1206.0,10.0,117.0,26.0,68.0,4.0,29.0,1513.0,PyTorch extensions for fast R&D prototyping and Kaggle farming.,7.0,23,True,2023-08-19 14:26:10.000,0.7.0,29.0,pytorch_toolbelt,,,['pytorch'],28.0,7311.0,7.0,,https://pypi.org/project/pytorch_toolbelt,2022-06-27 19:59:57.000,7.0,7311.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +598,sklearn-porter,nok/sklearn-porter,model-serialisation,,https://github.com/nok/sklearn-porter,https://github.com/nok/sklearn-porter,BSD-3-Clause,2016-06-22 22:21:34.000,2024-06-12 09:16:57.000000,2022-05-22 23:59:48,1219.0,,164.0,32.0,24.0,42.0,34.0,1282.0,"Transpile trained scikit-learn estimators to C, Java, JavaScript and others.",12.0,23,False,2019-12-18 13:39:19.000,0.7.4,20.0,sklearn-porter,,,['sklearn'],,873.0,64.0,64.0,https://pypi.org/project/sklearn-porter,2019-12-18 13:39:19.000,,873.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +599,PFRL,pfnet/pfrl,reinforcement-learning,,https://github.com/pfnet/pfrl,https://github.com/pfnet/pfrl,MIT,2020-06-24 09:31:50.000,2024-08-04 22:39:35.000000,2024-08-04 17:00:39,437.0,4.0,151.0,92.0,122.0,33.0,46.0,1176.0,PFRL: a PyTorch-based deep reinforcement learning library.,20.0,23,True,2023-07-16 15:34:00.704,0.4.0,6.0,pfrl,,,,,248.0,113.0,112.0,https://pypi.org/project/pfrl,2023-07-16 15:34:00.704,1.0,248.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +600,calamari,Calamari-OCR/calamari,ocr,,https://github.com/Calamari-OCR/calamari,https://github.com/Calamari-OCR/calamari,Apache-2.0,2018-03-20 15:22:29.000,2024-07-31 11:37:05.000000,2024-07-30 22:14:35,447.0,5.0,210.0,53.0,89.0,68.0,208.0,1035.0,Line based ATR Engine based on OCRopy.,20.0,23,True,2024-07-31 11:34:41.000,1.0.7,42.0,calamari_ocr,,,,,3816.0,8.0,,https://pypi.org/project/calamari_ocr,2024-07-31 11:34:41.000,8.0,3816.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +601,PyTorch Sparse,rusty1s/pytorch_sparse,pytorch-utils,,https://github.com/rusty1s/pytorch_sparse,https://github.com/rusty1s/pytorch_sparse,MIT,2018-07-28 18:46:53.000,2024-08-15 16:04:00.000000,2024-08-15 16:03:59,733.0,1.0,145.0,15.0,106.0,29.0,246.0,991.0,PyTorch Extension Library of Optimized Autograd Sparse Matrix Operations.,45.0,23,True,2023-10-06 08:51:55.000,0.6.18,31.0,torch-sparse,conda-forge/pytorch_sparse,,['pytorch'],,31103.0,122.0,,https://pypi.org/project/torch-sparse,2023-10-06 08:51:55.000,122.0,22777.0,https://anaconda.org/conda-forge/pytorch_sparse,2024-05-19 05:55:47.946,424647.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +602,Pandas-Bokeh,PatrikHlobil/Pandas-Bokeh,data-viz,,https://github.com/PatrikHlobil/Pandas-Bokeh,https://github.com/PatrikHlobil/Pandas-Bokeh,MIT,2018-11-23 20:49:14.000,2024-04-10 17:11:06.000000,2023-03-06 07:52:05,311.0,,110.0,26.0,36.0,34.0,69.0,879.0,Bokeh Plotting Backend for Pandas and GeoPandas.,15.0,23,False,2021-04-11 17:43:13.000,0.5.5,16.0,pandas-bokeh,,,['pandas'],,26172.0,665.0,653.0,https://pypi.org/project/pandas-bokeh,2021-04-11 17:43:13.000,12.0,26172.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +603,Guild AI,guildai/guildai,ml-experiments,,https://github.com/guildai/guildai,https://github.com/guildai/guildai,Apache-2.0,2017-09-27 18:57:50.000,2023-08-14 08:41:19.000000,2023-08-12 20:19:05,5777.0,,84.0,14.0,77.0,221.0,218.0,865.0,"Experiment tracking, ML developer tools.",29.0,23,False,2023-02-25 17:16:57.621,0.9.0,186.0,guildai,,,,20.0,1375.0,99.0,99.0,https://pypi.org/project/guildai,2022-05-11 01:13:31.000,,1375.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +604,python-ternary,marcharper/python-ternary,data-viz,,https://github.com/marcharper/python-ternary,https://github.com/marcharper/python-ternary,MIT,2012-08-07 23:48:55.000,2024-06-12 05:36:27.000000,2024-06-12 05:36:27,401.0,1.0,155.0,17.0,73.0,35.0,109.0,724.0,Ternary plotting library for python with matplotlib.,28.0,23,True,2021-02-17 18:38:15.000,1.0.8,11.0,python-ternary,conda-forge/python-ternary,,,30.0,16847.0,217.0,185.0,https://pypi.org/project/python-ternary,2021-02-17 18:38:15.000,32.0,15978.0,https://anaconda.org/conda-forge/python-ternary,2023-06-16 13:17:10.682,87787.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +605,vecstack,vecxoz/vecstack,others,,https://github.com/vecxoz/vecstack,https://github.com/vecxoz/vecstack,MIT,2016-11-08 13:23:21.000,2024-08-14 09:00:03.000000,2019-10-30 09:27:48,189.0,,80.0,21.0,12.0,,39.0,684.0,Python package for stacking (machine learning technique).,1.0,23,False,2019-08-12 16:09:01.000,0.4.0,6.0,vecstack,conda-forge/vecstack,,,,11387.0,502.0,497.0,https://pypi.org/project/vecstack,2019-08-12 16:01:22.000,5.0,11332.0,https://anaconda.org/conda-forge/vecstack,2023-06-16 19:26:00.374,2201.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +606,MONAILabel,Project-MONAI/MONAILabel,others,,https://github.com/Project-MONAI/MONAILabel,https://github.com/Project-MONAI/MONAILabel,Apache-2.0,2021-03-26 15:25:10.000,2024-09-05 05:07:45.000000,2024-09-05 05:07:45,985.0,7.0,189.0,24.0,855.0,130.0,394.0,586.0,MONAI Label is an intelligent open source image labeling and learning tool.,61.0,23,True,2024-07-23 17:48:05.000,0.8.3,114.0,monailabel-weekly,,,,92128.0,2947.0,,,https://pypi.org/project/monailabel-weekly,2023-10-01 02:24:07.000,,523.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +607,happy-transformer,EricFillion/happy-transformer,nlp,,https://github.com/EricFillion/happy-transformer,https://github.com/EricFillion/happy-transformer,Apache-2.0,2019-10-06 22:02:12.000,2024-08-01 23:26:59.000000,2024-03-19 15:52:03,1216.0,,66.0,7.0,211.0,20.0,109.0,516.0,Happy Transformer makes it easy to fine-tune and perform inference with NLP Transformer models.,14.0,23,True,2023-08-07 03:02:27.000,3.0.0,40.0,happytransformer,,,['huggingface'],,2272.0,281.0,276.0,https://pypi.org/project/happytransformer,2023-08-05 22:54:02.000,5.0,2272.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +608,chefboost,serengil/chefboost,ml-frameworks,,https://github.com/serengil/chefboost,https://github.com/serengil/chefboost,MIT,2019-03-06 12:26:27.000,2024-08-12 09:24:26.000000,2024-08-12 09:24:26,399.0,16.0,102.0,18.0,9.0,7.0,49.0,451.0,"A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4.5, CART, CHAID and Regression Trees; some..",7.0,23,True,2024-06-08 21:33:50.000,0.0.18,18.0,chefboost,,,,,3560.0,59.0,59.0,https://pypi.org/project/chefboost,2024-06-08 21:33:50.000,,3560.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +609,lightwood,mindsdb/lightwood,hyperopt,,https://github.com/mindsdb/lightwood,https://github.com/mindsdb/lightwood,GPL-3.0,2019-05-20 21:31:14.000,2024-09-04 00:22:36.000000,2024-05-15 12:32:23,5658.0,,92.0,17.0,764.0,16.0,446.0,437.0,Lightwood is Legos for Machine Learning.,46.0,23,False,2024-05-15 13:29:47.000,24.5.2.0,204.0,lightwood,,,['pytorch'],,5985.0,71.0,69.0,https://pypi.org/project/lightwood,2024-05-15 13:37:20.000,2.0,5985.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +610,pymap3d,geospace-code/pymap3d,geospatial-data,,https://github.com/geospace-code/pymap3d,https://github.com/geospace-code/pymap3d,BSD-2-Clause,2014-08-03 04:28:03.000,2024-05-07 21:17:52.000000,2024-02-11 00:53:13,766.0,,87.0,13.0,31.0,9.0,49.0,382.0,pure-Python (Numpy optional) 3D coordinate conversions for geospace ecef enu eci.,18.0,23,True,2024-02-11 00:59:05.000,3.1.0,58.0,pymap3d,conda-forge/pymap3d,,,,191254.0,476.0,432.0,https://pypi.org/project/pymap3d,2024-02-11 00:59:05.000,44.0,189590.0,https://anaconda.org/conda-forge/pymap3d,2024-02-11 07:50:28.337,79874.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +611,micrograd,karpathy/micrograd,pytorch-utils,,https://github.com/karpathy/micrograd,https://github.com/karpathy/micrograd,MIT,2020-04-13 04:31:18.000,2024-08-08 12:54:44.000000,2020-04-18 19:15:25,24.0,,1407.0,149.0,50.0,46.0,11.0,9929.0,A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API.,2.0,22,False,2020-04-18 19:06:59.000,0.1.0,1.0,micrograd,,,['pytorch'],,1008.0,64.0,61.0,https://pypi.org/project/micrograd,2020-04-18 19:06:59.000,3.0,1008.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +612,nebullvm,nebuly-ai/nebullvm,model-serialisation,,https://github.com/nebuly-ai/optimate,https://github.com/nebuly-ai/optimate,Apache-2.0,2022-02-12 17:17:14.000,2024-07-22 02:07:03.000000,2024-07-22 02:07:02,771.0,8.0,639.0,92.0,152.0,99.0,103.0,8369.0,A collection of libraries to optimise AI model performances.,40.0,22,True,2023-06-18 11:03:00.511,0.10.0,26.0,nebullvm,,,,,976.0,2.0,,https://pypi.org/project/nebullvm,2023-06-18 11:03:00.511,2.0,976.0,,,,3.0,,,,,,,,nebuly-ai/optimate,,,,,,,,,,,,,,,,, +613,cortex,cortexlabs/cortex,model-serialisation,,https://github.com/cortexlabs/cortex,https://github.com/cortexlabs/cortex,Apache-2.0,2019-01-24 04:43:14.000,2024-06-12 19:34:23.000000,2023-03-04 05:19:44,2327.0,,609.0,146.0,1362.0,129.0,987.0,8017.0,Production infrastructure for machine learning at scale.,25.0,22,False,2022-09-23 18:01:31.000,0.42.1,63.0,cortex,,,,,699.0,2.0,,https://pypi.org/project/cortex,2022-09-23 17:40:01.770,2.0,699.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +614,graph-nets,deepmind/graph_nets,graph,,https://github.com/google-deepmind/graph_nets,https://github.com/google-deepmind/graph_nets,Apache-2.0,2018-08-31 08:19:28.000,2022-12-12 11:28:07.000000,2022-12-12 11:28:07,48.0,,783.0,223.0,25.0,8.0,122.0,5342.0,Build Graph Nets in Tensorflow.,11.0,22,False,2020-01-29 16:00:25.000,1.1.0,7.0,graph-nets,,,['tensorflow'],,1338.0,22.0,20.0,https://pypi.org/project/graph-nets,2020-01-29 16:00:25.000,2.0,1338.0,,,,3.0,,,,,,,,google-deepmind/graph_nets,,,,,,,,,,,,,,,,, +615,MMLSpark,microsoft/SynapseML,distributed-ml,,https://github.com/microsoft/SynapseML,https://github.com/microsoft/SynapseML,MIT,2017-06-05 08:23:44.000,2024-08-31 18:49:56.000000,2024-08-30 02:03:46,1631.0,27.0,827.0,145.0,1552.0,367.0,401.0,5041.0,Simple and Distributed Machine Learning.,120.0,22,True,2024-08-30 02:16:51.000,1.0.5,51.0,mmlspark,,,['spark'],,1.0,,,https://pypi.org/project/mmlspark,2020-03-18 01:27:31.000,,1.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +616,deep-daze,lucidrains/deep-daze,image,,https://github.com/lucidrains/deep-daze,https://github.com/lucidrains/deep-daze,MIT,2021-01-17 06:00:50.000,2022-03-13 19:09:50.000000,2022-03-13 19:08:59,231.0,,322.0,75.0,37.0,95.0,75.0,4375.0,Simple command line tool for text to image generation using OpenAIs CLIP and Siren (Implicit neural representation..,14.0,22,False,2022-03-13 19:09:50.000,0.11.1,67.0,deep-daze,,,,,402.0,53.0,53.0,https://pypi.org/project/deep-daze,2022-03-13 19:09:50.000,,402.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +617,ReAgent,facebookresearch/ReAgent,reinforcement-learning,,https://github.com/facebookresearch/ReAgent,https://github.com/facebookresearch/ReAgent,BSD-3-Clause,2017-07-27 17:53:21.000,2024-08-12 15:50:03.000000,2024-08-12 15:45:58,1602.0,4.0,514.0,148.0,610.0,86.0,75.0,3555.0,"A platform for Reasoning systems (Reinforcement Learning, Contextual Bandits, etc.).",167.0,22,True,2020-01-27 22:06:00.000,0.0.0,2.0,reagent,,,['pytorch'],,41.0,,,https://pypi.org/project/reagent,2020-05-27 20:58:01.000,,41.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +618,finmarketpy,cuemacro/finmarketpy,financial-data,,https://github.com/cuemacro/finmarketpy,https://github.com/cuemacro/finmarketpy,Apache-2.0,2015-02-19 23:32:03.000,2024-05-19 22:21:30.000000,2024-05-19 22:15:20,687.0,,489.0,214.0,16.0,24.0,4.0,3415.0,Python library for backtesting trading strategies & analyzing financial markets (formerly pythalesians).,14.0,22,True,2024-05-19 22:21:30.000,0.11.14,15.0,finmarketpy,,,,54.0,287.0,14.0,14.0,https://pypi.org/project/finmarketpy,2024-05-19 22:21:30.000,,287.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +619,gpt-2-simple,minimaxir/gpt-2-simple,nlp,,https://github.com/minimaxir/gpt-2-simple,https://github.com/minimaxir/gpt-2-simple,MIT,2019-04-13 20:00:52.000,2022-12-14 11:50:45.000000,2022-05-22 02:02:04,149.0,,677.0,74.0,53.0,179.0,101.0,3401.0,Python package to easily retrain OpenAIs GPT-2 text-generating model on new texts.,21.0,22,False,2021-10-18 02:38:39.000,0.8.1,18.0,gpt-2-simple,,,['tensorflow'],599.0,1261.0,8.0,,https://pypi.org/project/gpt-2-simple,2021-10-18 01:47:20.000,8.0,1252.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +620,vissl,facebookresearch/vissl,image,,https://github.com/facebookresearch/vissl,https://github.com/facebookresearch/vissl,MIT,2020-04-09 19:40:33.000,2024-03-03 01:41:37.000000,2024-03-03 01:31:19,412.0,,328.0,53.0,414.0,82.0,106.0,3248.0,"VISSL is FAIRs library of extensible, modular and scalable components for SOTA Self-Supervised Learning with images.",38.0,22,True,2021-11-02 17:21:02.000,0.1.6,6.0,vissl,,,['pytorch'],,148.0,49.0,48.0,https://pypi.org/project/vissl,2021-11-02 15:36:07.000,1.0,148.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +621,TRFL,deepmind/trfl,reinforcement-learning,,https://github.com/google-deepmind/trfl,https://github.com/google-deepmind/trfl,Apache-2.0,2018-08-08 14:44:11.000,2022-12-08 18:07:05.000000,2021-08-16 11:45:18,123.0,,386.0,205.0,9.0,4.0,16.0,3136.0,TensorFlow Reinforcement Learning.,13.0,22,False,2021-08-16 12:19:16.000,1.2.0,5.0,trfl,,,['tensorflow'],,1673.0,160.0,158.0,https://pypi.org/project/trfl,2021-08-16 12:19:16.000,2.0,1673.0,,,,3.0,,,,,,,,google-deepmind/trfl,,,,,,,,,,,,,,,,, +622,opyrator,ml-tooling/opyrator,others,,https://github.com/ml-tooling/opyrator,https://github.com/ml-tooling/opyrator,MIT,2021-04-06 08:09:06.000,2024-09-02 02:30:42.000000,2021-05-06 12:10:38,127.0,,155.0,48.0,70.0,2.0,30.0,3055.0,"Turns your machine learning code into microservices with web API, interactive GUI, and more.",4.0,22,False,2021-05-04 18:48:03.000,0.0.12,11.0,opyrator,conda-forge/opyrator,,,,521.0,53.0,53.0,https://pypi.org/project/opyrator,2021-05-04 18:48:03.000,,468.0,https://anaconda.org/conda-forge/opyrator,2023-06-18 08:40:31.958,1717.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +623,NLP Architect,IntelLabs/nlp-architect,nlp,,https://github.com/IntelLabs/nlp-architect,https://github.com/IntelLabs/nlp-architect,Apache-2.0,2018-05-17 21:00:13.000,2022-11-07 16:21:47.000000,2022-11-07 16:21:47,957.0,,454.0,165.0,120.0,22.0,112.0,2936.0,A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language..,38.0,22,False,2020-11-17 12:32:37.000,0.5.5.1,13.0,nlp-architect,,,,,283.0,10.0,10.0,https://pypi.org/project/nlp-architect,2020-04-12 11:34:38.000,,283.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +624,Texthero,jbesomi/texthero,nlp,,https://github.com/jbesomi/texthero,https://github.com/jbesomi/texthero,MIT,2020-04-06 15:16:05.000,2023-08-29 08:45:13.000000,2023-08-29 08:45:10,277.0,,239.0,42.0,110.0,80.0,64.0,2882.0,"Text preprocessing, representation and visualization from zero to hero.",21.0,22,False,2021-07-01 17:11:02.000,1.1.0,10.0,texthero,,,,141.0,3513.0,6.0,,https://pypi.org/project/texthero,2021-07-01 17:11:02.000,6.0,3511.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +625,analytics-zoo,intel-analytics/analytics-zoo,distributed-ml,,https://github.com/intel-analytics/analytics-zoo,https://github.com/intel-analytics/analytics-zoo,Apache-2.0,2024-03-05 03:41:26.000,2024-08-05 15:27:11.000000,2024-08-05 15:27:03,3460.0,3.0,727.0,7.0,30.0,406.0,855.0,2606.0,"Distributed Tensorflow, Keras and PyTorch on Apache Spark/Flink & Ray.",108.0,22,True,2024-03-05 10:02:36.000,0.1.0,418.0,analytics-zoo,,,['spark'],,576.0,1.0,,https://pypi.org/project/analytics-zoo,2022-08-22 20:19:01.213,1.0,576.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +626,Texar,asyml/texar,nlp,,https://github.com/asyml/texar,https://github.com/asyml/texar,Apache-2.0,2017-07-22 19:02:05.000,2021-08-26 09:49:50.000000,2020-07-29 00:38:30,1719.0,,381.0,77.0,144.0,36.0,126.0,2385.0,"Toolkit for Machine Learning, Natural Language Processing, and Text Generation, in TensorFlow. This is part of the..",43.0,22,False,2019-11-19 04:11:18.000,0.2.4,6.0,texar,,,['tensorflow'],,68.0,30.0,28.0,https://pypi.org/project/texar,2019-11-19 04:11:18.000,2.0,68.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +627,fast-bert,utterworks/fast-bert,nlp,,https://github.com/utterworks/fast-bert,https://github.com/utterworks/fast-bert,Apache-2.0,2019-04-18 22:01:20.000,2024-08-19 09:45:05.000000,2024-08-19 09:41:36,346.0,1.0,341.0,42.0,68.0,163.0,95.0,1855.0,Super easy library for BERT based NLP models.,37.0,22,True,2024-08-19 09:45:05.000,2.0.26,72.0,fast-bert,,,,,1389.0,,,https://pypi.org/project/fast-bert,2024-08-19 09:45:05.000,,1389.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +628,hiddenlayer,waleedka/hiddenlayer,ml-experiments,,https://github.com/waleedka/hiddenlayer,https://github.com/waleedka/hiddenlayer,MIT,2018-05-18 22:34:51.000,2024-02-11 12:41:49.000000,2020-04-24 06:58:09,58.0,,255.0,44.0,14.0,57.0,35.0,1788.0,"Neural network graphs and training metrics for PyTorch, Tensorflow, and Keras.",6.0,22,False,2018-12-03 04:33:29.000,0.2,3.0,hiddenlayer,,,"['pytorch', 'tensorflow', 'jupyter']",,2587.0,308.0,297.0,https://pypi.org/project/hiddenlayer,2020-04-24 07:32:11.000,11.0,2587.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +629,sklearn-contrib-lightning,scikit-learn-contrib/lightning,sklearn-utils,,https://github.com/scikit-learn-contrib/lightning,https://github.com/scikit-learn-contrib/lightning,BSD-3-Clause,2012-01-11 13:53:52.000,2023-07-18 11:41:11.000000,2022-01-30 01:22:30,743.0,,213.0,38.0,111.0,56.0,42.0,1719.0,"Large-scale linear classification, regression and ranking in Python.",17.0,22,False,2022-01-30 01:10:13.000,0.6.2.post0,12.0,sklearn-contrib-lightning,conda-forge/sklearn-contrib-lightning,,['sklearn'],611.0,4458.0,168.0,162.0,https://pypi.org/project/sklearn-contrib-lightning,2022-01-30 00:43:43.000,6.0,2106.0,https://anaconda.org/conda-forge/sklearn-contrib-lightning,2023-06-16 13:18:02.734,229087.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +630,auto_ml,ClimbsRocks/auto_ml,hyperopt,,https://github.com/ClimbsRocks/auto_ml,https://github.com/ClimbsRocks/auto_ml,MIT,2016-08-07 21:35:08.000,2021-02-10 07:52:35.000000,2018-03-25 19:46:25,1149.0,,311.0,97.0,45.0,187.0,217.0,1641.0,[UNMAINTAINED] Automated machine learning for analytics & production.,14.0,22,False,2018-02-22 01:13:03.000,2.9.10,78.0,auto_ml,,,,59.0,1087.0,9.0,,https://pypi.org/project/auto_ml,2018-02-22 01:13:03.000,9.0,1087.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +631,jiant,nyu-mll/jiant,nlp,,https://github.com/nyu-mll/jiant,https://github.com/nyu-mll/jiant,MIT,2018-06-18 18:12:47.000,2023-07-06 22:00:38.000000,2022-10-17 19:34:56,1930.0,,294.0,44.0,801.0,72.0,485.0,1635.0,jiant is an nlp toolkit.,60.0,22,False,2021-05-10 18:56:39.000,2.2.0,19.0,jiant,,,,,99.0,5.0,5.0,https://pypi.org/project/jiant,2021-05-10 18:56:39.000,,99.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +632,Classy Vision,facebookresearch/ClassyVision,image,,https://github.com/facebookresearch/ClassyVision,https://github.com/facebookresearch/ClassyVision,MIT,2019-09-13 22:54:44.000,2024-06-27 16:05:09.000000,2023-03-23 14:35:34,422.0,,278.0,70.0,730.0,51.0,64.0,1588.0,An end-to-end PyTorch framework for image and video classification.,77.0,22,False,2023-03-21 05:24:19.000,0.7.0,18.0,classy_vision,conda-forge/classy_vision,,['pytorch'],,1211.0,4.0,,https://pypi.org/project/classy_vision,2023-03-21 05:15:00.935,4.0,782.0,https://anaconda.org/conda-forge/classy_vision,2023-06-16 19:17:34.578,24045.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +633,FinQuant,fmilthaler/FinQuant,financial-data,,https://github.com/fmilthaler/FinQuant,https://github.com/fmilthaler/FinQuant,MIT,2019-01-20 15:07:19.000,2023-11-04 08:38:31.000000,2023-09-03 19:16:54,508.0,,183.0,32.0,86.0,16.0,33.0,1377.0,"A program for financial portfolio management, analysis and optimisation.",11.0,22,True,2023-09-04 06:57:56.000,0.7.0,15.0,FinQuant,,,,,377.0,94.0,93.0,https://pypi.org/project/FinQuant,2023-09-04 06:57:56.000,1.0,377.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +634,jraph,deepmind/jraph,graph,,https://github.com/google-deepmind/jraph,https://github.com/google-deepmind/jraph,Apache-2.0,2020-11-23 10:27:12.000,2024-03-18 13:56:39.000000,2022-08-31 13:13:15,103.0,,88.0,40.0,15.0,11.0,27.0,1353.0,A Graph Neural Network Library in Jax.,17.0,22,False,2022-08-12 15:24:20.000,0.0.6.de0,5.0,jraph,conda-forge/jraph,,['jax'],,11306.0,235.0,213.0,https://pypi.org/project/jraph,2022-08-12 15:25:29.659,22.0,11136.0,https://anaconda.org/conda-forge/jraph,2023-06-16 19:27:46.249,5982.0,3.0,,,,,,,,google-deepmind/jraph,,,,,,,,,,,,,,,,, +635,pytorch_tabular,manujosephv/pytorch_tabular,tabular,,https://github.com/manujosephv/pytorch_tabular,https://github.com/manujosephv/pytorch_tabular,MIT,2020-12-15 07:17:03.000,2024-09-02 23:23:31.000000,2024-06-07 09:12:27,550.0,,133.0,21.0,295.0,21.0,138.0,1313.0,A standard framework for modelling Deep Learning Models for tabular data.,22.0,22,True,2024-01-15 12:17:19.000,1.1.0,12.0,pytorch_tabular,,,['pytorch'],35.0,2981.0,3.0,,https://pypi.org/project/pytorch_tabular,2024-01-15 02:46:25.000,3.0,2981.0,,,,2.0,,,,,,,,,,,,,,,,,,,,,,,,, +636,advertorch,BorealisAI/advertorch,adversarial,,https://github.com/BorealisAI/advertorch,https://github.com/BorealisAI/advertorch,GPL-3.0,2018-11-29 22:17:33.000,2023-09-14 02:51:02.000000,2022-05-29 19:09:18,309.0,,189.0,27.0,57.0,22.0,36.0,1288.0,A Toolbox for Adversarial Robustness Research.,21.0,22,False,2020-06-15 01:20:07.000,0.2.3,10.0,advertorch,,,['pytorch'],,546.0,179.0,174.0,https://pypi.org/project/advertorch,2020-06-15 01:20:07.000,5.0,546.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +637,NGT,yahoojapan/NGT,nn-search,,https://github.com/yahoojapan/NGT,https://github.com/yahoojapan/NGT,Apache-2.0,2016-09-01 07:36:57.000,2024-07-26 00:37:30.000000,2024-07-26 00:21:42,195.0,6.0,113.0,38.0,30.0,17.0,118.0,1235.0,Nearest Neighbor Search with Neighborhood Graph and Tree for High-dimensional Data.,15.0,22,True,2024-07-26 00:44:37.000,2.2.4,84.0,ngt,,,,,2893.0,8.0,,https://pypi.org/project/ngt,2023-12-06 05:33:15.000,8.0,2893.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +638,luminol,linkedin/luminol,time-series-data,,https://github.com/linkedin/luminol,https://github.com/linkedin/luminol,Apache-2.0,2015-11-18 23:16:33.000,2023-05-09 00:52:44.000000,2023-05-09 00:52:44,72.0,,213.0,65.0,29.0,31.0,12.0,1178.0,Anomaly Detection and Correlation library.,9.0,22,False,2016-01-20 01:01:44.000,0.3.1,5.0,luminol,,,,,11718.0,81.0,79.0,https://pypi.org/project/luminol,2017-12-11 06:04:15.000,2.0,11718.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +639,AstroML,astroML/astroML,others,,https://github.com/astroML/astroML,https://github.com/astroML/astroML,BSD-2-Clause,2012-10-17 22:33:50.000,2024-05-25 09:25:40.000000,2024-01-04 20:41:21,582.0,,293.0,96.0,123.0,62.0,97.0,1044.0,"Machine learning, statistics, and data mining for astronomy and astrophysics.",31.0,22,True,2022-01-25 21:56:31.000,1.0.2,13.0,astroML,conda-forge/astroml,,['sklearn'],,2119.0,16.0,,https://pypi.org/project/astroML,2022-03-01 20:02:01.000,16.0,1569.0,https://anaconda.org/conda-forge/astroml,2023-06-16 13:21:24.079,46800.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +640,tf-explain,sicara/tf-explain,interpretability,,https://github.com/sicara/tf-explain,https://github.com/sicara/tf-explain,MIT,2019-07-15 08:26:24.000,2024-06-03 10:38:45.000000,2022-06-30 08:14:18,208.0,,112.0,52.0,99.0,44.0,51.0,1016.0,Interpretability Methods for tf.keras models with Tensorflow 2.x.,18.0,22,False,2021-11-18 20:57:29.000,0.3.1,8.0,tf-explain,,,['tensorflow'],,2875.0,255.0,244.0,https://pypi.org/project/tf-explain,2021-11-18 20:57:29.000,11.0,2875.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +641,nnAudio,KinWaiCheuk/nnAudio,audio,,https://github.com/KinWaiCheuk/nnAudio,https://github.com/KinWaiCheuk/nnAudio,MIT,2019-09-02 04:31:14.000,2024-02-13 05:58:29.000000,2024-02-13 05:55:37,305.0,,89.0,18.0,73.0,18.0,45.0,1004.0,Audio processing by using pytorch 1D convolution network.,15.0,22,True,2024-02-13 05:58:29.000,0.3.3,40.0,nnAudio,,,,,12510.0,207.0,203.0,https://pypi.org/project/nnAudio,2024-02-13 05:58:29.000,4.0,12510.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +642,YouTokenToMe,vkcom/youtokentome,nlp,,https://github.com/VKCOM/YouTokenToMe,https://github.com/VKCOM/YouTokenToMe,MIT,2019-06-06 11:38:28.000,2024-03-29 10:21:35.000000,2023-03-29 07:39:45,85.0,,87.0,26.0,55.0,36.0,28.0,952.0,Unsupervised text tokenizer focused on computational efficiency.,8.0,22,False,2020-02-13 09:57:47.000,1.0.6,14.0,youtokentome,conda-forge/youtokentome,,,,46937.0,756.0,733.0,https://pypi.org/project/youtokentome,2020-02-12 18:24:46.000,23.0,45218.0,https://anaconda.org/conda-forge/youtokentome,2023-09-27 19:23:04.851,61901.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +643,Saliency,PAIR-code/saliency,tensorflow-utils,,https://github.com/PAIR-code/saliency,https://github.com/PAIR-code/saliency,Apache-2.0,2017-06-09 22:07:35.000,2024-03-20 19:51:28.000000,2024-03-20 19:28:51,85.0,,190.0,24.0,58.0,12.0,27.0,950.0,"Framework-agnostic implementation for state-of-the-art saliency methods (XRAI, BlurIG, SmoothGrad, and more).",18.0,22,True,2024-03-20 19:51:28.000,0.2.1,12.0,saliency,,,['tensorflow'],,42067.0,108.0,100.0,https://pypi.org/project/saliency,2024-03-20 19:51:28.000,8.0,42067.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +644,detoxify,unitaryai/detoxify,nlp,,https://github.com/unitaryai/detoxify,https://github.com/unitaryai/detoxify,Apache-2.0,2020-09-23 15:24:21.000,2024-08-17 17:13:45.000000,2024-08-17 13:50:12,251.0,2.0,115.0,15.0,48.0,38.0,29.0,920.0,Trained models & code to predict toxic comments on all 3 Jigsaw Toxic Comment Challenges. Built using Pytorch..,12.0,22,True,2024-02-01 14:51:21.000,0.5.2,13.0,detoxify,,,,641342.0,41309.0,704.0,674.0,https://pypi.org/project/detoxify,2024-02-01 14:51:21.000,30.0,27367.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +645,kapre,keunwoochoi/kapre,audio,,https://github.com/keunwoochoi/kapre,https://github.com/keunwoochoi/kapre,MIT,2016-12-14 18:36:36.000,2023-10-23 02:52:41.000000,2022-07-04 00:10:02,195.0,,146.0,23.0,46.0,16.0,82.0,919.0,kapre: Keras Audio Preprocessors.,13.0,22,False,2022-01-21 20:10:47.000,Kapre-0.3.7,24.0,kapre,,,['tensorflow'],28.0,1725.0,2442.0,2433.0,https://pypi.org/project/kapre,2022-01-21 20:09:21.000,9.0,1725.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +646,What-If Tool,PAIR-code/what-if-tool,interpretability,,https://github.com/PAIR-code/what-if-tool,https://github.com/PAIR-code/what-if-tool,Apache-2.0,2018-09-07 20:26:10.000,2024-03-14 21:28:06.000000,2024-02-01 21:38:56,330.0,,167.0,29.0,111.0,88.0,56.0,903.0,Source code/webpage/demos for the What-If Tool.,20.0,22,True,2021-10-12 17:42:50.869,1.8.1,40.0,witwidget,conda-forge/tensorboard-plugin-wit,,,,50783.0,11.0,2.0,https://pypi.org/project/witwidget,2021-10-12 17:42:30.000,6.0,5585.0,https://anaconda.org/conda-forge/tensorboard-plugin-wit,2023-06-16 19:20:28.498,2268354.0,3.0,,,,,,,,,wit-widget,https://www.npmjs.com/package/wit-widget,2021-10-12 17:42:50.869,3.0,721.0,,,,,,,,,,,, +647,mlens,flennerhag/mlens,others,,https://github.com/flennerhag/mlens,https://github.com/flennerhag/mlens,MIT,2017-01-10 20:53:47.000,2023-11-13 16:09:34.000000,2020-02-25 14:31:53,879.0,,107.0,28.0,60.0,27.0,74.0,844.0,ML-Ensemble high performance ensemble learning.,7.0,22,False,2018-10-30 22:34:35.000,0.2.3,14.0,mlens,,,,,1839.0,477.0,476.0,https://pypi.org/project/mlens,2018-10-30 22:30:43.000,1.0,1839.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +648,icevision,airctic/icevision,image,,https://github.com/airctic/icevision,https://github.com/airctic/icevision,Apache-2.0,2020-05-04 01:57:02.000,2023-10-07 18:05:54.000000,2022-12-07 13:45:45,1234.0,,133.0,24.0,594.0,63.0,511.0,843.0,"An Agnostic Computer Vision Framework - Pluggable to any Training Library: Fastai, Pytorch-Lightning with more to come.",41.0,22,False,2022-02-10 15:55:46.374,0.12.0,41.0,icevision,,,,,2629.0,6.0,,https://pypi.org/project/icevision,2022-02-10 15:55:46.374,6.0,2629.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +649,torch-cluster,rusty1s/pytorch_cluster,graph,,https://github.com/rusty1s/pytorch_cluster,https://github.com/rusty1s/pytorch_cluster,MIT,2018-01-12 20:56:06.000,2024-08-28 13:26:28.147000,2024-08-15 11:12:26,601.0,1.0,142.0,15.0,63.0,37.0,134.0,803.0,PyTorch Extension Library of Optimized Graph Cluster Algorithms.,34.0,22,True,2023-10-12 06:54:28.000,1.6.3,43.0,torch-cluster,conda-forge/pytorch_cluster,,['pytorch'],,16808.0,62.0,,https://pypi.org/project/torch-cluster,2023-10-12 06:52:43.000,62.0,13326.0,https://anaconda.org/conda-forge/pytorch_cluster,2024-08-28 13:26:28.147,181070.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +650,gmaps,pbugnion/gmaps,geospatial-data,,https://github.com/pbugnion/gmaps,https://github.com/pbugnion/gmaps,BSD-3-Clause,2014-12-01 09:12:06.000,2023-06-16 13:23:14.332000,2019-07-22 06:22:45,1380.0,,147.0,25.0,154.0,79.0,137.0,760.0,Google maps for Jupyter notebooks.,16.0,22,False,2019-07-21 08:49:48.715,0.9.0,96.0,gmaps,conda-forge/gmaps,,['jupyter'],,10271.0,18.0,,https://pypi.org/project/gmaps,2021-12-15 15:42:57.506,13.0,5957.0,https://anaconda.org/conda-forge/gmaps,2023-06-16 13:23:14.332,334866.0,3.0,,,,,,,,,jupyter-gmaps,https://www.npmjs.com/package/jupyter-gmaps,2019-07-21 08:49:48.715,5.0,509.0,,,,,,,,,,,, +651,finetune,IndicoDataSolutions/finetune,nlp,,https://github.com/IndicoDataSolutions/finetune,https://github.com/IndicoDataSolutions/finetune,MPL-2.0,2018-06-12 17:02:16.000,2024-08-25 07:39:58.000000,2024-07-23 12:43:38,1508.0,3.0,80.0,34.0,674.0,22.0,118.0,700.0,Scikit-learn style model finetuning for NLP.,23.0,22,True,2023-09-29 10:19:51.000,0.10.0,39.0,finetune,,,"['tensorflow', 'sklearn']",,267.0,14.0,12.0,https://pypi.org/project/finetune,2023-09-29 10:19:51.000,2.0,267.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +652,pivottablejs,nicolaskruchten/jupyter_pivottablejs,data-viz,,https://github.com/nicolaskruchten/jupyter_pivottablejs,https://github.com/nicolaskruchten/jupyter_pivottablejs,MIT,2015-09-09 13:39:18.000,2024-03-15 12:50:01.000000,2018-12-04 14:43:25,32.0,,88.0,21.0,9.0,25.0,41.0,683.0,"Dragndrop Pivot Tables and Charts for Jupyter/IPython Notebook, care of PivotTable.js.",3.0,22,False,2018-01-15 18:14:37.000,0.9.0,10.0,pivottablejs,anaconda/pivottablejs,,['jupyter'],,32836.0,475.0,465.0,https://pypi.org/project/pivottablejs,2018-01-15 18:14:37.000,10.0,32808.0,https://anaconda.org/anaconda/pivottablejs,2023-12-06 04:45:55.894,2985.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +653,HpBandSter,automl/HpBandSter,hyperopt,,https://github.com/automl/HpBandSter,https://github.com/automl/HpBandSter,BSD-3-Clause,2017-12-17 20:28:20.000,2023-06-16 19:24:00.330000,2022-04-22 06:33:31,188.0,,111.0,26.0,23.0,66.0,35.0,609.0,a distributed Hyperband implementation on Steroids.,11.0,22,False,2019-07-30 12:47:43.000,1.0,8.0,hpbandster,conda-forge/hpbandster,,,,8886.0,488.0,463.0,https://pypi.org/project/hpbandster,2018-11-06 12:56:55.000,25.0,8455.0,https://anaconda.org/conda-forge/hpbandster,2023-06-16 19:24:00.330,19431.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +654,random-forest-importances,parrt/random-forest-importances,interpretability,,https://github.com/parrt/random-forest-importances,https://github.com/parrt/random-forest-importances,MIT,2018-03-22 19:20:13.000,2023-11-18 04:12:38.000000,2021-01-30 21:50:02,249.0,,130.0,22.0,19.0,8.0,30.0,596.0,Code to compute permutation and drop-column importances in Python scikit-learn models.,14.0,22,False,2021-01-28 23:23:17.000,1.3.7,22.0,rfpimp,,,['sklearn'],,10274.0,171.0,166.0,https://pypi.org/project/rfpimp,2021-01-28 23:19:33.000,5.0,10274.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +655,Poutyne,GRAAL-Research/poutyne,pytorch-utils,,https://github.com/GRAAL-Research/poutyne,https://github.com/GRAAL-Research/poutyne,LGPL-3.0,2017-12-07 18:30:17.000,2024-07-08 19:15:42.000000,2024-07-08 19:11:02,771.0,4.0,63.0,17.0,114.0,8.0,48.0,570.0,A simplified framework and utilities for PyTorch.,21.0,22,False,2024-07-08 19:12:54.000,1.17.2,38.0,poutyne,,,['pytorch'],,3101.0,147.0,142.0,https://pypi.org/project/poutyne,2024-07-08 19:15:42.000,5.0,3101.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +656,small-text,webis-de/small-text,nlp,,https://github.com/webis-de/small-text,https://github.com/webis-de/small-text,MIT,2021-05-24 08:06:41.000,2024-08-18 16:37:29.577000,2024-08-18 15:52:42,512.0,28.0,60.0,25.0,10.0,13.0,44.0,545.0,Active Learning for Text Classification in Python.,7.0,22,True,2024-08-18 16:02:51.000,1.4.1,22.0,small-text,conda-forge/small-text,,"['sklearn', 'pytorch']",,1043.0,30.0,30.0,https://pypi.org/project/small-text,2024-08-18 16:00:34.000,,707.0,https://anaconda.org/conda-forge/small-text,2024-08-18 16:37:29.577,8742.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +657,Auto ViML,AutoViML/Auto_ViML,hyperopt,,https://github.com/AutoViML/Auto_ViML,https://github.com/AutoViML/Auto_ViML,Apache-2.0,2019-06-10 13:09:15.000,2024-07-09 19:44:12.000000,2024-05-11 10:43:02,331.0,,99.0,26.0,8.0,1.0,33.0,518.0,Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome...,9.0,22,True,2024-05-11 10:46:51.000,0.1.800,146.0,autoviml,,,,,2941.0,29.0,26.0,https://pypi.org/project/autoviml,2024-05-11 10:46:51.000,3.0,2941.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +658,tick,X-DataInitiative/tick,time-series-data,,https://github.com/X-DataInitiative/tick,https://github.com/X-DataInitiative/tick,BSD-3-Clause,2016-12-01 10:59:08.000,2024-08-18 17:30:50.000000,2023-03-05 00:16:57,419.0,,102.0,36.0,276.0,71.0,173.0,484.0,"Module for statistical learning, with a particular emphasis on time-dependent modelling.",20.0,22,False,2019-09-11 11:25:15.000,0.6,23.0,tick,,,,362.0,1257.0,83.0,81.0,https://pypi.org/project/tick,2020-05-24 22:01:17.000,2.0,1253.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +659,pydlm,wwrechard/pydlm,time-series-data,,https://github.com/wwrechard/pydlm,https://github.com/wwrechard/pydlm,BSD-3-Clause,2016-06-29 07:58:53.000,2024-08-30 06:50:55.000000,2024-08-30 06:50:52,386.0,14.0,98.0,28.0,33.0,41.0,15.0,475.0,A python library for Bayesian time series modeling.,7.0,22,True,2024-08-13 04:20:08.000,0.1.1.13,15.0,pydlm,,,,,23138.0,38.0,36.0,https://pypi.org/project/pydlm,2024-08-13 04:20:45.000,2.0,23138.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +660,Studio.ml,studioml/studio,ml-experiments,,https://github.com/studioml/studio,https://github.com/studioml/studio,Apache-2.0,2017-05-15 01:49:28.000,2024-07-06 00:47:45.000000,2023-09-06 17:29:29,2412.0,,52.0,23.0,232.0,57.0,195.0,379.0,Studio: Simplify and expedite model building process.,24.0,22,True,2021-09-14 22:55:51.000,0.0.49,208.0,studioml,,,,,719.0,6.0,6.0,https://pypi.org/project/studioml,2021-09-14 22:55:51.000,,719.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +661,vega,vega/ipyvega,data-viz,,https://github.com/vega/ipyvega,https://github.com/vega/ipyvega,BSD-3-Clause,2015-08-04 03:22:47.000,2024-09-01 02:29:03.000000,2024-09-01 02:27:39,668.0,8.0,65.0,30.0,481.0,21.0,91.0,372.0,IPython/Jupyter notebook module for Vega and Vega-Lite.,15.0,22,True,2023-07-18 13:09:18.000,4.0.0,40.0,vega,conda-forge/vega,,['jupyter'],,23323.0,19.0,4.0,https://pypi.org/project/vega,2023-04-12 02:09:01.110,15.0,11059.0,https://anaconda.org/conda-forge/vega,2024-05-18 03:50:45.535,637728.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +662,TimeSide,Parisson/TimeSide,audio,,https://github.com/Parisson/TimeSide,https://github.com/Parisson/TimeSide,AGPL-3.0,2011-11-21 21:48:08.000,2024-08-19 11:40:22.000000,2023-02-01 10:38:52,3728.0,,60.0,28.0,110.0,33.0,184.0,368.0,scalable audio processing framework and server written in Python.,22.0,22,False,2023-01-03 17:34:09.000,1.1.3,28.0,TimeSide,,,,,158.0,18.0,18.0,https://pypi.org/project/TimeSide,2020-11-27 09:33:19.000,,158.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +663,Orion,Epistimio/orion,hyperopt,,https://github.com/Epistimio/orion,https://github.com/Epistimio/orion,BSD-3-Clause,2017-09-07 06:05:21.000,2023-12-11 19:25:59.000000,2023-11-17 21:43:05,4051.0,,49.0,14.0,712.0,217.0,204.0,282.0,Asynchronous Distributed Hyperparameter Optimization.,32.0,22,False,2023-03-02 22:26:01.035,0.2.7,26.0,orion,,,,,613.0,116.0,108.0,https://pypi.org/project/orion,2022-08-22 17:10:40.826,8.0,613.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +664,py3nvml,fbcotter/py3nvml,gpu-utilities,,https://github.com/fbcotter/py3nvml,https://github.com/fbcotter/py3nvml,BSD-3-Clause,2016-11-21 01:07:37.000,2023-09-25 06:14:21.168000,2022-04-14 09:41:50,86.0,,33.0,12.0,9.0,4.0,12.0,236.0,Python 3 Bindings for NVML library. Get NVIDIA GPU status inside your program.,9.0,22,False,2021-11-22 14:30:25.000,0.2.7,14.0,py3nvml,conda-forge/py3nvml,,,,154248.0,1231.0,1174.0,https://pypi.org/project/py3nvml,2021-11-22 14:30:25.000,57.0,152617.0,https://anaconda.org/conda-forge/py3nvml,2023-09-25 06:14:21.168,76677.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +665,stop-words,Alir3z4/python-stop-words,nlp,,https://github.com/Alir3z4/python-stop-words,https://github.com/Alir3z4/python-stop-words,BSD-3-Clause,2014-05-26 06:44:03.000,2024-03-12 10:32:40.000000,2018-07-23 21:04:09,90.0,,28.0,7.0,20.0,5.0,9.0,155.0,Get list of common stop words in various languages in Python.,8.0,22,False,2018-07-23 20:58:34.000,2018.7.23,8.0,stop-words,,,,,103107.0,2377.0,2333.0,https://pypi.org/project/stop-words,2018-07-23 20:55:55.000,44.0,103107.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +666,PySlowFast,facebookresearch/SlowFast,image,,https://github.com/facebookresearch/SlowFast,https://github.com/facebookresearch/SlowFast,Apache-2.0,2019-08-20 22:47:26.000,2024-08-13 19:13:05.000000,2024-08-13 19:09:33,193.0,2.0,1190.0,93.0,49.0,395.0,286.0,6480.0,PySlowFast: video understanding codebase from FAIR for reproducing state-of-the-art video models.,33.0,21,True,,,1.0,pyslowfast,,,['pytorch'],,49.0,17.0,17.0,https://pypi.org/project/pyslowfast,2020-01-15 23:51:07.000,,49.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +667,mace,XiaoMi/mace,ml-frameworks,,https://github.com/XiaoMi/mace,https://github.com/XiaoMi/mace,Apache-2.0,2018-06-27 03:50:12.000,2024-06-17 09:17:33.000000,2024-03-11 13:23:01,3347.0,,820.0,229.0,111.0,57.0,622.0,4907.0,MACE is a deep learning inference framework optimized for mobile heterogeneous computing platforms.,69.0,21,True,2022-01-13 09:55:14.000,1.1.1,12.0,,,,,1524.0,20.0,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +668,Image Super-Resolution,idealo/image-super-resolution,image,,https://github.com/idealo/image-super-resolution,https://github.com/idealo/image-super-resolution,Apache-2.0,2018-11-26 13:41:13.000,2024-03-12 11:21:52.000000,2021-06-02 09:45:13,150.0,,742.0,102.0,35.0,107.0,113.0,4599.0,Super-scale your images and run experiments with Residual Dense and Adversarial Networks.,10.0,21,False,2020-01-08 15:37:35.000,2.2.0,11.0,ISR,,,['tensorflow'],,4594.0,5.0,,https://pypi.org/project/ISR,2020-01-08 15:37:35.000,5.0,4591.0,,,,3.0,idealo/image-super-resolution-gpu,https://hub.docker.com/r/idealo/image-super-resolution-gpu,2019-04-01 13:48:45.697251,1.0,238.0,,,,,,,,,,,,,,,,,,,, +669,tf-quant-finance,google/tf-quant-finance,financial-data,,https://github.com/google/tf-quant-finance,https://github.com/google/tf-quant-finance,Apache-2.0,2019-07-24 16:09:50.000,2024-05-20 22:36:46.000000,2023-08-15 07:38:22,956.0,,567.0,166.0,47.0,35.0,28.0,4445.0,High-performance TensorFlow library for quantitative finance.,47.0,21,False,,,30.0,tf-quant-finance,,,['tensorflow'],,464.0,3.0,,https://pypi.org/project/tf-quant-finance,2022-08-19 12:40:54.257,3.0,464.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +670,AdaBound,Luolc/AdaBound,pytorch-utils,,https://github.com/Luolc/AdaBound,https://github.com/Luolc/AdaBound,Apache-2.0,2019-02-15 18:05:20.000,2023-07-23 10:44:20.000000,2019-03-06 17:01:45,27.0,,330.0,72.0,2.0,20.0,7.0,2904.0,An optimizer that trains as fast as Adam and as good as SGD.,2.0,21,False,2019-03-06 16:44:42.000,0.0.5,4.0,adabound,,,['pytorch'],,1359.0,206.0,203.0,https://pypi.org/project/adabound,2019-02-26 04:23:45.000,3.0,1359.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +671,kubric,google-research/kubric,image,,https://github.com/google-research/kubric,https://github.com/google-research/kubric,Apache-2.0,2020-07-22 19:56:38.000,2024-06-27 09:47:40.000000,2024-06-27 09:47:40,546.0,1.0,223.0,42.0,133.0,63.0,127.0,2272.0,A data generation pipeline for creating semi-realistic synthetic multi-object videos with rich annotations such as..,30.0,21,True,2023-12-27 00:46:01.000,2023.12.27,773.0,kubric-nightly,,,,,4549.0,6.0,6.0,https://pypi.org/project/kubric-nightly,2023-12-27 00:46:01.000,,4549.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +672,pdftabextract,WZBSocialScienceCenter/pdftabextract,ocr,,https://github.com/WZBSocialScienceCenter/pdftabextract,https://github.com/WZBSocialScienceCenter/pdftabextract,Apache-2.0,2016-07-08 11:44:46.000,2022-06-24 09:51:22.000000,2022-06-24 09:51:22,171.0,,370.0,84.0,4.0,5.0,18.0,2203.0,A set of tools for extracting tables from PDF files helping to do data mining on (OCR-processed) scanned documents.,3.0,21,False,2018-01-09 08:00:24.000,0.3.0,5.0,pdftabextract,,,,,835.0,50.0,50.0,https://pypi.org/project/pdftabextract,2018-01-09 08:00:24.000,,835.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +673,reformer-pytorch,lucidrains/reformer-pytorch,pytorch-utils,,https://github.com/lucidrains/reformer-pytorch,https://github.com/lucidrains/reformer-pytorch,MIT,2020-01-09 20:42:37.000,2023-06-21 14:17:49.000000,2023-06-21 14:07:30,249.0,,248.0,54.0,35.0,16.0,105.0,2091.0,"Reformer, the efficient Transformer, in Pytorch.",11.0,21,False,2021-11-06 23:09:00.000,1.4.4,139.0,reformer-pytorch,,,['pytorch'],,8203.0,,,https://pypi.org/project/reformer-pytorch,2021-11-06 23:09:00.000,,8203.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +674,ecco,jalammar/ecco,interpretability,,https://github.com/jalammar/ecco,https://github.com/jalammar/ecco,BSD-3-Clause,2020-11-07 10:06:34.000,2024-08-15 19:08:06.000000,2024-08-15 19:08:06,312.0,1.0,163.0,24.0,34.0,33.0,31.0,1962.0,"Explain, analyze, and visualize NLP language models. Ecco creates interactive visualizations directly in Jupyter..",12.0,21,True,2022-01-09 21:17:53.000,0.1.2,18.0,ecco,conda-forge/ecco,,['pytorch'],105.0,514.0,30.0,29.0,https://pypi.org/project/ecco,2022-01-09 21:14:50.000,1.0,353.0,https://anaconda.org/conda-forge/ecco,2023-06-16 19:28:19.211,5275.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +675,DIG,divelab/DIG,graph,,https://github.com/divelab/DIG,https://github.com/divelab/DIG,GPL-3.0,2020-10-30 03:51:15.000,2024-07-15 07:18:56.000000,2024-02-04 20:37:53,1083.0,,281.0,30.0,41.0,34.0,176.0,1838.0,A library for graph deep learning research.,50.0,21,False,2023-04-07 20:33:15.000,1.1.0,10.0,dig,,,,,465.0,,,https://pypi.org/project/dig,2015-08-23 10:30:20.000,,465.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +676,benchmark_VAE,clementchadebec/benchmark_VAE,others,,https://github.com/clementchadebec/benchmark_VAE,https://github.com/clementchadebec/benchmark_VAE,Apache-2.0,2021-10-02 16:26:24.000,2024-07-31 12:13:28.000000,2024-07-17 07:59:47,373.0,2.0,158.0,18.0,74.0,23.0,41.0,1764.0,Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022).,18.0,21,True,2023-09-06 15:46:59.000,0.1.2,12.0,pythae,,,['pytorch'],,1658.0,31.0,31.0,https://pypi.org/project/pythae,2023-09-06 15:46:59.000,,1658.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +677,graph4nlp,graph4ai/graph4nlp,graph,,https://github.com/graph4ai/graph4nlp,https://github.com/graph4ai/graph4nlp,Apache-2.0,2020-07-16 03:28:48.000,2024-06-24 03:38:13.000000,2022-11-13 04:54:45,1941.0,,197.0,29.0,424.0,11.0,163.0,1663.0,Graph4nlp is the library for the easy use of Graph Neural Networks for NLP. Welcome to visit our DLG4NLP website..,29.0,21,False,2022-01-20 18:07:32.000,0.5.5,12.0,graph4nlp,,,['pytorch'],,135.0,,,https://pypi.org/project/graph4nlp,2022-01-20 15:18:44.000,,135.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +678,Antialiased CNNs,adobe/antialiased-cnns,pytorch-utils,,https://github.com/adobe/antialiased-cnns,https://github.com/adobe/antialiased-cnns,CC BY-NC-SA 4.0,2019-05-14 20:51:25.000,2024-04-08 12:49:27.000000,2021-09-29 18:48:52,239.0,,200.0,38.0,7.0,15.0,33.0,1653.0,pip install antialiased-cnns to improve stability and accuracy.,6.0,21,False,2020-10-23 22:45:52.000,0.3,6.0,antialiased-cnns,,,['pytorch'],,4594.0,65.0,59.0,https://pypi.org/project/antialiased-cnns,2020-10-23 22:42:49.000,6.0,4594.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +679,ThunderSVM,Xtra-Computing/thundersvm,ml-frameworks,,https://github.com/Xtra-Computing/thundersvm,https://github.com/Xtra-Computing/thundersvm,Apache-2.0,2014-12-11 04:24:04.000,2024-04-01 08:11:14.000000,2024-04-01 08:11:13,912.0,,210.0,56.0,52.0,80.0,149.0,1560.0,ThunderSVM: A Fast SVM Library on GPUs and CPUs.,37.0,21,True,2020-03-13 12:36:30.000,0.3.12,9.0,thundersvm,,,,2849.0,721.0,,,https://pypi.org/project/thundersvm,2020-03-13 12:36:30.000,,691.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +680,lore,instacart/lore,ml-experiments,,https://github.com/instacart/lore,https://github.com/instacart/lore,MIT,2017-10-19 21:51:45.000,2023-05-13 02:26:19.000000,2022-09-27 19:41:48,274.0,,135.0,102.0,150.0,21.0,20.0,1550.0,Lore makes machine learning approachable for Software Engineers and maintainable for Machine Learning Researchers.,29.0,21,False,2022-02-18 18:01:38.000,0.8.6,233.0,lore,,,,,1932.0,23.0,23.0,https://pypi.org/project/lore,2022-02-18 18:01:38.000,,1932.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +681,MLBox,AxeldeRomblay/MLBox,hyperopt,,https://github.com/AxeldeRomblay/MLBox,https://github.com/AxeldeRomblay/MLBox,BSD-1-Clause,2017-06-01 16:59:24.000,2023-08-06 18:20:04.000000,2020-08-25 09:26:27,1121.0,,271.0,65.0,51.0,23.0,75.0,1490.0,MLBox is a powerful Automated Machine Learning python library.,9.0,21,False,2020-08-25 09:32:37.000,0.8.5,21.0,mlbox,,,,,342.0,36.0,36.0,https://pypi.org/project/mlbox,2020-08-25 09:32:37.000,,342.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +682,anaGo,Hironsan/anago,nlp,,https://github.com/Hironsan/anago,https://github.com/Hironsan/anago,MIT,2017-06-26 21:28:36.000,2022-12-07 23:44:31.000000,2021-04-01 12:34:50,298.0,,353.0,60.0,47.0,37.0,71.0,1480.0,"Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition, Part-of-Speech Tagging and so on.",11.0,21,False,2018-07-17 01:59:21.000,1.0.8,14.0,anago,,,['tensorflow'],,186.0,39.0,33.0,https://pypi.org/project/anago,2018-07-17 01:59:21.000,6.0,186.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +683,tensorrec,jfkirk/tensorrec,recommender-systems,,https://github.com/jfkirk/tensorrec,https://github.com/jfkirk/tensorrec,Apache-2.0,2017-02-28 18:51:11.000,2023-05-22 21:34:54.000000,2020-02-04 21:10:25,334.0,,222.0,64.0,48.0,40.0,90.0,1274.0,A TensorFlow recommendation algorithm and framework in Python.,9.0,21,False,2019-04-02 00:53:47.000,0.26.2,30.0,tensorrec,,,['tensorflow'],,252.0,36.0,36.0,https://pypi.org/project/tensorrec,2019-04-02 00:53:47.000,,252.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +684,Sockeye,awslabs/sockeye,nlp,,https://github.com/awslabs/sockeye,https://github.com/awslabs/sockeye,Apache-2.0,2017-06-08 07:44:30.000,2024-06-07 14:38:03.000000,2024-06-07 14:37:59,835.0,,324.0,51.0,796.0,11.0,300.0,1210.0,Sequence-to-sequence framework with a focus on Neural Machine Translation based on PyTorch.,60.0,21,True,2023-03-03 07:51:00.411,3.1.34,85.0,sockeye,,,['mxnet'],19.0,762.0,,,https://pypi.org/project/sockeye,2023-03-03 07:51:00.411,,762.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +685,ADTK,arundo/adtk,time-series-data,,https://github.com/arundo/adtk,https://github.com/arundo/adtk,MPL-2.0,2019-09-27 00:34:22.000,2024-08-01 11:53:43.000000,2020-04-17 02:27:44,79.0,,144.0,25.0,77.0,51.0,36.0,1076.0,A Python toolkit for rule-based/unsupervised anomaly detection in time series.,11.0,21,False,2020-04-17 02:18:00.000,0.6.2,13.0,adtk,conda-forge/adtk,,,,240186.0,5.0,,https://pypi.org/project/adtk,2020-04-17 02:18:00.000,5.0,240026.0,https://anaconda.org/conda-forge/adtk,2023-06-16 19:18:16.533,8690.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +686,fastFM,ibayer/fastFM,recommender-systems,,https://github.com/ibayer/fastFM,https://github.com/ibayer/fastFM,BSD-3-Clause,2014-10-27 12:25:51.000,2022-07-17 13:12:39.000000,2021-03-24 12:22:31,297.0,,205.0,27.0,61.0,52.0,61.0,1075.0,fastFM: A Library for Factorization Machines.,20.0,21,False,2017-11-23 06:59:56.000,0.2.11,10.0,fastfm,,,,703.0,518.0,124.0,122.0,https://pypi.org/project/fastfm,2017-11-23 06:59:56.000,2.0,512.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +687,attention-ocr,emedvedev/attention-ocr,ocr,,https://github.com/emedvedev/attention-ocr,https://github.com/emedvedev/attention-ocr,MIT,2017-07-21 18:35:19.000,2023-10-20 17:48:54.000000,2023-10-20 17:48:54,207.0,,250.0,48.0,46.0,26.0,127.0,1066.0,A Tensorflow model for text recognition (CNN + seq2seq with visual attention) available as a Python package and..,28.0,21,True,2020-10-12 06:56:40.000,0.7.6,21.0,aocr,,,['tensorflow'],,186.0,29.0,29.0,https://pypi.org/project/aocr,2019-04-19 05:28:27.000,,186.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +688,Baal,baal-org/baal,probabilistics,,https://github.com/baal-org/baal,https://github.com/baal-org/baal,Apache-2.0,2019-09-30 20:16:26.000,2024-06-27 20:02:41.000000,2024-06-27 20:02:41,240.0,2.0,86.0,18.0,160.0,20.0,94.0,858.0,Bayesian active learning library for research and industrial usecases.,23.0,21,True,2024-06-11 15:50:56.000,2.0.0,21.0,baal,conda-forge/baal,,,,1834.0,62.0,60.0,https://pypi.org/project/baal,2024-06-11 15:50:56.000,2.0,1614.0,https://anaconda.org/conda-forge/baal,2023-06-12 15:14:19.747,9684.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +689,TF Compression,tensorflow/compression,tensorflow-utils,,https://github.com/tensorflow/compression,https://github.com/tensorflow/compression,Apache-2.0,2018-05-15 23:32:19.000,2024-08-07 20:25:13.000000,2024-08-07 18:21:25,294.0,1.0,248.0,46.0,18.0,11.0,91.0,850.0,Data compression in TensorFlow.,21.0,21,True,2024-08-07 20:25:13.000,2.17.0,26.0,tensorflow-compression,,,['tensorflow'],,2080.0,2.0,,https://pypi.org/project/tensorflow-compression,2024-02-02 01:38:32.000,2.0,2080.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +690,PDPbox,SauceCat/PDPbox,data-viz,,https://github.com/SauceCat/PDPbox,https://github.com/SauceCat/PDPbox,MIT,2017-06-26 08:01:54.000,2024-09-03 22:24:30.000000,2023-06-05 01:35:02,228.0,,129.0,18.0,25.0,28.0,39.0,840.0,python partial dependence plot toolbox.,7.0,21,False,2023-06-05 02:53:01.145,0.3.0,4.0,pdpbox,conda-forge/pdpbox,,,,13585.0,26.0,,https://pypi.org/project/pdpbox,2021-03-14 16:21:17.000,26.0,13240.0,https://anaconda.org/conda-forge/pdpbox,2023-06-10 14:57:37.569,21390.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +691,iterative-stratification,trent-b/iterative-stratification,sklearn-utils,,https://github.com/trent-b/iterative-stratification,https://github.com/trent-b/iterative-stratification,BSD-3-Clause,2018-02-04 00:32:10.000,2022-06-06 22:38:33.000000,2022-06-06 22:38:33,57.0,,75.0,6.0,5.0,2.0,23.0,839.0,scikit-learn cross validators for iterative stratification of multilabel data.,7.0,21,False,2021-10-03 18:49:49.000,0.1.7,6.0,iterative-stratification,,,['sklearn'],,21582.0,486.0,471.0,https://pypi.org/project/iterative-stratification,2021-10-03 18:49:49.000,15.0,21582.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +692,deeplift,kundajelab/deeplift,interpretability,,https://github.com/kundajelab/deeplift,https://github.com/kundajelab/deeplift,MIT,2016-06-01 02:18:06.000,2022-04-28 10:04:52.000000,2021-11-11 17:50:26,553.0,,160.0,37.0,46.0,43.0,49.0,815.0,Public facing deeplift repo.,11.0,21,False,2018-07-13 21:11:52.000,0.6.6,21.0,deeplift,,,,,487.0,106.0,97.0,https://pypi.org/project/deeplift,2020-11-11 09:32:57.000,9.0,487.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +693,Objax,google/objax,ml-frameworks,,https://github.com/google/objax,https://github.com/google/objax,Apache-2.0,2020-08-20 06:20:40.000,2024-01-27 00:16:56.000000,2024-01-27 00:08:50,463.0,,78.0,26.0,162.0,51.0,62.0,768.0,Objax is a machine learning framework that provides an Object Oriented layer for JAX.,26.0,21,True,2023-11-06 22:17:30.000,1.8.0,11.0,objax,,,['jax'],,561.0,59.0,55.0,https://pypi.org/project/objax,2023-11-06 22:03:10.000,4.0,561.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +694,NeoML,neoml-lib/neoml,ml-frameworks,,https://github.com/neoml-lib/neoml,https://github.com/neoml-lib/neoml,Apache-2.0,2020-06-14 17:37:36.000,2024-09-05 12:37:36.000000,2024-09-04 16:47:26,1237.0,40.0,126.0,30.0,1046.0,37.0,54.0,763.0,Machine learning framework for both deep learning and traditional algorithms.,40.0,21,True,2023-12-26 02:42:15.000,2.0.210,15.0,neoml,,,,,480.0,1.0,1.0,https://pypi.org/project/neoml,2023-12-26 02:42:15.000,,480.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +695,TreeInterpreter,andosa/treeinterpreter,interpretability,,https://github.com/andosa/treeinterpreter,https://github.com/andosa/treeinterpreter,BSD-3-Clause,2015-08-02 20:26:21.000,2023-07-18 10:50:27.000000,2021-02-28 18:33:06,37.0,,141.0,24.0,19.0,26.0,5.0,743.0,Package for interpreting scikit-learns decision tree and random forest predictions.,11.0,21,False,2021-01-10 20:12:39.000,0.2.3,5.0,treeinterpreter,conda-forge/treeinterpreter,,['sklearn'],,42159.0,663.0,655.0,https://pypi.org/project/treeinterpreter,2021-01-10 20:12:39.000,8.0,41981.0,https://anaconda.org/conda-forge/treeinterpreter,2023-06-16 19:22:55.011,8391.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +696,Test Tube,williamFalcon/test-tube,hyperopt,,https://github.com/williamFalcon/test-tube,https://github.com/williamFalcon/test-tube,MIT,2017-09-06 02:14:57.000,2022-07-22 06:10:37.000000,2020-03-17 22:44:47,642.0,,74.0,25.0,37.0,27.0,21.0,736.0,Python library to easily log experiments and parallelize hyperparameter search for neural networks.,16.0,21,False,2019-12-01 01:19:50.000,0.7.5,64.0,test_tube,,,,25.0,39659.0,35.0,,https://pypi.org/project/test_tube,2019-12-01 01:19:50.000,35.0,39659.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +697,combo,yzhao062/combo,sklearn-utils,,https://github.com/yzhao062/combo,https://github.com/yzhao062/combo,BSD-2-Clause,2019-07-14 01:13:36.000,2023-01-14 04:46:24.000000,2023-01-14 04:46:24,210.0,,107.0,30.0,1.0,15.0,3.0,641.0,(AAAI 20) A Python Toolbox for Machine Learning Model Combination.,2.0,21,False,2022-04-02 16:20:07.000,0.1.3,13.0,combo,,,"['sklearn', 'xgboost']",,33021.0,668.0,651.0,https://pypi.org/project/combo,2022-04-02 16:20:07.000,17.0,33021.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +698,Torchbearer,pytorchbearer/torchbearer,ml-frameworks,,https://github.com/pytorchbearer/torchbearer,https://github.com/pytorchbearer/torchbearer,MIT,2018-03-12 16:30:42.000,2023-12-04 11:10:47.000000,2023-12-04 11:10:46,442.0,,68.0,25.0,433.0,10.0,237.0,633.0,torchbearer: A model fitting library for PyTorch.,14.0,21,True,2023-12-01 18:48:07.000,0.5.5,26.0,torchbearer,,,['pytorch'],,340.0,94.0,90.0,https://pypi.org/project/torchbearer,2023-12-01 18:48:07.000,4.0,340.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +699,TensorBoard Logger,TeamHG-Memex/tensorboard_logger,ml-experiments,,https://github.com/TeamHG-Memex/tensorboard_logger,https://github.com/TeamHG-Memex/tensorboard_logger,MIT,2016-10-27 14:02:25.000,2022-12-26 20:24:35.000000,2019-10-21 07:52:07,46.0,,54.0,29.0,12.0,13.0,15.0,631.0,Log TensorBoard events without touching TensorFlow.,5.0,21,False,2018-02-08 07:28:51.000,0.1.0,5.0,tensorboard_logger,,,,,30260.0,217.0,209.0,https://pypi.org/project/tensorboard_logger,2018-02-08 07:28:51.000,8.0,30260.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +700,detecto,alankbi/detecto,image,,https://github.com/alankbi/detecto,https://github.com/alankbi/detecto,MIT,2019-12-11 21:50:28.000,2024-07-25 11:20:23.000000,2022-02-09 16:35:40,142.0,,103.0,23.0,26.0,44.0,61.0,612.0,Build fully-functioning computer vision models with PyTorch.,12.0,21,False,2022-02-02 00:22:07.000,1.2.2,13.0,detecto,conda-forge/detecto,,['pytorch'],,3599.0,180.0,178.0,https://pypi.org/project/detecto,2022-02-02 00:12:06.000,2.0,3481.0,https://anaconda.org/conda-forge/detecto,2023-06-16 19:26:16.964,4612.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +701,skope-rules,scikit-learn-contrib/skope-rules,sklearn-utils,,https://github.com/scikit-learn-contrib/skope-rules,https://github.com/scikit-learn-contrib/skope-rules,BSD-1-Clause,2018-02-18 13:42:47.000,2024-01-31 14:01:51.000000,2023-02-14 11:18:28,249.0,,95.0,26.0,32.0,35.0,6.0,608.0,machine learning with logical rules in Python.,19.0,21,False,2020-12-11 09:37:02.000,1.0.1,4.0,skope-rules,,,['sklearn'],,19716.0,403.0,395.0,https://pypi.org/project/skope-rules,2020-01-25 12:01:37.000,8.0,19716.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +702,Neuraxle,Neuraxio/Neuraxle,hyperopt,,https://github.com/Neuraxio/Neuraxle,https://github.com/Neuraxio/Neuraxle,Apache-2.0,2019-03-26 21:01:54.000,2023-05-01 22:43:43.000000,2022-08-16 17:43:49,1877.0,,57.0,19.0,216.0,49.0,315.0,605.0,The worlds cleanest AutoML library - Do hyperparameter tuning with the right pipeline abstractions to write clean deep..,9.0,21,False,2022-08-16 19:54:29.000,0.8.1,27.0,neuraxle,,,,,275.0,63.0,62.0,https://pypi.org/project/neuraxle,2022-08-16 19:50:37.507,1.0,275.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +703,featurewiz,AutoViML/featurewiz,hyperopt,,https://github.com/AutoViML/featurewiz,https://github.com/AutoViML/featurewiz,Apache-2.0,2020-11-29 16:46:16.000,2024-05-02 14:24:25.000000,2024-05-02 14:23:46,346.0,,85.0,7.0,20.0,3.0,92.0,575.0,Use advanced feature engineering strategies and select best features from your data set with a single line of code...,18.0,21,True,2024-02-10 13:12:00.000,0.5.7,162.0,featurewiz,,,,,9487.0,74.0,72.0,https://pypi.org/project/featurewiz,2024-02-10 13:12:00.000,2.0,9487.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +704,joypy,leotac/joypy,data-viz,,https://github.com/leotac/joypy,https://github.com/leotac/joypy,MIT,2017-07-30 17:18:50.000,2024-03-21 11:25:40.000000,2021-12-19 09:41:43,133.0,,57.0,10.0,21.0,15.0,37.0,553.0,Joyplots in Python with matplotlib & pandas.,8.0,21,False,2021-12-19 09:42:50.000,0.2.6,17.0,joypy,conda-forge/joypy,,,,11203.0,445.0,436.0,https://pypi.org/project/joypy,2021-12-19 09:42:50.000,9.0,10787.0,https://anaconda.org/conda-forge/joypy,2023-06-16 16:14:43.440,27484.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +705,pyhsmm,mattjj/pyhsmm,probabilistics,,https://github.com/mattjj/pyhsmm,https://github.com/mattjj/pyhsmm,MIT,2012-03-18 17:40:13.000,2022-10-26 08:37:57.000000,2020-08-24 17:03:59,1426.0,,167.0,56.0,20.0,39.0,60.0,546.0,Bayesian inference in HSMMs and HMMs.,13.0,21,False,2017-05-10 17:14:37.000,0.1.7,8.0,pyhsmm,,,,,174.0,32.0,31.0,https://pypi.org/project/pyhsmm,2017-05-10 17:14:37.000,1.0,174.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +706,apricot,jmschrei/apricot,others,,https://github.com/jmschrei/apricot,https://github.com/jmschrei/apricot,MIT,2018-08-12 02:42:12.000,2024-08-20 18:39:53.000000,2021-11-18 21:06:54,172.0,,48.0,9.0,10.0,13.0,21.0,496.0,apricot implements submodular optimization for the purpose of selecting subsets of massive data sets to train machine..,4.0,21,False,2023-11-17 16:33:58.000,0.6.1,14.0,apricot-select,,,,28.0,6398.0,141.0,133.0,https://pypi.org/project/apricot-select,2021-02-18 06:55:02.000,8.0,6398.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +707,Julius,adefossez/julius,audio,,https://github.com/adefossez/julius,https://github.com/adefossez/julius,MIT,2020-10-26 10:54:21.000,2022-09-26 14:14:12.000000,2022-09-19 16:13:14,69.0,,25.0,9.0,9.0,2.0,9.0,419.0,Fast PyTorch based DSP for audio and 1D signals.,2.0,21,False,2022-09-20 06:43:57.063,0.2.7,11.0,julius,,,['pytorch'],,435639.0,1758.0,1752.0,https://pypi.org/project/julius,2022-09-20 06:43:57.063,6.0,435639.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +708,optunity,claesenm/optunity,hyperopt,,https://github.com/claesenm/optunity,https://github.com/claesenm/optunity,BSD-3-Clause,2014-05-28 17:29:11.000,2023-11-25 01:31:29.000000,2020-05-11 14:32:38,782.0,,79.0,24.0,12.0,48.0,49.0,413.0,optimization routines for hyperparameter tuning.,9.0,21,False,2015-09-30 05:02:00.000,1.1.1,6.0,optunity,,,,97.0,4531.0,128.0,125.0,https://pypi.org/project/optunity,2015-09-30 05:02:00.000,3.0,4531.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +709,tsflex,predict-idlab/tsflex,time-series-data,,https://github.com/predict-idlab/tsflex,https://github.com/predict-idlab/tsflex,MIT,2021-07-06 15:16:45.577,2024-08-24 14:34:24.000000,2024-08-24 14:34:21,823.0,3.0,25.0,8.0,78.0,30.0,22.0,395.0,Flexible time series feature extraction & processing.,6.0,21,True,2024-04-04 10:31:07.000,0.4.0,37.0,tsflex,conda-forge/tsflex,,,,1500.0,16.0,15.0,https://pypi.org/project/tsflex,2024-04-04 10:23:01.000,1.0,843.0,https://anaconda.org/conda-forge/tsflex,2024-04-08 09:54:58.786,24992.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +710,SUOD,yzhao062/SUOD,others,,https://github.com/yzhao062/SUOD,https://github.com/yzhao062/SUOD,BSD-2-Clause,2019-11-20 00:23:54.000,2024-02-08 01:53:44.000000,2024-02-08 01:48:49,168.0,,49.0,17.0,2.0,12.0,3.0,377.0,(MLSys 21) An Acceleration System for Large-scare Unsupervised Heterogeneous Outlier Detection (Anomaly Detection).,3.0,21,True,2024-02-08 01:53:44.000,0.1.3,14.0,suod,,,,,18735.0,535.0,527.0,https://pypi.org/project/suod,2024-02-08 01:53:44.000,8.0,18735.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +711,TensorFlow Cloud,tensorflow/cloud,tensorflow-utils,,https://github.com/tensorflow/cloud,https://github.com/tensorflow/cloud,Apache-2.0,2020-02-10 18:51:59.000,2024-02-25 19:17:18.000000,2024-02-25 19:17:13,576.0,,85.0,29.0,318.0,75.0,27.0,372.0,The TensorFlow Cloud repository provides APIs that will allow to easily go from debugging and training your Keras and..,27.0,21,True,2021-06-17 01:15:10.000,0.1.16,19.0,tensorflow-cloud,,,['tensorflow'],,33125.0,7.0,,https://pypi.org/project/tensorflow-cloud,2021-06-17 01:15:10.000,7.0,33125.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +712,impyute,eltonlaw/impyute,others,,https://github.com/eltonlaw/impyute,https://github.com/eltonlaw/impyute,MIT,2017-01-21 09:16:27.000,2021-11-06 21:15:04.000000,2021-11-06 21:15:04,292.0,,49.0,11.0,37.0,29.0,37.0,352.0,Data imputations library to preprocess datasets with missing data.,11.0,21,False,2019-04-29 02:33:05.659,0.0.8,8.0,impyute,,,,,3523.0,255.0,239.0,https://pypi.org/project/impyute,2017-05-31 08:31:47.000,16.0,3523.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +713,launchpad,deepmind/launchpad,distributed-ml,,https://github.com/google-deepmind/launchpad,https://github.com/google-deepmind/launchpad,Apache-2.0,2021-02-18 15:16:49.000,2023-08-22 08:22:46.000000,2023-08-22 08:22:26,367.0,,35.0,18.0,6.0,19.0,21.0,310.0,Launchpad is a library that simplifies writing distributed programs and seamlessly launching them on a range of..,28.0,21,False,2022-04-28 06:23:38.000,0.5.2,9.0,dm-launchpad,,,['tensorflow'],,1349.0,114.0,111.0,https://pypi.org/project/dm-launchpad,2022-04-28 06:23:38.000,3.0,1349.0,,,,3.0,,,,,,,,google-deepmind/launchpad,,,,,,,,,,,,,,,,, +714,upgini,upgini/upgini,tabular,,https://github.com/upgini/upgini,https://github.com/upgini/upgini,BSD-3-Clause,2021-12-08 21:53:58.000,2024-09-05 14:47:34.000000,2024-09-05 14:47:26,781.0,40.0,25.0,5.0,294.0,5.0,,310.0,Data search & enrichment library for Machine Learning Easily find and add relevant features to your ML & AI pipeline..,13.0,21,True,2024-09-05 14:47:28.000,1.2.3,799.0,upgini,,,,,9872.0,7.0,7.0,https://pypi.org/project/upgini,2024-09-05 14:47:28.000,,9872.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +715,sk-dist,Ibotta/sk-dist,distributed-ml,,https://github.com/Ibotta/sk-dist,https://github.com/Ibotta/sk-dist,Apache-2.0,2019-08-14 21:07:17.000,2024-04-18 12:38:22.000000,2023-02-07 20:17:52,60.0,,56.0,26.0,42.0,8.0,10.0,285.0,Distributed scikit-learn meta-estimators in PySpark.,8.0,21,False,2020-05-14 22:20:14.000,0.1.9,12.0,sk-dist,,,"['sklearn', 'spark']",,458639.0,19.0,17.0,https://pypi.org/project/sk-dist,2020-05-14 22:20:14.000,2.0,458639.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +716,Glow,projectglow/glow,medical-data,,https://github.com/projectglow/glow,https://github.com/projectglow/glow,Apache-2.0,2019-10-04 21:26:47.000,2024-09-01 00:12:21.000000,2024-06-26 15:54:34,489.0,6.0,109.0,19.0,539.0,58.0,126.0,263.0,An open-source toolkit for large-scale genomic analysis.,28.0,21,False,2024-03-12 08:52:09.000,2.0.0,16.0,glow.py,conda-forge/glow,,,89.0,69266.0,,,https://pypi.org/project/glow.py,2024-03-12 08:52:09.000,,69153.0,https://anaconda.org/conda-forge/glow,2024-03-13 03:00:18.463,4842.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +717,OMLT,cog-imperial/omlt,model-serialisation,,https://github.com/cog-imperial/OMLT,https://github.com/cog-imperial/OMLT,,2021-06-03 12:39:38.000,2024-08-26 15:06:41.000000,2024-08-24 17:15:47,524.0,4.0,57.0,14.0,89.0,26.0,39.0,261.0,Represent trained machine learning models as Pyomo optimization formulations.,21.0,21,False,2024-08-26 15:06:41.000,1.2.0,8.0,omlt,,,,,18251.0,22.0,19.0,https://pypi.org/project/omlt,2024-08-26 15:06:41.000,3.0,18251.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +718,pyRDF2Vec,IBCNServices/pyRDF2Vec,graph,,https://github.com/IBCNServices/pyRDF2Vec,https://github.com/IBCNServices/pyRDF2Vec,MIT,2019-06-13 11:36:12.000,2024-09-03 04:39:16.000000,2023-07-02 18:02:16,1462.0,,47.0,16.0,203.0,27.0,64.0,243.0,Python Implementation and Extension of RDF2Vec.,7.0,21,False,2021-06-09 10:56:14.000,0.2.3,11.0,pyrdf2vec,,,,,425.0,50.0,44.0,https://pypi.org/project/pyrdf2vec,2021-06-09 10:56:14.000,6.0,425.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +719,Larq Compute Engine,larq/compute-engine,model-serialisation,,https://github.com/larq/compute-engine,https://github.com/larq/compute-engine,Apache-2.0,2019-08-29 15:02:43.000,2024-08-09 06:53:19.000000,2024-08-09 06:53:17,591.0,6.0,34.0,24.0,644.0,21.0,129.0,242.0,Highly optimized inference engine for Binarized Neural Networks.,18.0,21,False,2024-06-21 06:39:45.000,0.16.0,21.0,larq-compute-engine,,,,1143.0,1387.0,8.0,8.0,https://pypi.org/project/larq-compute-engine,2024-06-21 07:18:03.000,,1367.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +720,DEβ«ΆTR,facebookresearch/detr,image,,https://github.com/facebookresearch/detr,https://github.com/facebookresearch/detr,Apache-2.0,2020-05-26 23:54:52.000,2024-03-12 15:58:25.000000,2024-03-12 15:58:25,48.0,,2392.0,148.0,89.0,255.0,286.0,13319.0,End-to-End Object Detection with Transformers.,27.0,20,True,2020-06-29 16:41:01.000,0.2,1.0,,,,['pytorch'],,,21.0,21.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +721,DeepMatcher,anhaidgroup/deepmatcher,nlp,,https://github.com/anhaidgroup/deepmatcher,https://github.com/anhaidgroup/deepmatcher,BSD-3-Clause,2017-12-01 19:01:11.000,2024-06-18 11:46:06.000000,2021-06-13 00:22:13,176.0,,1717.0,19.0,19.0,72.0,24.0,5077.0,Python package for performing Entity and Text Matching using Deep Learning.,7.0,20,False,2021-05-27 22:28:29.000,0.1.2,13.0,deepmatcher,,,,,5140.0,,,https://pypi.org/project/deepmatcher,2021-06-13 01:13:24.000,,5140.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +722,BytePS,bytedance/byteps,distributed-ml,,https://github.com/bytedance/byteps,https://github.com/bytedance/byteps,Apache-2.0,2019-06-25 07:00:13.000,2023-10-03 18:02:27.000000,2022-02-10 07:36:23,432.0,,476.0,85.0,180.0,108.0,161.0,3612.0,A high performance and generic framework for distributed DNN training.,21.0,20,False,2020-08-27 15:42:13.000,0.2.4,8.0,byteps,,,,,121.0,2.0,2.0,https://pypi.org/project/byteps,2021-08-02 17:37:42.000,,100.0,,,,3.0,bytepsimage/tensorflow,https://hub.docker.com/r/bytepsimage/tensorflow,2020-03-03 02:33:23.358610,,1345.0,,,,,,,,,,,,,,,,,,,, +723,TensorWatch,microsoft/tensorwatch,ml-experiments,,https://github.com/microsoft/tensorwatch,https://github.com/microsoft/tensorwatch,MIT,2019-05-15 08:29:34.000,2023-08-30 07:47:40.000000,2023-08-30 07:47:36,119.0,,357.0,100.0,16.0,53.0,17.0,3407.0,"Debugging, monitoring and visualization for Python Machine Learning and Data Science.",15.0,20,False,2020-03-04 07:26:22.000,0.9.1,14.0,tensorwatch,,,,,823.0,157.0,150.0,https://pypi.org/project/tensorwatch,2020-03-04 07:26:22.000,7.0,823.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +724,lightseq,bytedance/lightseq,nlp,,https://github.com/bytedance/lightseq,https://github.com/bytedance/lightseq,Apache-2.0,2019-12-06 08:25:24.000,2023-05-16 10:47:48.000000,2023-05-10 04:35:39,269.0,,321.0,59.0,242.0,175.0,111.0,3163.0,LightSeq: A High Performance Library for Sequence Processing and Generation.,20.0,20,False,2022-11-03 06:46:55.989,3.0.1,22.0,lightseq,,,,688.0,3690.0,2.0,,https://pypi.org/project/lightseq,2022-11-03 06:46:55.989,2.0,3678.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +725,igel,nidhaloff/igel,hyperopt,,https://github.com/nidhaloff/igel,https://github.com/nidhaloff/igel,MIT,2020-08-27 20:54:59.000,2023-04-08 21:24:52.000000,2023-04-08 21:24:51,429.0,,171.0,65.0,54.0,6.0,44.0,3080.0,"a delightful machine learning tool that allows you to train, test, and use models without writing code.",20.0,20,False,2021-11-19 16:51:47.000,1.0.0,34.0,igel,,,,46.0,335.0,5.0,5.0,https://pypi.org/project/igel,2021-11-19 16:45:29.543,,335.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +726,image-match,ProvenanceLabs/image-match,image,,https://github.com/rhsimplex/image-match,https://github.com/rhsimplex/image-match,Apache-2.0,2016-03-08 18:16:45.000,2022-12-06 11:29:04.000000,2022-12-06 11:29:04,406.0,,398.0,101.0,54.0,64.0,48.0,2932.0,Quickly search over billions of images.,19.0,20,False,2017-02-13 14:54:48.000,1.1.2,10.0,image_match,,,,,694.0,4.0,,https://pypi.org/project/image_match,2017-02-13 14:54:48.000,4.0,694.0,,,,3.0,,,,,,,,rhsimplex/image-match,,,,,,,,,,,,,,,,, +727,StreamAlert,airbnb/streamalert,others,,https://github.com/airbnb/streamalert,https://github.com/airbnb/streamalert,Apache-2.0,2017-01-22 01:10:56.000,2023-10-23 17:15:34.000000,2022-07-20 20:54:36,1904.0,,332.0,101.0,1000.0,94.0,263.0,2851.0,"StreamAlert is a serverless, realtime data analysis framework which empowers you to ingest, analyze, and alert on data..",33.0,20,False,2021-11-04 19:07:51.000,3.5.0,28.0,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +728,DeepWalk,phanein/deepwalk,graph,,https://github.com/phanein/deepwalk,https://github.com/phanein/deepwalk,GPL-3.0,2014-08-23 03:38:20.000,2023-06-14 23:22:41.000000,2020-04-02 01:05:35,46.0,,831.0,84.0,30.0,46.0,80.0,2663.0,DeepWalk - Deep Learning for Graphs.,10.0,20,False,2018-04-29 21:05:18.000,1.0.3,4.0,deepwalk,,,,,519.0,71.0,71.0,https://pypi.org/project/deepwalk,2018-04-29 21:05:18.000,,519.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +729,Coach,IntelLabs/coach,reinforcement-learning,,https://github.com/IntelLabs/coach,https://github.com/IntelLabs/coach,Apache-2.0,2017-10-01 19:27:43.000,2022-12-11 17:54:07.000000,2022-12-11 17:54:06,524.0,,462.0,126.0,225.0,90.0,183.0,2322.0,Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning..,38.0,20,False,2019-10-10 14:17:10.000,1.0.1,13.0,rl_coach,,,,,93.0,2.0,,https://pypi.org/project/rl_coach,2019-10-10 14:17:10.000,2.0,93.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +730,pycls,facebookresearch/pycls,image,,https://github.com/facebookresearch/pycls,https://github.com/facebookresearch/pycls,MIT,2019-06-10 22:47:17.000,2024-03-20 15:45:40.000000,2023-08-26 20:55:56,106.0,,237.0,61.0,106.0,27.0,56.0,2133.0,"Codebase for Image Classification Research, written in PyTorch.",19.0,20,False,2021-05-21 00:29:47.000,0.2,3.0,pycls,,,['pytorch'],,1234.0,19.0,19.0,https://pypi.org/project/pycls,2020-09-05 00:21:00.000,,1234.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +731,BlazingSQL,BlazingDB/blazingsql,gpu-utilities,,https://github.com/BlazingDB/blazingsql,https://github.com/BlazingDB/blazingsql,Apache-2.0,2018-09-24 18:25:45.000,2023-06-16 16:17:31.557000,2021-09-30 21:51:09,8208.0,,181.0,55.0,895.0,129.0,586.0,1928.0,"BlazingSQL is a lightweight, GPU accelerated, SQL engine for Python. Built on RAPIDS cuDF.",52.0,20,False,2021-08-16 15:40:43.000,21.08.00,19.0,,blazingsql/blazingsql-protocol,,,,17.0,,,,,,,https://anaconda.org/blazingsql/blazingsql-protocol,2023-06-16 16:17:31.557,1037.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +732,greykite,linkedin/greykite,time-series-data,,https://github.com/linkedin/greykite,https://github.com/linkedin/greykite,BSD-2-Clause,2021-04-27 17:05:53.000,2024-06-13 10:11:03.000000,2024-01-16 17:27:35,27.0,,104.0,38.0,31.0,30.0,79.0,1809.0,"A flexible, intuitive and fast forecasting library.",10.0,20,True,2024-01-18 18:33:20.000,1.0.0,11.0,greykite,,,,32.0,6552.0,33.0,33.0,https://pypi.org/project/greykite,2024-01-12 20:13:07.000,,6552.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +733,Magnitude,plasticityai/magnitude,nn-search,,https://github.com/plasticityai/magnitude,https://github.com/plasticityai/magnitude,MIT,2018-02-24 07:28:16.000,2023-08-03 00:59:57.000000,2020-07-17 20:19:46,350.0,,118.0,37.0,11.0,39.0,51.0,1622.0,"A fast, efficient universal vector embedding utility package.",4.0,20,False,2020-05-25 11:26:36.000,0.1.143,128.0,pymagnitude,,,,,1480.0,9.0,,https://pypi.org/project/pymagnitude,2020-05-25 11:26:36.000,9.0,1480.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +734,DELTA,Delta-ML/delta,nlp,,https://github.com/Delta-ML/delta,https://github.com/Delta-ML/delta,Apache-2.0,2019-05-29 08:33:57.000,2024-04-19 09:46:18.000000,2020-12-17 06:57:15,932.0,,292.0,66.0,202.0,5.0,74.0,1590.0,DELTA is a deep learning based natural language and speech processing platform.,41.0,20,False,2020-07-16 09:31:45.000,0.3.3,4.0,delta-nlp,,,['tensorflow'],,230.0,1.0,1.0,https://pypi.org/project/delta-nlp,2020-03-27 04:46:19.000,,26.0,,,,3.0,zh794390558/delta,https://hub.docker.com/r/zh794390558/delta,2021-08-03 14:50:00.516864,,13118.0,,,,,,,,,,,,,,,,,,,, +735,Lambda Networks,lucidrains/lambda-networks,pytorch-utils,,https://github.com/lucidrains/lambda-networks,https://github.com/lucidrains/lambda-networks,MIT,2020-10-08 19:01:15.000,2020-11-18 19:54:34.000000,2020-11-18 19:54:30,31.0,,155.0,46.0,3.0,13.0,15.0,1532.0,"Implementation of LambdaNetworks, a new approach to image recognition that reaches SOTA with less compute.",3.0,20,False,2020-11-18 08:19:23.000,0.4.0,11.0,lambda-networks,,,['pytorch'],,1708.0,29.0,29.0,https://pypi.org/project/lambda-networks,2020-11-18 08:19:23.000,,1708.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +736,DLTK,DLTK/DLTK,medical-data,,https://github.com/DLTK/DLTK,https://github.com/DLTK/DLTK,Apache-2.0,2017-05-02 15:40:36.000,2023-03-24 22:27:46.000000,2019-01-21 14:01:28,379.0,,405.0,101.0,36.0,13.0,24.0,1426.0,Deep Learning Toolkit for Medical Image Analysis.,9.0,20,False,2018-02-26 17:43:57.000,0.2.1,5.0,dltk,,,['tensorflow'],,95.0,32.0,32.0,https://pypi.org/project/dltk,2018-02-26 17:43:57.000,,95.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +737,DiCE,interpretml/DiCE,interpretability,,https://github.com/interpretml/DiCE,https://github.com/interpretml/DiCE,MIT,2019-05-02 09:51:02.000,2024-04-17 19:59:55.000000,2024-04-17 19:59:46,779.0,,182.0,18.0,262.0,77.0,94.0,1331.0,Generate Diverse Counterfactual Explanations for any machine learning model.,19.0,20,True,2023-10-26 11:36:48.000,0.11,12.0,dice-ml,,,"['tensorflow', 'pytorch']",,42427.0,6.0,,https://pypi.org/project/dice-ml,2023-10-27 03:54:06.000,6.0,42427.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +738,doc2text,jlsutherland/doc2text,ocr,,https://github.com/jlsutherland/doc2text,https://github.com/jlsutherland/doc2text,MIT,2016-08-28 19:30:02.000,2020-12-01 22:56:27.000000,2020-12-01 22:56:26,62.0,,101.0,39.0,13.0,14.0,9.0,1272.0,Detect text blocks and OCR poorly scanned PDFs in bulk. Python module available via pip.,5.0,20,False,2016-09-06 21:59:21.000,0.2.4,5.0,doc2text,,,,,2543.0,158.0,156.0,https://pypi.org/project/doc2text,2016-09-06 21:59:21.000,2.0,2543.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +739,AlphaPy,ScottfreeLLC/AlphaPy,hyperopt,,https://github.com/ScottfreeLLC/AlphaPy,https://github.com/ScottfreeLLC/AlphaPy,Apache-2.0,2016-02-14 00:47:32.000,2024-02-10 16:41:21.000000,2024-02-10 16:41:20,438.0,,200.0,62.0,7.0,13.0,29.0,1124.0,Python AutoML for Trading Systems and Sports Betting.,5.0,20,True,2020-08-29 18:48:20.000,2.5.0,25.0,alphapy,,,,,237.0,5.0,5.0,https://pypi.org/project/alphapy,2020-08-29 18:44:15.000,,237.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +740,geoplotlib,andrea-cuttone/geoplotlib,geospatial-data,,https://github.com/andrea-cuttone/geoplotlib,https://github.com/andrea-cuttone/geoplotlib,MIT,2015-02-24 13:13:07.000,2023-06-16 19:26:09.140000,2019-05-06 07:06:50,159.0,,169.0,57.0,14.0,30.0,19.0,1025.0,python toolbox for visualizing geographical data and making maps.,8.0,20,False,2016-07-27 14:55:01.000,0.3.2,4.0,geoplotlib,conda-forge/geoplotlib,,,,711.0,183.0,181.0,https://pypi.org/project/geoplotlib,2016-07-27 14:55:01.000,2.0,480.0,https://anaconda.org/conda-forge/geoplotlib,2023-06-16 19:26:09.140,9262.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +741,TensorNets,taehoonlee/tensornets,tensorflow-utils,,https://github.com/taehoonlee/tensornets,https://github.com/taehoonlee/tensornets,MIT,2017-09-19 05:19:01.000,2021-01-02 06:28:10.000000,2021-01-02 06:26:24,284.0,,183.0,52.0,12.0,16.0,42.0,1003.0,High level network definitions with pre-trained weights in TensorFlow.,6.0,20,False,2020-03-31 04:38:27.000,0.4.6,12.0,tensornets,,,['tensorflow'],,91.0,87.0,83.0,https://pypi.org/project/tensornets,2020-03-31 04:35:15.000,4.0,91.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +742,nude.py,hhatto/nude.py,image,,https://github.com/hhatto/nude.py,https://github.com/hhatto/nude.py,MIT,2013-06-09 06:55:55.000,2020-11-23 13:49:32.000000,2020-11-23 13:49:02,79.0,,130.0,36.0,16.0,9.0,4.0,921.0,Nudity detection with Python.,12.0,20,False,2020-11-23 13:49:17.000,0.5.1,10.0,nudepy,,,,,610.0,3640.0,3635.0,https://pypi.org/project/nudepy,2020-11-23 13:49:17.000,5.0,610.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +743,evojax,google/evojax,jax-utils,,https://github.com/google/evojax,https://github.com/google/evojax,Apache-2.0,2021-12-07 00:30:07.000,2024-06-27 07:32:19.000000,2024-06-27 07:26:43,298.0,4.0,77.0,23.0,47.0,16.0,17.0,826.0,EvoJAX: Hardware-accelerated Neuroevolution.,14.0,20,True,2024-06-18 06:17:13.000,0.2.17,23.0,evojax,conda-forge/evojax,,['jax'],,1964.0,31.0,25.0,https://pypi.org/project/evojax,2024-06-18 06:17:13.000,6.0,1043.0,https://anaconda.org/conda-forge/evojax,2024-06-18 11:07:15.191,28579.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +744,sklearn-deap,rsteca/sklearn-deap,hyperopt,,https://github.com/rsteca/sklearn-deap,https://github.com/rsteca/sklearn-deap,MIT,2015-10-28 22:52:34.000,2024-02-10 07:16:54.000000,2021-07-30 15:06:27,104.0,,126.0,30.0,29.0,21.0,34.0,772.0,Use evolutionary algorithms instead of gridsearch in scikit-learn.,23.0,20,False,2021-07-30 15:13:54.000,0.3.0,14.0,sklearn-deap,,,['sklearn'],,747.0,46.0,46.0,https://pypi.org/project/sklearn-deap,2021-07-30 15:13:54.000,,747.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +745,NearPy,pixelogik/NearPy,nn-search,,https://github.com/pixelogik/NearPy,https://github.com/pixelogik/NearPy,MIT,2013-04-25 09:10:26.000,2023-02-23 15:20:18.000000,2023-01-22 20:07:16,161.0,,146.0,36.0,33.0,26.0,39.0,761.0,"Python framework for fast (approximated) nearest neighbour search in large, high-dimensional data sets using different..",20.0,20,False,2016-09-27 13:04:44.000,1.0.0,8.0,NearPy,,,,,696.0,113.0,113.0,https://pypi.org/project/NearPy,2016-09-27 13:03:12.000,,696.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +746,Merlin,NVIDIA-Merlin/Merlin,gpu-utilities,,https://github.com/NVIDIA-Merlin/Merlin,https://github.com/NVIDIA-Merlin/Merlin,Apache-2.0,2021-03-30 23:35:26.000,2024-07-28 01:04:48.000000,2024-07-22 10:16:42,493.0,2.0,112.0,34.0,561.0,211.0,246.0,743.0,"NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems, from feature..",32.0,20,True,2024-06-14 12:19:07.000,24.06.00,16.0,merlin-core,,,,,8082.0,1.0,,https://pypi.org/project/merlin-core,2023-08-29 16:27:32.000,1.0,8082.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +747,matrixprofile-ts,target/matrixprofile-ts,time-series-data,,https://github.com/target/matrixprofile-ts,https://github.com/target/matrixprofile-ts,Apache-2.0,2018-09-10 19:03:34.000,2024-07-16 19:49:29.000000,2020-04-25 18:37:42,198.0,,102.0,26.0,49.0,15.0,54.0,732.0,A Python library for detecting patterns and anomalies in massive datasets using the Matrix Profile.,15.0,20,False,2019-08-08 01:24:38.000,0.0.9,9.0,matrixprofile-ts,,,,,447.0,29.0,27.0,https://pypi.org/project/matrixprofile-ts,2019-08-08 01:24:38.000,2.0,447.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +748,dabl,amueller/dabl,sklearn-utils,,https://github.com/amueller/dabl,https://github.com/amueller/dabl,BSD-3-Clause,2020-01-30 18:26:49.000,2024-08-07 20:31:21.000000,2024-01-09 18:05:38,305.0,,106.0,5.0,3.0,1.0,,722.0,Data Analysis Baseline Library.,24.0,20,True,2024-08-07 20:31:21.000,0.3.1,19.0,dabl,,,['sklearn'],,4727.0,3.0,,https://pypi.org/project/dabl,2024-08-07 20:31:21.000,3.0,4727.0,,,,3.0,,,,,,5.0,,,,,,,,,,,,,,,,,,, +749,Auto TS,AutoViML/Auto_TS,time-series-data,,https://github.com/AutoViML/Auto_TS,https://github.com/AutoViML/Auto_TS,Apache-2.0,2020-02-15 15:23:32.000,2024-08-20 13:45:17.000000,2024-05-05 11:51:05,300.0,,113.0,18.0,26.0,1.0,87.0,721.0,"Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of..",13.0,20,True,2024-05-05 11:51:57.000,0.0.92,39.0,auto-ts,,,,,8724.0,,,https://pypi.org/project/auto-ts,2024-05-05 11:51:57.000,,8724.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +750,tcav,tensorflow/tcav,interpretability,,https://github.com/tensorflow/tcav,https://github.com/tensorflow/tcav,Apache-2.0,2018-07-03 17:45:35.000,2024-07-30 21:34:45.000000,2021-09-16 17:56:31,171.0,,144.0,34.0,84.0,16.0,55.0,627.0,Code for the TCAV ML interpretability project.,19.0,20,False,2021-02-23 16:17:42.000,0.2.2,4.0,tcav,,,['tensorflow'],,218.0,26.0,23.0,https://pypi.org/project/tcav,2021-02-23 16:17:42.000,3.0,218.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +751,PyWaffle,gyli/PyWaffle,data-viz,,https://github.com/gyli/PyWaffle,https://github.com/gyli/PyWaffle,MIT,2017-11-14 20:03:47.000,2024-06-16 04:23:17.000000,2024-06-16 04:23:17,307.0,2.0,105.0,9.0,15.0,6.0,16.0,579.0,Make Waffle Charts in Python.,6.0,20,True,2024-06-16 04:18:08.000,1.1.1,28.0,pywaffle,conda-forge/pywaffle,,,,5745.0,404.0,398.0,https://pypi.org/project/pywaffle,2024-06-16 04:18:08.000,6.0,5556.0,https://anaconda.org/conda-forge/pywaffle,2023-06-16 16:12:33.889,13067.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +752,seglearn,dmbee/seglearn,time-series-data,,https://github.com/dmbee/seglearn,https://github.com/dmbee/seglearn,BSD-3-Clause,2018-03-05 20:53:59.000,2022-08-27 09:01:18.000000,2022-08-27 09:00:35,283.0,,64.0,27.0,31.0,5.0,24.0,570.0,Python module for machine learning time series:.,14.0,20,False,2022-08-27 09:04:02.113,1.2.5,24.0,seglearn,,,,,1057.0,52.0,50.0,https://pypi.org/project/seglearn,2021-03-13 16:18:30.000,2.0,1057.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +753,N2,kakao/n2,nn-search,,https://github.com/kakao/n2,https://github.com/kakao/n2,Apache-2.0,2017-11-23 02:27:59.000,2023-06-27 16:54:16.000000,2023-06-27 16:54:13,266.0,,75.0,39.0,17.0,13.0,22.0,565.0,TOROS N2 - lightweight approximate Nearest Neighbor library which runs fast even with large datasets.,22.0,20,False,2020-10-16 03:43:47.000,0.1.7,9.0,n2,,,,,182.0,37.0,33.0,https://pypi.org/project/n2,2020-10-16 03:10:01.000,4.0,182.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +754,deepsnap,snap-stanford/deepsnap,graph,,https://github.com/snap-stanford/deepsnap,https://github.com/snap-stanford/deepsnap,MIT,2020-06-06 21:17:38.000,2023-11-11 03:23:44.000000,2023-11-11 03:23:44,413.0,,57.0,60.0,9.0,25.0,25.0,541.0,Python library assists deep learning on graphs.,18.0,20,True,2021-09-05 23:08:21.000,0.2.1,5.0,deepsnap,,,,12.0,527.0,111.0,109.0,https://pypi.org/project/deepsnap,2021-09-05 22:57:16.000,2.0,527.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +755,Popmon,ing-bank/popmon,data-viz,,https://github.com/ing-bank/popmon,https://github.com/ing-bank/popmon,MIT,2020-04-23 11:21:14.000,2024-06-28 04:46:54.000000,2023-07-18 10:24:07,542.0,,35.0,14.0,224.0,15.0,40.0,493.0,Monitor the stability of a Pandas or Spark dataframe.,17.0,20,False,2023-07-18 10:32:00.587,1.4.6,36.0,popmon,,,"['pandas', 'spark']",197.0,36392.0,23.0,21.0,https://pypi.org/project/popmon,2023-07-18 10:32:00.587,2.0,36389.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +756,rrcf,kLabUM/rrcf,others,,https://github.com/kLabUM/rrcf,https://github.com/kLabUM/rrcf,MIT,2018-10-20 05:39:05.000,2024-02-24 12:21:01.000000,2023-08-12 16:28:59,266.0,,108.0,20.0,57.0,26.0,21.0,492.0,Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams.,7.0,20,False,2023-04-30 02:25:49.592,0.4.4,8.0,rrcf,,,,,2889.0,76.0,68.0,https://pypi.org/project/rrcf,2023-04-30 02:25:49.592,8.0,2889.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +757,pymdp,infer-actively/pymdp,others,,https://github.com/infer-actively/pymdp,https://github.com/infer-actively/pymdp,MIT,2019-11-27 19:03:35.000,2024-09-02 10:07:56.000000,2024-07-16 08:32:27,987.0,30.0,80.0,30.0,95.0,15.0,27.0,433.0,A Python implementation of active inference for Markov Decision Processes.,18.0,20,True,2023-03-25 17:58:52.000,0.0.7.1,8.0,inferactively-pymdp,,,,,242.0,12.0,12.0,https://pypi.org/project/inferactively-pymdp,2022-12-08 15:25:01.498,,242.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +758,animatplot,t-makaro/animatplot,data-viz,,https://github.com/t-makaro/animatplot,https://github.com/t-makaro/animatplot,MIT,2017-04-03 00:54:04.000,2024-09-01 04:12:59.669000,2024-08-29 18:18:33,183.0,5.0,38.0,9.0,32.0,17.0,20.0,409.0,A python package for animating plots build on matplotlib.,7.0,20,True,2024-08-29 18:26:55.000,0.4.3,11.0,animatplot,conda-forge/animatplot,,,,599.0,63.0,59.0,https://pypi.org/project/animatplot,2024-08-29 17:08:23.000,4.0,297.0,https://anaconda.org/conda-forge/animatplot,2024-09-01 04:12:59.669,14231.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +759,fairness-indicators,tensorflow/fairness-indicators,interpretability,,https://github.com/tensorflow/fairness-indicators,https://github.com/tensorflow/fairness-indicators,Apache-2.0,2019-09-30 22:56:45.000,2024-08-28 17:11:07.000000,2024-04-26 20:31:49,327.0,,78.0,25.0,345.0,26.0,10.0,341.0,Tensorflows Fairness Evaluation and Visualization Toolkit.,36.0,20,True,2024-04-26 21:27:16.000,0.46.0,31.0,fairness-indicators,,,"['tensorflow', 'jupyter']",,1120.0,,,https://pypi.org/project/fairness-indicators,2024-04-26 21:27:16.000,,1120.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +760,ivis,beringresearch/ivis,data-viz,,https://github.com/beringresearch/ivis,https://github.com/beringresearch/ivis,Apache-2.0,2018-08-13 08:31:01.000,2024-06-13 05:29:40.000000,2024-06-13 05:28:48,643.0,9.0,43.0,13.0,63.0,3.0,57.0,327.0,Dimensionality reduction in very large datasets using Siamese Networks.,10.0,20,True,2024-06-13 05:28:35.000,2.0.11,36.0,ivis,,,['tensorflow'],,1411.0,37.0,35.0,https://pypi.org/project/ivis,2024-06-13 05:28:35.000,2.0,1411.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +761,MXBoard,awslabs/mxboard,ml-experiments,,https://github.com/awslabs/mxboard,https://github.com/awslabs/mxboard,Apache-2.0,2018-02-06 23:03:51.000,2021-11-30 10:46:24.000000,2020-01-24 23:21:55,42.0,,52.0,25.0,19.0,15.0,17.0,324.0,Logging MXNet data for visualization in TensorBoard.,9.0,20,False,2018-05-22 20:25:51.000,0.1.0,12.0,mxboard,,,['mxnet'],,2489.0,253.0,253.0,https://pypi.org/project/mxboard,2018-05-22 20:25:51.000,,2489.0,,,,3.0,,,,,,4.0,,,,,,,,,,,,,,,,,,, +762,vegafusion,vegafusion/vegafusion,data-viz,,https://github.com/vega/vegafusion,https://github.com/vega/vegafusion,BSD-3-Clause,2021-10-01 09:19:27.000,2024-08-15 00:23:47.000000,2024-08-14 15:39:49,663.0,2.0,18.0,24.0,353.0,47.0,87.0,316.0,Serverside scaling for Vega and Altair visualizations.,4.0,20,True,2024-05-09 19:19:11.000,1.6.9,75.0,vegafusion-jupyter,conda-forge/vegafusion-python-embed,,,5846.0,8518.0,5.0,,https://pypi.org/project/vegafusion-jupyter,2024-05-09 19:01:07.000,2.0,926.0,https://anaconda.org/conda-forge/vegafusion-python-embed,2024-05-10 13:02:13.580,218096.0,3.0,,,,,,,,vega/vegafusion,vegafusion-jupyter,https://www.npmjs.com/package/vegafusion-jupyter,2024-05-09 19:11:31.675,3.0,141.0,,,,,,,,,,,, +763,textpipe,textpipe/textpipe,nlp,,https://github.com/textpipe/textpipe,https://github.com/textpipe/textpipe,MIT,2018-06-21 16:23:32.000,2021-06-09 11:55:53.000000,2021-06-09 11:55:53,371.0,,26.0,22.0,239.0,24.0,25.0,300.0,Textpipe: clean and extract metadata from text.,29.0,20,False,2021-01-25 14:05:21.000,0.12.2,39.0,textpipe,,,,,399.0,10.0,9.0,https://pypi.org/project/textpipe,2021-01-25 14:05:21.000,1.0,399.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +764,somoclu,peterwittek/somoclu,distributed-ml,,https://github.com/peterwittek/somoclu,https://github.com/peterwittek/somoclu,MIT,2013-01-16 06:33:16.000,2024-05-21 04:33:27.096000,2024-01-18 11:58:51,626.0,,67.0,28.0,31.0,32.0,113.0,265.0,"Massively parallel self-organizing maps: accelerate training on multicore CPUs, GPUs, and clusters.",20.0,20,False,2023-02-18 02:51:08.166,1.7.6,18.0,somoclu,conda-forge/somoclu,,,1999.0,3535.0,18.0,,https://pypi.org/project/somoclu,2023-02-18 02:51:08.166,18.0,1092.0,https://anaconda.org/conda-forge/somoclu,2024-05-21 04:33:27.096,114045.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +765,solt,Oulu-IMEDS/solt,image,,https://github.com/Oulu-IMEDS/solt,https://github.com/Oulu-IMEDS/solt,MIT,2018-08-02 15:09:05.000,2024-07-25 10:53:20.000000,2024-06-22 08:32:56,378.0,11.0,19.0,6.0,33.0,20.0,39.0,263.0,Streaming over lightweight data transformations.,6.0,20,False,2020-03-10 14:09:31.000,0.1.9,18.0,solt,,,,,320.0,60.0,57.0,https://pypi.org/project/solt,2020-03-10 14:09:31.000,3.0,320.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +766,Funsor,pyro-ppl/funsor,probabilistics,,https://github.com/pyro-ppl/funsor,https://github.com/pyro-ppl/funsor,Apache-2.0,2019-01-30 23:13:39.000,2023-08-31 18:37:21.000000,2023-08-31 18:34:42,577.0,,21.0,18.0,464.0,90.0,76.0,234.0,Functional tensors for probabilistic programming.,11.0,20,False,2023-08-31 18:37:22.000,0.4.6,12.0,funsor,,,['pytorch'],,5336.0,81.0,71.0,https://pypi.org/project/funsor,2023-01-23 08:32:39.757,10.0,5336.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +767,pyfasttext,vrasneur/pyfasttext,nlp,,https://github.com/vrasneur/pyfasttext,https://github.com/vrasneur/pyfasttext,GPL-3.0,2017-06-30 18:44:42.000,2018-12-08 15:32:09.000000,2018-12-08 15:02:12,153.0,,31.0,9.0,4.0,20.0,29.0,227.0,Yet another Python binding for fastText.,4.0,20,False,2018-12-08 15:32:09.000,0.4.6,13.0,pyfasttext,,,,401.0,1121.0,444.0,442.0,https://pypi.org/project/pyfasttext,2018-12-08 15:32:09.000,2.0,1117.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +768,pytorchviz,szagoruyko/pytorchviz,pytorch-utils,,https://github.com/szagoruyko/pytorchviz,https://github.com/szagoruyko/pytorchviz,MIT,2018-01-30 15:37:55.000,2024-04-02 17:52:52.000000,2021-06-15 18:41:51,22.0,,279.0,31.0,22.0,34.0,37.0,3160.0,A small package to create visualizations of PyTorch execution graphs.,6.0,19,False,,,,,,,,,,2106.0,2106.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +769,AdvBox,advboxes/AdvBox,adversarial,,https://github.com/advboxes/AdvBox,https://github.com/advboxes/AdvBox,Apache-2.0,2018-08-08 08:55:41.000,2023-02-15 19:57:27.000000,2022-08-08 02:56:23,378.0,,254.0,56.0,65.0,8.0,31.0,1378.0,Advbox is a toolbox to generate adversarial examples that fool neural networks in..,19.0,19,False,2018-12-05 02:48:50.000,0.4.1,2.0,advbox,,,,,59.0,3.0,3.0,https://pypi.org/project/advbox,2018-12-05 02:48:50.000,,59.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +770,Torch-Struct,harvardnlp/pytorch-struct,pytorch-utils,,https://github.com/harvardnlp/pytorch-struct,https://github.com/harvardnlp/pytorch-struct,MIT,2019-08-26 19:34:30.000,2022-04-20 08:21:20.000000,2022-01-30 19:49:08,271.0,,93.0,33.0,72.0,31.0,30.0,1105.0,"Fast, general, and tested differentiable structured prediction in PyTorch.",16.0,19,False,2021-02-15 20:20:59.000,0.5,2.0,torch-struct,,,['pytorch'],,17328.0,2.0,,https://pypi.org/project/torch-struct,2021-02-14 02:43:46.000,2.0,17328.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +771,Performer Pytorch,lucidrains/performer-pytorch,pytorch-utils,,https://github.com/lucidrains/performer-pytorch,https://github.com/lucidrains/performer-pytorch,MIT,2020-10-03 03:41:36.000,2022-02-02 20:34:04.000000,2022-02-02 20:33:18,124.0,,138.0,17.0,11.0,42.0,43.0,1079.0,"An implementation of Performer, a linear attention-based transformer, in Pytorch.",6.0,19,False,2022-02-02 20:34:04.000,1.1.4,80.0,performer-pytorch,,,['pytorch'],,3865.0,153.0,148.0,https://pypi.org/project/performer-pytorch,2022-02-02 20:34:04.000,5.0,3865.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +772,pytorch2keras,gmalivenko/pytorch2keras,model-serialisation,,https://github.com/gmalivenko/pytorch2keras,https://github.com/gmalivenko/pytorch2keras,MIT,2017-11-16 20:21:43.000,2022-12-08 11:42:52.000000,2021-08-06 08:18:46,282.0,,141.0,14.0,24.0,58.0,69.0,857.0,PyTorch to Keras model convertor.,13.0,19,False,2020-05-14 10:03:56.000,0.2.4,23.0,pytorch2keras,,,,,277.0,102.0,101.0,https://pypi.org/project/pytorch2keras,2020-05-14 10:03:56.000,1.0,277.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +773,Dragonfly,dragonfly/dragonfly,hyperopt,,https://github.com/dragonfly/dragonfly,https://github.com/dragonfly/dragonfly,MIT,2018-04-20 22:19:50.000,2023-06-19 20:23:17.000000,2022-10-01 22:21:50,400.0,,230.0,29.0,38.0,43.0,21.0,849.0,An open source python library for scalable Bayesian optimisation.,13.0,19,False,2022-10-01 22:28:00.848,0.1.7,10.0,dragonfly-opt,,,,,2088.0,,,https://pypi.org/project/dragonfly-opt,2022-10-01 22:28:00.848,,2088.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +774,tffm,geffy/tffm,tensorflow-utils,,https://github.com/geffy/tffm,https://github.com/geffy/tffm,MIT,2016-05-02 17:06:07.000,2022-01-17 20:39:04.000000,2022-01-17 20:38:58,107.0,,175.0,33.0,15.0,19.0,22.0,780.0,TensorFlow implementation of an arbitrary order Factorization Machine.,11.0,19,False,2022-01-17 20:35:57.000,1.0.2,3.0,tffm,,,['tensorflow'],,211.0,14.0,14.0,https://pypi.org/project/tffm,2022-01-17 20:35:57.000,,211.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +775,opytimizer,gugarosa/opytimizer,hyperopt,,https://github.com/gugarosa/opytimizer,https://github.com/gugarosa/opytimizer,Apache-2.0,2017-11-01 16:04:01.000,2024-08-18 17:19:42.000000,2024-08-18 17:07:49,821.0,2.0,40.0,15.0,18.0,1.0,22.0,599.0,Opytimizer is a Python library consisting of meta-heuristic optimization algorithms.,4.0,19,True,2024-08-18 17:19:42.000,3.1.4,28.0,opytimizer,,,,,626.0,17.0,17.0,https://pypi.org/project/opytimizer,2024-08-18 17:19:42.000,,626.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +776,recmetrics,statisticianinstilettos/recmetrics,recommender-systems,,https://github.com/statisticianinstilettos/recmetrics,https://github.com/statisticianinstilettos/recmetrics,MIT,2018-10-15 15:29:49.000,2024-01-11 20:34:53.000000,2023-10-04 12:31:54,297.0,,97.0,15.0,53.0,13.0,16.0,561.0,A library of metrics for evaluating recommender systems.,20.0,19,True,2022-04-26 18:03:18.000,0.1.5,20.0,recmetrics,,,,7.0,4090.0,56.0,56.0,https://pypi.org/project/recmetrics,2022-04-26 17:57:01.000,,4090.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +777,fastT5,Ki6an/fastT5,nlp,,https://github.com/Ki6an/fastT5,https://github.com/Ki6an/fastT5,Apache-2.0,2021-03-11 08:46:42.000,2023-04-24 18:46:40.000000,2022-04-05 03:21:24,38.0,,71.0,13.0,10.0,24.0,41.0,557.0,boost inference speed of T5 models by 5x & reduce the model size by 3x.,5.0,19,False,2022-04-05 03:23:12.000,0.1.4,14.0,fastt5,,,,,1236.0,51.0,51.0,https://pypi.org/project/fastt5,2022-04-05 03:23:12.000,,1236.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +778,scikit-tda,scikit-tda/scikit-tda,sklearn-utils,,https://github.com/scikit-tda/scikit-tda,https://github.com/scikit-tda/scikit-tda,MIT,2018-04-13 21:00:31.000,2024-07-19 18:49:00.000000,2024-07-19 16:10:42,70.0,1.0,54.0,18.0,10.0,4.0,18.0,518.0,Topological Data Analysis for Python.,6.0,19,True,2024-07-19 18:49:00.000,1.1.1,6.0,scikit-tda,,,['sklearn'],,1138.0,60.0,60.0,https://pypi.org/project/scikit-tda,2024-07-19 18:49:00.000,,1138.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +779,elegy,poets-ai/elegy,ml-frameworks,,https://github.com/poets-ai/elegy,https://github.com/poets-ai/elegy,MIT,2020-06-30 14:00:37.000,2022-12-15 19:23:10.000000,2022-05-23 17:26:29,339.0,,32.0,16.0,148.0,40.0,66.0,468.0,A High Level API for Deep Learning in JAX.,18.0,19,False,2022-03-23 21:51:07.000,0.8.6,33.0,elegy,,,"['tensorflow', 'jax']",,366.0,52.0,52.0,https://pypi.org/project/elegy,2022-04-22 15:42:03.000,,366.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +780,pykale,pykale/pykale,others,,https://github.com/pykale/pykale,https://github.com/pykale/pykale,MIT,2020-06-30 08:06:10.000,2024-09-04 12:31:15.000000,2024-07-27 08:09:44,3033.0,8.0,63.0,11.0,266.0,11.0,110.0,435.0,Knowledge-Aware machine LEarning (KALE): accessible machine learning from multiple sources for interdisciplinary..,24.0,19,True,2023-07-13 11:41:03.541,0.1.2,12.0,pykale,,,['pytorch'],,131.0,3.0,3.0,https://pypi.org/project/pykale,2022-04-12 08:56:50.000,,131.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +781,model-card-toolkit,tensorflow/model-card-toolkit,interpretability,,https://github.com/tensorflow/model-card-toolkit,https://github.com/tensorflow/model-card-toolkit,Apache-2.0,2020-07-24 16:48:58.000,2023-07-26 12:05:00.000000,2023-07-26 12:04:59,273.0,,83.0,20.0,247.0,10.0,23.0,418.0,A toolkit that streamlines and automates the generation of model cards.,22.0,19,False,2023-04-03 18:05:05.715,2.0.0,12.0,model-card-toolkit,,,,24.0,1004.0,25.0,24.0,https://pypi.org/project/model-card-toolkit,2022-04-28 16:34:21.000,1.0,1004.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +782,scikit-rebate,EpistasisLab/scikit-rebate,others,,https://github.com/EpistasisLab/scikit-rebate,https://github.com/EpistasisLab/scikit-rebate,MIT,2016-09-19 13:36:17.000,2023-06-16 16:08:23.527000,2021-02-15 17:10:59,283.0,,72.0,24.0,48.0,18.0,19.0,405.0,"A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for..",14.0,19,False,2017-04-12 16:12:01.000,0.3.4,13.0,skrebate,conda-forge/skrebate,,['sklearn'],,5566.0,28.0,,https://pypi.org/project/skrebate,2021-03-20 17:11:52.000,28.0,5138.0,https://anaconda.org/conda-forge/skrebate,2023-06-16 16:08:23.527,34242.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +783,DeepGraph,deepgraph/deepgraph,graph,,https://github.com/deepgraph/deepgraph,https://github.com/deepgraph/deepgraph,BSD-3-Clause,2015-10-27 12:28:45.000,2024-09-03 22:45:13.000000,2024-03-27 08:46:27,190.0,,41.0,19.0,4.0,10.0,8.0,283.0,Analyze Data with Pandas-based Networks. Documentation:.,3.0,19,False,2024-03-27 10:16:33.000,0.2.4,14.0,deepgraph,conda-forge/deepgraph,,['pandas'],,5146.0,10.0,10.0,https://pypi.org/project/deepgraph,2024-03-27 10:16:33.000,,586.0,https://anaconda.org/conda-forge/deepgraph,2024-07-11 16:39:33.824,214359.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +784,PipelineDP,OpenMined/PipelineDP,privacy-ml,,https://github.com/OpenMined/PipelineDP,https://github.com/OpenMined/PipelineDP,Apache-2.0,2021-02-10 18:04:22.000,2024-08-02 14:28:42.000000,2024-08-02 14:28:42,423.0,1.0,76.0,21.0,441.0,27.0,51.0,271.0,PipelineDP is a Python framework for applying differentially private aggregations to large datasets using batch..,32.0,19,False,2023-10-25 10:51:36.000,0.2.1,23.0,pipeline-dp,,,,,234.0,3.0,3.0,https://pypi.org/project/pipeline-dp,2023-11-22 19:01:05.000,,234.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +785,numerizer,jaidevd/numerizer,nlp,,https://github.com/jaidevd/numerizer,https://github.com/jaidevd/numerizer,MIT,2019-12-02 07:00:34.000,2023-05-01 07:53:03.000000,2023-05-01 07:50:02,24.0,,23.0,8.0,11.0,5.0,9.0,212.0,A Python module to convert natural language numerics into ints and floats.,4.0,19,False,2023-05-01 07:55:52.405,0.2.3,11.0,numerizer,,,,,15952.0,91.0,89.0,https://pypi.org/project/numerizer,2023-01-03 08:08:01.830,2.0,15952.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +786,celer,mathurinm/celer,sklearn-utils,,https://github.com/mathurinm/celer,https://github.com/mathurinm/celer,BSD-3-Clause,2018-02-20 19:37:31.000,2024-08-01 08:27:07.000000,2024-08-01 08:10:33,265.0,3.0,33.0,11.0,202.0,21.0,76.0,198.0,"Fast solver for L1-type problems: Lasso, sparse Logisitic regression, Group Lasso, weighted Lasso, Multitask Lasso, etc.",13.0,19,False,2023-07-26 15:36:39.000,0.7.3,15.0,celer,,,['sklearn'],,618.0,40.0,39.0,https://pypi.org/project/celer,2023-07-26 15:36:39.000,1.0,618.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +787,SerpentAI,SerpentAI/SerpentAI,reinforcement-learning,,https://github.com/SerpentAI/SerpentAI,https://github.com/SerpentAI/SerpentAI,MIT,2017-04-16 21:48:39.000,2022-11-07 01:59:31.000000,2020-05-22 22:34:09,250.0,,765.0,338.0,58.0,2.0,,6744.0,Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!.,7.0,18,False,2018-02-17 00:12:46.000,2018.1.2,18.0,SerpentAI,,,,359.0,88.0,,,https://pypi.org/project/SerpentAI,2018-02-17 00:12:46.000,,82.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +788,mesh-transformer-jax,kingoflolz/mesh-transformer-jax,distributed-ml,,https://github.com/kingoflolz/mesh-transformer-jax,https://github.com/kingoflolz/mesh-transformer-jax,Apache-2.0,2021-03-13 23:31:13.000,2023-01-21 00:09:29.000000,2023-01-12 19:54:10,143.0,,891.0,112.0,51.0,46.0,160.0,6269.0,Model parallel transformers in JAX and Haiku.,23.0,18,False,,,,,,,['jax'],,,20.0,20.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +789,scenic,google-research/scenic,image,,https://github.com/google-research/scenic,https://github.com/google-research/scenic,Apache-2.0,2021-07-12 14:27:08.000,2024-08-28 18:43:26.000000,2024-08-28 18:43:21,703.0,10.0,423.0,39.0,851.0,149.0,118.0,3229.0,Scenic: A Jax Library for Computer Vision Research and Beyond.,84.0,18,True,,,,,,,['jax'],,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +790,Spotlight,maciejkula/spotlight,recommender-systems,,https://github.com/maciejkula/spotlight,https://github.com/maciejkula/spotlight,MIT,2017-06-25 18:52:19.000,2023-06-16 13:22:46.522000,2020-02-09 21:03:48,299.0,,413.0,106.0,83.0,67.0,48.0,2966.0,Deep recommender models using PyTorch.,11.0,18,False,2019-09-08 10:19:53.000,0.1.6,7.0,,maciejkula/spotlight,,['pytorch'],,98.0,,,,,,,https://anaconda.org/maciejkula/spotlight,2023-06-16 13:22:46.522,8603.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +791,GraphGym,snap-stanford/GraphGym,graph,,https://github.com/snap-stanford/GraphGym,https://github.com/snap-stanford/GraphGym,MIT,2020-10-14 05:01:35.000,2023-11-10 05:37:18.000000,2023-03-14 23:02:49,75.0,,176.0,23.0,20.0,18.0,30.0,1671.0,Platform for designing and evaluating Graph Neural Networks (GNN).,6.0,18,False,2022-03-24 23:28:17.000,0.4.0,3.0,graphgym,,,,40.0,116.0,7.0,7.0,https://pypi.org/project/graphgym,2022-03-24 23:19:13.000,,115.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +792,keepsake,replicate/keepsake,ml-experiments,,https://github.com/replicate/keepsake,https://github.com/replicate/keepsake,Apache-2.0,2020-07-01 04:37:44.000,2024-08-12 14:02:24.000000,2022-05-24 23:48:09,791.0,,71.0,26.0,1005.0,127.0,65.0,1647.0,Version control for machine learning.,17.0,18,False,2021-03-11 21:15:01.000,0.4.2,7.0,keepsake,,,,,117.0,1.0,,https://pypi.org/project/keepsake,2021-01-25 21:51:16.000,1.0,117.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +793,Xcessiv,reiinakano/xcessiv,hyperopt,,https://github.com/reiinakano/xcessiv,https://github.com/reiinakano/xcessiv,Apache-2.0,2017-03-07 18:18:25.000,2018-06-06 22:23:37.000000,2017-08-21 00:51:15,316.0,,109.0,55.0,34.0,22.0,13.0,1266.0,"A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python.",6.0,18,False,2017-08-21 00:53:25.000,0.5.1,34.0,xcessiv,,,,,192.0,3.0,2.0,https://pypi.org/project/xcessiv,2017-08-21 00:49:41.000,1.0,192.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +794,XAI,EthicalML/xai,interpretability,,https://github.com/EthicalML/xai,https://github.com/EthicalML/xai,MIT,2019-01-11 20:00:09.000,2021-10-30 06:35:19.000000,2021-10-30 06:30:12,91.0,,163.0,43.0,5.0,4.0,7.0,1095.0,XAI - An eXplainability toolbox for machine learning.,3.0,18,False,2021-10-30 06:35:19.000,0.1.0,6.0,xai,,,,,326.0,31.0,31.0,https://pypi.org/project/xai,2021-10-30 06:33:26.000,,326.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +795,UForm,unum-cloud/uform,nlp,,https://github.com/unum-cloud/uform,https://github.com/unum-cloud/uform,Apache-2.0,2023-02-21 10:04:40.000,2024-05-29 14:46:40.000000,2024-04-25 03:40:02,286.0,,60.0,15.0,60.0,8.0,21.0,1011.0,"Pocket-Sized Multimodal AI for content understanding and generation across multilingual texts, images, and video, up..",14.0,18,True,2024-04-25 03:41:41.000,3.0.2,34.0,uform,,,['pytorch'],381.0,961.0,7.0,6.0,https://pypi.org/project/uform,2024-04-25 03:41:41.000,1.0,941.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +796,robustness,MadryLab/robustness,adversarial,,https://github.com/MadryLab/robustness,https://github.com/MadryLab/robustness,MIT,2019-08-21 09:26:33.000,2024-01-11 13:06:10.000000,2022-02-14 20:43:06,145.0,,179.0,18.0,42.0,23.0,60.0,903.0,"A library for experimenting with, training and evaluating neural networks, with a focus on adversarial robustness.",13.0,18,False,2020-12-01 06:11:12.000,1.2.1.post2,10.0,robustness,conda-forge/robustness,,,,516.0,190.0,187.0,https://pypi.org/project/robustness,2020-12-01 06:21:33.000,3.0,322.0,https://anaconda.org/conda-forge/robustness,2023-06-16 19:21:11.893,9545.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +797,LOFO,aerdem4/lofo-importance,interpretability,,https://github.com/aerdem4/lofo-importance,https://github.com/aerdem4/lofo-importance,MIT,2019-01-14 10:46:46.000,2024-01-16 09:19:50.000000,2024-01-16 09:12:58,32.0,,84.0,14.0,35.0,3.0,24.0,813.0,Leave One Feature Out Importance.,6.0,18,True,2024-01-16 09:19:50.000,0.3.4,14.0,lofo-importance,,,,,3207.0,37.0,33.0,https://pypi.org/project/lofo-importance,2024-01-16 09:19:50.000,4.0,3207.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +798,Tensor Sensor,parrt/tensor-sensor,pytorch-utils,,https://github.com/parrt/tensor-sensor,https://github.com/parrt/tensor-sensor,MIT,2020-08-28 22:54:04.000,2023-06-16 19:27:38.210000,2022-04-07 20:49:56,235.0,,36.0,12.0,13.0,8.0,16.0,768.0,"The goal of this library is to generate more helpful exception messages for matrix algebra expressions for numpy,..",4.0,18,False,2021-12-11 21:24:11.000,1.0,37.0,tensor-sensor,conda-forge/tensor-sensor,,['pytorch'],,2860.0,43.0,43.0,https://pypi.org/project/tensor-sensor,2021-12-11 21:24:35.000,,2763.0,https://anaconda.org/conda-forge/tensor-sensor,2023-06-16 19:27:38.210,3416.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +799,nboost,koursaros-ai/nboost,nlp,,https://github.com/koursaros-ai/nboost,https://github.com/koursaros-ai/nboost,Apache-2.0,2019-10-29 20:56:24.000,2020-09-30 14:51:16.000000,2020-07-16 19:48:25,1336.0,,65.0,17.0,21.0,29.0,50.0,675.0,"NBoost is a scalable, search-api-boosting platform for deploying transformer models to improve the relevance of search..",10.0,18,False,2020-06-12 20:05:15.000,0.3.9,26.0,nboost,,,,,528.0,4.0,4.0,https://pypi.org/project/nboost,2020-06-12 20:05:15.000,,528.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +800,baikal,alegonz/baikal,others,,https://github.com/alegonz/baikal,https://github.com/alegonz/baikal,BSD-3-Clause,2019-01-21 12:59:02.000,2023-10-01 08:59:57.840000,2021-04-11 07:50:00,405.0,,29.0,18.0,42.0,6.0,18.0,592.0,A graph-based functional API for building complex scikit-learn pipelines.,2.0,18,False,2020-11-15 13:40:18.000,0.4.2,15.0,baikal,conda-forge/cython-blis,,,,47256.0,14.0,13.0,https://pypi.org/project/baikal,2020-11-15 13:40:18.000,1.0,251.0,https://anaconda.org/conda-forge/cython-blis,2023-10-01 08:59:57.840,2256242.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +801,shap-hypetune,cerlymarco/shap-hypetune,hyperopt,,https://github.com/cerlymarco/shap-hypetune,https://github.com/cerlymarco/shap-hypetune,MIT,2021-05-16 09:30:03.000,2024-06-08 12:12:57.000000,2024-02-21 14:09:04,30.0,,70.0,7.0,6.0,4.0,32.0,558.0,A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.,3.0,18,True,2024-02-21 14:38:09.000,0.2.7,10.0,shap-hypetune,,,,,1377.0,21.0,19.0,https://pypi.org/project/shap-hypetune,2024-02-21 14:34:22.000,2.0,1377.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +802,Auto Tune Models,HDI-Project/ATM,hyperopt,,https://github.com/HDI-Project/ATM,https://github.com/HDI-Project/ATM,MIT,2016-10-14 18:03:00.000,2020-02-21 17:44:07.000000,2020-02-21 17:40:58,775.0,,140.0,56.0,72.0,18.0,71.0,524.0,"Auto Tune Models - A multi-tenant, multi-data system for automated machine learning (model selection and tuning).",17.0,18,False,2019-07-30 09:28:26.000,0.2.2,14.0,atm,,,,,148.0,21.0,21.0,https://pypi.org/project/atm,2019-07-30 09:25:11.000,,148.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +803,Quantus,understandable-machine-intelligence-lab/quantus,interpretability,,https://github.com/understandable-machine-intelligence-lab/Quantus,https://github.com/understandable-machine-intelligence-lab/Quantus,GPL-3.0,2021-03-18 15:04:58.000,2024-08-11 17:21:13.000000,2024-08-11 17:21:13,1772.0,1.0,74.0,9.0,218.0,49.0,81.0,524.0,Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations.,20.0,18,False,2023-12-05 11:42:47.000,0.5.3,27.0,quantus,,,,178.0,741.0,33.0,32.0,https://pypi.org/project/quantus,2023-12-05 11:42:47.000,1.0,736.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +804,Case Recommender,caserec/CaseRecommender,recommender-systems,,https://github.com/caserec/CaseRecommender,https://github.com/caserec/CaseRecommender,MIT,2015-11-12 18:25:39.000,2024-01-10 20:36:33.000000,2021-11-25 23:08:43,204.0,,92.0,22.0,19.0,6.0,20.0,478.0,Case Recommender: A Flexible and Extensible Python Framework for Recommender Systems.,11.0,18,False,2021-11-25 23:19:05.000,1.1.1,42.0,caserecommender,,,['sklearn'],,508.0,13.0,13.0,https://pypi.org/project/caserecommender,2021-11-25 23:19:05.000,,508.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +805,DESlib,scikit-learn-contrib/DESlib,sklearn-utils,,https://github.com/scikit-learn-contrib/DESlib,https://github.com/scikit-learn-contrib/DESlib,BSD-3-Clause,2017-12-08 22:49:49.000,2024-04-15 06:19:14.000000,2024-04-15 06:19:14,282.0,,105.0,13.0,130.0,18.0,138.0,477.0,A Python library for dynamic classifier and ensemble selection.,17.0,18,True,2024-04-12 03:07:31.000,0.3.7,6.0,deslib,,,['sklearn'],,745.0,3.0,,https://pypi.org/project/deslib,2024-04-12 03:07:31.000,3.0,745.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +806,Sematch,gsi-upm/sematch,graph,,https://github.com/gsi-upm/sematch,https://github.com/gsi-upm/sematch,Apache-2.0,2012-11-30 11:11:53.000,2023-11-07 11:11:44.000000,2023-11-07 11:10:46,137.0,,105.0,71.0,7.0,15.0,19.0,428.0,semantic similarity framework for knowledge graph.,10.0,18,True,2017-04-17 10:56:52.000,1.0.4,5.0,sematch,,,,,226.0,47.0,47.0,https://pypi.org/project/sematch,2017-04-17 10:56:52.000,,226.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +807,textaugment,dsfsi/textaugment,nlp,,https://github.com/dsfsi/textaugment,https://github.com/dsfsi/textaugment,MIT,2019-05-06 12:28:19.000,2024-02-20 11:57:52.000000,2023-11-17 08:50:12,72.0,,60.0,8.0,12.0,11.0,18.0,393.0,TextAugment: Text Augmentation Library.,8.0,18,True,2023-11-16 20:54:10.000,2.0.0,9.0,textaugment,,,,92.0,6058.0,126.0,122.0,https://pypi.org/project/textaugment,2023-11-16 20:49:04.000,4.0,6057.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +808,datmo,datmo/datmo,ml-experiments,,https://github.com/datmo/datmo,https://github.com/datmo/datmo,MIT,2017-11-03 05:46:43.000,2022-06-21 21:41:58.000000,2019-11-29 00:48:44,1051.0,,30.0,11.0,121.0,31.0,150.0,345.0,Open source production model management tool for data scientists.,6.0,18,False,2018-12-07 06:16:42.000,0.0.40,41.0,datmo,,,,,182.0,6.0,6.0,https://pypi.org/project/datmo,2018-12-07 06:16:42.000,,182.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +809,Camphr,PKSHATechnology-Research/camphr,nlp,,https://github.com/PKSHATechnology-Research/camphr,https://github.com/PKSHATechnology-Research/camphr,Apache-2.0,2020-02-10 03:39:58.000,2023-03-07 22:10:10.175000,2021-08-18 06:06:51,1404.0,,17.0,6.0,217.0,4.0,26.0,340.0,Camphr - NLP libary for creating pipeline components.,8.0,18,False,2023-03-07 22:10:10.175,0.8.9,49.0,camphr,,,['spacy'],,303.0,16.0,14.0,https://pypi.org/project/camphr,2023-03-07 22:10:10.175,2.0,303.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +810,Sherpa,sherpa-ai/sherpa,hyperopt,,https://github.com/sherpa-ai/sherpa,https://github.com/sherpa-ai/sherpa,GPL-3.0,2018-05-16 21:41:54.000,2020-10-18 07:57:50.000000,2020-10-18 07:57:48,823.0,,52.0,11.0,60.0,17.0,41.0,331.0,"Hyperparameter optimization that enables researchers to experiment, visualize, and scale quickly.",43.0,18,False,2020-07-31 05:29:09.000,1.0.7,8.0,parameter-sherpa,,,,,215.0,41.0,37.0,https://pypi.org/project/parameter-sherpa,2019-11-23 21:32:27.000,4.0,215.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +811,Brainiak,brainiak/brainiak,medical-data,,https://github.com/brainiak/brainiak,https://github.com/brainiak/brainiak,Apache-2.0,2016-02-08 23:19:27.000,2024-09-03 22:33:34.000000,2024-07-08 16:17:35,399.0,1.0,129.0,34.0,325.0,84.0,131.0,330.0,Brain Imaging Analysis Kit.,35.0,18,True,2019-08-27 23:52:29.000,0.9.1,15.0,brainiak,,,,,214.0,,,https://pypi.org/project/brainiak,2020-10-15 20:45:08.000,,197.0,,,,3.0,brainiak/brainiak,https://hub.docker.com/r/brainiak/brainiak,2020-10-15 21:11:03.379549,1.0,1844.0,,,,,,,,,,,,,,,,,,,, +812,bluefog,Bluefog-Lib/bluefog,distributed-ml,,https://github.com/Bluefog-Lib/bluefog,https://github.com/Bluefog-Lib/bluefog,Apache-2.0,2019-12-03 05:27:21.000,2024-07-25 10:59:34.000000,2023-03-28 03:38:13,1094.0,,69.0,28.0,59.0,30.0,32.0,291.0,Distributed and decentralized training framework for PyTorch over graph.,9.0,18,False,2021-05-15 01:39:45.000,0.3.0,10.0,bluefog,,,['pytorch'],181.0,83.0,4.0,4.0,https://pypi.org/project/bluefog,2021-05-15 01:39:45.000,,80.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +813,chitra,gradsflow/chitra,ml-experiments,,https://github.com/aniketmaurya/chitra,https://github.com/aniketmaurya/chitra,Apache-2.0,2020-01-23 14:17:54.000,2024-07-02 00:10:02.000000,2024-06-01 12:08:31,372.0,,37.0,6.0,134.0,,35.0,224.0,"A multi-functional library for full-stack Deep Learning. Simplifies Model Building, API development, and Model..",14.0,18,False,2021-11-26 17:10:22.000,0.2.0,38.0,chitra,conda-forge/chitra,,,,1987.0,1.0,,https://pypi.org/project/chitra,2022-01-09 08:50:45.005,1.0,1878.0,https://anaconda.org/conda-forge/chitra,2023-06-18 08:40:33.534,3495.0,3.0,,,,,,,,aniketmaurya/chitra,,,,,,,,,,,,,,,,, +814,DeepMind Lab,deepmind/lab,reinforcement-learning,,https://github.com/google-deepmind/lab,https://github.com/google-deepmind/lab,,2016-11-30 13:41:26.000,2023-01-04 15:38:37.000000,2023-01-04 15:19:06,509.0,,1348.0,466.0,21.0,59.0,167.0,7090.0,A customisable 3D platform for agent-based AI research.,9.0,17,False,2020-12-07 11:26:33.000,release-2020-12-07,8.0,,,,,,,,,,,,,,,,3.0,,,,,,,,google-deepmind/lab,,,,,,,,,,,,,,,,, +815,NeuroNER,Franck-Dernoncourt/NeuroNER,nlp,,https://github.com/Franck-Dernoncourt/NeuroNER,https://github.com/Franck-Dernoncourt/NeuroNER,MIT,2017-03-07 01:24:15.000,2023-03-24 22:29:09.000000,2019-10-02 23:26:11,132.0,,460.0,79.0,36.0,83.0,68.0,1688.0,Named-entity recognition using neural networks. Easy-to-use and state-of-the-art results.,7.0,17,False,2019-10-02 23:30:15.000,1.0.8,7.0,pyneuroner,,,,,142.0,,,https://pypi.org/project/pyneuroner,2019-10-02 23:30:15.000,,142.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +816,Advisor,tobegit3hub/advisor,hyperopt,,https://github.com/tobegit3hub/advisor,https://github.com/tobegit3hub/advisor,Apache-2.0,2017-09-14 03:50:33.000,2019-11-11 07:09:57.869705,2019-11-11 06:59:31,165.0,,254.0,52.0,13.0,20.0,13.0,1541.0,Open-source implementation of Google Vizier for hyper parameters tuning.,11.0,17,False,2018-10-18 02:54:09.000,0.1.6,4.0,advisor,,,,,89.0,,,https://pypi.org/project/advisor,2018-10-18 02:54:09.000,,69.0,,,,3.0,tobegit3hub/advisor,https://hub.docker.com/r/tobegit3hub/advisor,2019-11-11 07:09:57.869705,,1690.0,,,,,,,,,,,,,,,,,,,, +817,Tez,abhishekkrthakur/tez,pytorch-utils,,https://github.com/abhishekkrthakur/tez,https://github.com/abhishekkrthakur/tez,Apache-2.0,2020-11-13 10:19:22.000,2023-01-29 16:52:18.000000,2022-09-16 11:03:31,144.0,,144.0,17.0,11.0,25.0,18.0,1162.0,Tez is a super-simple and lightweight Trainer for PyTorch. It also comes with many utils that you can use to tackle..,2.0,17,False,2022-09-20 02:28:33.973,0.7.2,26.0,tez,,,['pytorch'],,291.0,58.0,56.0,https://pypi.org/project/tez,2022-09-20 02:28:33.973,2.0,291.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +818,parallelformers,tunib-ai/parallelformers,distributed-ml,,https://github.com/tunib-ai/parallelformers,https://github.com/tunib-ai/parallelformers,Apache-2.0,2021-07-17 12:50:43.000,2023-04-24 11:42:30.000000,2022-07-27 19:55:38,93.0,,57.0,15.0,10.0,26.0,17.0,776.0,Parallelformers: An Efficient Model Parallelization Toolkit for Deployment.,5.0,17,False,2022-07-27 19:52:00.185,1.2.7,19.0,parallelformers,,,,,400.0,51.0,51.0,https://pypi.org/project/parallelformers,2022-07-27 19:52:00.185,,400.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +819,Caer,jasmcaus/caer,image,,https://github.com/jasmcaus/caer,https://github.com/jasmcaus/caer,MIT,2020-08-06 18:36:14.000,2023-10-13 12:16:35.000000,2023-04-01 08:26:45,5080.0,,111.0,19.0,58.0,2.0,13.0,763.0,"A lightweight Computer Vision library. Scale your models, not boilerplate.",8.0,17,False,2021-10-13 21:04:12.000,2.0.8,119.0,caer,,https://caer.rtfd.io,,34.0,5209.0,2.0,,https://pypi.org/project/caer,2021-10-13 21:04:12.000,2.0,5209.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +820,HyperparameterHunter,HunterMcGushion/hyperparameter_hunter,hyperopt,,https://github.com/HunterMcGushion/hyperparameter_hunter,https://github.com/HunterMcGushion/hyperparameter_hunter,MIT,2018-06-01 23:17:00.000,2021-01-20 03:52:41.000000,2021-01-20 03:52:40,1096.0,,103.0,24.0,101.0,37.0,84.0,703.0,Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries.,4.0,17,False,2021-02-16 11:34:12.211,3.0.0,16.0,hyperparameter-hunter,,,,469.0,188.0,,,https://pypi.org/project/hyperparameter-hunter,2018-06-14 02:21:57.000,,182.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +821,ThunderGBM,Xtra-Computing/thundergbm,ml-frameworks,,https://github.com/Xtra-Computing/thundergbm,https://github.com/Xtra-Computing/thundergbm,Apache-2.0,2016-11-11 09:58:08.000,2024-01-29 12:26:32.000000,2024-01-29 12:26:25,611.0,,87.0,25.0,4.0,39.0,42.0,690.0,ThunderGBM: Fast GBDTs and Random Forests on GPUs.,12.0,17,True,2022-09-19 20:15:07.376,0.3.17,25.0,thundergbm,,,,,101.0,3.0,3.0,https://pypi.org/project/thundergbm,2022-09-19 20:15:07.376,,101.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +822,sklearn-evaluation,edublancas/sklearn-evaluation,interpretability,,https://github.com/edublancas/sklearn-evaluation,https://github.com/edublancas/sklearn-evaluation,MIT,2023-01-15 21:18:52.000,2024-02-08 01:27:56.000000,2023-01-13 21:57:34,832.0,,55.0,,,,,432.0,"Machine learning model evaluation made easy: plots, tables, HTML reports, experiment tracking and Jupyter notebook..",19.0,17,False,2024-02-08 01:27:56.000,0.12.1,49.0,sklearn-evaluation,,,['sklearn'],,3824.0,3.0,,https://pypi.org/project/sklearn-evaluation,2024-02-08 01:27:56.000,3.0,3824.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +823,carefree-learn,carefree0910/carefree-learn,tabular,,https://github.com/carefree0910/carefree-learn,https://github.com/carefree0910/carefree-learn,MIT,2020-06-17 17:44:17.000,2024-03-18 12:01:04.000000,2024-03-18 12:01:00,5152.0,,38.0,12.0,1.0,2.0,80.0,399.0,Deep Learning PyTorch.,1.0,17,True,2024-01-09 05:17:07.000,0.5.0,103.0,carefree-learn,,,['pytorch'],,846.0,7.0,7.0,https://pypi.org/project/carefree-learn,2024-01-09 05:17:07.000,,846.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +824,skggm,skggm/skggm,sklearn-utils,,https://github.com/skggm/skggm,https://github.com/skggm/skggm,MIT,2016-06-11 18:35:56.000,2024-03-20 15:29:38.000000,2023-06-15 16:53:55,703.0,,43.0,11.0,60.0,31.0,47.0,238.0,Scikit-learn compatible estimation of general graphical models.,7.0,17,False,2018-09-12 01:12:49.000,0.2.8,6.0,skggm,,,['sklearn'],,62.0,20.0,16.0,https://pypi.org/project/skggm,2018-09-12 01:12:49.000,4.0,62.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +825,Muda,bmcfee/muda,audio,,https://github.com/bmcfee/muda,https://github.com/bmcfee/muda,ISC,2014-11-07 21:21:22.000,2021-12-15 16:53:25.527000,2021-05-03 14:04:36,293.0,,33.0,14.0,36.0,8.0,44.0,230.0,A library for augmenting annotated audio data.,7.0,17,False,2019-11-15 15:46:21.000,0.4.1,12.0,muda,,,,,99.0,30.0,28.0,https://pypi.org/project/muda,2019-11-15 15:46:21.000,2.0,99.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +826,nvidia-ml-py3,nicolargo/nvidia-ml-py3,gpu-utilities,,https://github.com/nicolargo/nvidia-ml-py3,https://github.com/nicolargo/nvidia-ml-py3,BSD-3-Clause,2017-06-03 07:47:03.000,2024-06-30 08:01:08.000000,2024-06-30 08:01:08,6.0,1.0,57.0,5.0,2.0,3.0,1.0,130.0,Python 3 Bindings for the NVIDIA Management Library.,2.0,17,False,2017-06-03 07:43:46.000,7.352.0,1.0,nvidia-ml-py3,anaconda/nvidia-ml,,,,304549.0,9689.0,9560.0,https://pypi.org/project/nvidia-ml-py3,2017-06-03 07:43:46.000,129.0,304517.0,https://anaconda.org/anaconda/nvidia-ml,2023-06-16 19:26:58.970,1232.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +827,OpenNRE,thunlp/OpenNRE,nlp,,https://github.com/thunlp/OpenNRE,https://github.com/thunlp/OpenNRE,MIT,2017-02-26 07:37:12.000,2024-01-10 11:52:49.000000,2024-01-10 11:52:48,177.0,,1055.0,119.0,24.0,17.0,353.0,4309.0,An Open-Source Package for Neural Relation Extraction (NRE).,13.0,16,True,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +828,StarSpace,facebookresearch/StarSpace,ml-frameworks,,https://github.com/facebookresearch/StarSpace,https://github.com/facebookresearch/StarSpace,MIT,2017-06-28 17:50:18.000,2022-12-04 04:02:21.000000,2019-12-13 19:03:25,138.0,,531.0,176.0,110.0,56.0,149.0,3937.0,"Learning embeddings for classification, retrieval and ranking.",17.0,16,False,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +829,Euler,alibaba/euler,graph,,https://github.com/alibaba/euler,https://github.com/alibaba/euler,Apache-2.0,2019-01-10 06:32:32.000,2023-08-19 12:30:48.000000,2020-07-29 05:53:01,8.0,,560.0,139.0,28.0,217.0,102.0,2889.0,A distributed graph deep learning framework.,5.0,16,False,2020-07-07 02:24:18.000,2.0.0,2.0,euler-gl,,,['tensorflow'],,21.0,1.0,1.0,https://pypi.org/project/euler-gl,2019-04-10 01:53:45.000,,21.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +830,automl-gs,minimaxir/automl-gs,hyperopt,,https://github.com/minimaxir/automl-gs,https://github.com/minimaxir/automl-gs,MIT,2019-01-13 18:57:44.000,2019-10-22 11:20:40.000000,2019-04-05 06:48:14,102.0,,170.0,61.0,10.0,26.0,6.0,1845.0,"Provide an input CSV and a target field to predict, generate a model + code to run it.",7.0,16,False,2019-04-05 06:51:04.000,0.2.1,2.0,automl_gs,,,,46.0,42.0,,,https://pypi.org/project/automl_gs,2019-04-05 06:47:54.000,,42.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +831,AutoGL,THUMNLab/AutoGL,graph,,https://github.com/THUMNLab/AutoGL,https://github.com/THUMNLab/AutoGL,Apache-2.0,2020-11-30 14:26:22.000,2024-08-08 16:55:04.000000,2024-02-05 15:11:35,743.0,,120.0,29.0,111.0,14.0,25.0,1078.0,An autoML framework & toolkit for machine learning on graphs.,15.0,16,True,2022-12-30 06:11:04.000,0.4.0,4.0,auto-graph-learning,,,['pytorch'],,,,,https://pypi.org/project/auto-graph-learning,2020-12-23 08:05:25.000,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +832,Fiber,uber/fiber,distributed-ml,,https://github.com/uber/fiber,https://github.com/uber/fiber,Apache-2.0,2020-01-07 18:16:24.000,2023-03-19 22:55:22.000000,2021-03-15 07:00:08,66.0,,108.0,19.0,37.0,20.0,8.0,1040.0,Distributed Computing for AI Made Simple.,5.0,16,False,2020-07-09 03:28:28.000,0.2.1,6.0,fiber,,,,,110.0,79.0,78.0,https://pypi.org/project/fiber,2020-07-09 03:28:28.000,1.0,110.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +833,Translate,pytorch/translate,nlp,,https://github.com/pytorch/translate,https://github.com/pytorch/translate,BSD-3-Clause,2018-04-24 16:44:04.000,2023-04-27 20:56:00.000000,2022-06-10 23:04:56,813.0,,203.0,42.0,667.0,28.0,27.0,821.0,Translate - a PyTorch Language Library.,88.0,16,False,,,1.0,pytorch-translate,,,['pytorch'],,27.0,,,https://pypi.org/project/pytorch-translate,2018-05-01 19:59:40.000,,27.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +834,madgrad,facebookresearch/madgrad,pytorch-utils,,https://github.com/facebookresearch/madgrad,https://github.com/facebookresearch/madgrad,MIT,2021-01-12 19:41:06.000,2023-04-11 19:24:43.000000,2023-04-11 19:24:38,24.0,,57.0,17.0,7.0,,10.0,799.0,MADGRAD Optimization Method.,2.0,16,False,,,4.0,madgrad,,,['pytorch'],,4139.0,84.0,83.0,https://pypi.org/project/madgrad,2022-03-08 18:23:32.000,1.0,4139.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +835,TensorFrames,databricks/tensorframes,distributed-ml,,https://github.com/databricks/tensorframes,https://github.com/databricks/tensorframes,Apache-2.0,2016-03-04 19:25:19.000,2018-12-28 23:37:03.000000,,,,150.0,,,51.0,,718.0,Tensorflow wrapper for DataFrames on Apache Spark.,9.0,16,False,2018-05-16 14:20:28.000,0.2.9,2.0,tensorframes,,,"['tensorflow', 'spark']",,9561.0,1.0,,https://pypi.org/project/tensorframes,2018-05-16 14:20:28.000,1.0,9561.0,,,,3.0,,,,,,-4.0,,,,,,,,,,,,,,,,,,, +836,cuSignal,rapidsai/cusignal,gpu-utilities,,https://github.com/rapidsai/cusignal,https://github.com/rapidsai/cusignal,Apache-2.0,2019-08-22 14:27:27.000,2023-09-21 18:53:21.000000,2023-09-21 18:53:18,1296.0,,125.0,42.0,435.0,25.0,130.0,712.0,GPU accelerated signal processing.,46.0,16,True,2023-08-09 16:45:21.000,23.08.00,21.0,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +837,textflint,textflint/textflint,adversarial,,https://github.com/textflint/textflint,https://github.com/textflint/textflint,GPL-3.0,2021-03-06 11:15:52.000,2022-09-27 17:09:16.000000,2022-06-21 04:27:47,257.0,,92.0,18.0,19.0,4.0,29.0,634.0,Unified Multilingual Robustness Evaluation Toolkit for Natural Language Processing.,18.0,16,False,2022-03-15 07:18:47.000,0.1.0,6.0,textflint,,,,,88.0,17.0,17.0,https://pypi.org/project/textflint,2022-03-15 07:18:47.000,,88.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +838,kglib,vaticle/kglib,graph,,https://github.com/typedb/typedb-ml,https://github.com/typedb/typedb-ml,Apache-2.0,2018-09-16 16:46:48.000,2023-11-18 17:08:08.000000,2023-11-18 17:08:08,508.0,,98.0,38.0,106.0,12.0,51.0,551.0,TypeDB-ML is the Machine Learning integrations library for TypeDB.,13.0,16,True,2022-07-29 11:37:34.000,0.3.0,8.0,grakn-kglib,,,,235.0,131.0,,,https://pypi.org/project/grakn-kglib,2020-08-19 15:39:10.000,,128.0,,,,3.0,,,,,,,,typedb/typedb-ml,,,,,,,,,,,,,,,,, +839,OpenRec,ylongqi/openrec,recommender-systems,,https://github.com/ylongqi/openrec,https://github.com/ylongqi/openrec,Apache-2.0,2017-11-29 16:04:40.000,2023-03-24 23:54:19.000000,2020-02-19 07:57:17,213.0,,84.0,36.0,47.0,5.0,12.0,411.0,OpenRec is an open-source and modular library for neural network-inspired recommendation algorithms.,11.0,16,False,2020-02-18 06:52:11.000,0.3.0,12.0,openrec,,,,,64.0,4.0,3.0,https://pypi.org/project/openrec,2020-02-18 06:52:11.000,1.0,64.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +840,Pywick,achaiah/pywick,pytorch-utils,,https://github.com/achaiah/pywick,https://github.com/achaiah/pywick,MIT,2019-03-25 15:42:47.000,2022-02-04 15:57:11.000000,2021-10-22 03:09:17,149.0,,37.0,15.0,39.0,2.0,13.0,397.0,High-level batteries-included neural network training library for Pytorch.,4.0,16,False,2021-10-22 03:19:11.000,0.6.5,8.0,pywick,,,['pytorch'],,93.0,11.0,11.0,https://pypi.org/project/pywick,2021-10-22 03:19:11.000,,93.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +841,tfdeploy,riga/tfdeploy,model-serialisation,,https://github.com/riga/tfdeploy,https://github.com/riga/tfdeploy,BSD-3-Clause,2016-03-07 13:08:21.000,2024-02-25 19:50:49.000000,2024-02-25 19:50:49,174.0,,38.0,21.0,5.0,11.0,23.0,352.0,Deploy tensorflow graphs for fast evaluation and export to tensorflow-less environments running numpy.,4.0,16,True,2017-03-30 10:51:26.000,0.4.2,22.0,tfdeploy,,,['tensorflow'],,93.0,,,https://pypi.org/project/tfdeploy,2017-03-30 10:51:26.000,,93.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +842,pdvega,altair-viz/pdvega,data-viz,,https://github.com/altair-viz/pdvega,https://github.com/altair-viz/pdvega,MIT,2018-01-11 21:30:27.000,2019-03-29 16:09:14.000000,2019-03-29 16:09:13,177.0,,32.0,23.0,21.0,17.0,10.0,344.0,Interactive plotting for Pandas using Vega-Lite.,9.0,16,False,,,1.0,pdvega,,,,,52.0,88.0,88.0,https://pypi.org/project/pdvega,2018-02-01 04:56:43.000,,52.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +843,pandas-ml,pandas-ml/pandas-ml,others,,https://github.com/pandas-ml/pandas-ml,https://github.com/pandas-ml/pandas-ml,BSD-3-Clause,2015-02-21 03:14:04.000,2020-08-14 12:29:33.000000,2019-03-05 01:36:55,153.0,,79.0,18.0,93.0,30.0,18.0,317.0,"pandas, scikit-learn, xgboost and seaborn integration.",4.0,16,False,2019-03-05 01:36:12.000,0.6.1,9.0,pandas-ml,,,"['sklearn', 'pandas']",11.0,2639.0,2.0,,https://pypi.org/project/pandas-ml,2019-03-05 01:35:23.000,2.0,2639.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +844,nanodl,HMUNACHI/nanodl,ml-frameworks,,https://github.com/HMUNACHI/nanodl,https://github.com/HMUNACHI/nanodl,MIT,2023-08-22 13:22:24.000,2024-08-28 21:24:22.000000,2024-08-28 21:24:19,158.0,3.0,11.0,9.0,15.0,2.0,7.0,271.0,A Jax-based library for designing and training transformer models from scratch.,3.0,16,False,2024-08-28 20:41:08.000,0.0.0,8.0,nanodl,,,['jax'],,166.0,1.0,1.0,https://pypi.org/project/nanodl,2024-08-28 20:41:08.000,,166.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +845,backprop,backprop-ai/backprop,model-serialisation,,https://github.com/backprop-ai/backprop,https://github.com/backprop-ai/backprop,Apache-2.0,2020-10-30 15:25:14.000,2024-07-31 15:16:51.000000,2021-05-03 09:15:21,219.0,,12.0,16.0,14.0,5.0,4.0,242.0,"Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models.",8.0,16,False,2021-04-20 13:53:12.000,0.1.2,16.0,backprop,,,,,245.0,3.0,3.0,https://pypi.org/project/backprop,2024-07-31 15:16:51.000,,245.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +846,skift,shaypal5/skift,nlp,,https://github.com/shaypal5/skift,https://github.com/shaypal5/skift,MIT,2018-02-03 11:37:21.000,2022-06-07 15:07:07.000000,2022-06-07 15:07:04,141.0,,24.0,10.0,8.0,1.0,10.0,235.0,scikit-learn wrappers for Python fastText.,9.0,16,False,2022-02-14 13:45:54.000,0.0.23,18.0,skift,,,['sklearn'],,233.0,16.0,16.0,https://pypi.org/project/skift,2018-03-15 09:05:47.000,,233.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +847,Torch Points 3D,nicolas-chaulet/torch-points3d,image,,https://github.com/nicolas-chaulet/torch-points3d,https://github.com/nicolas-chaulet/torch-points3d,BSD-3-Clause,2022-01-09 14:41:37.000,2021-12-10 20:17:18.000000,2021-12-10 20:17:18,1788.0,,44.0,1.0,,,,206.0,Pytorch framework for doing deep learning on point clouds.,29.0,16,False,2021-04-30 09:00:22.000,1.3.0,14.0,torch-points3d,,,['pytorch'],,991.0,,,https://pypi.org/project/torch-points3d,2021-04-30 09:00:22.000,,991.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +848,ipyexperiments,stas00/ipyexperiments,gpu-utilities,,https://github.com/stas00/ipyexperiments,https://github.com/stas00/ipyexperiments,Apache-2.0,2018-11-15 01:19:40.000,2023-12-15 03:22:24.000000,2023-12-15 03:22:22,207.0,,13.0,9.0,2.0,,5.0,202.0,"Automatic GPU+CPU memory profiling, re-use and memory leaks detection using jupyter/ipython experiment containers.",3.0,16,False,2023-12-15 03:21:06.000,0.1.29,25.0,ipyexperiments,,,['jupyter'],,238.0,11.0,9.0,https://pypi.org/project/ipyexperiments,2023-12-15 03:21:06.000,2.0,238.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +849,modelkit,Cornerstone-OnDemand/modelkit,model-serialisation,,https://github.com/Cornerstone-OnDemand/modelkit,https://github.com/Cornerstone-OnDemand/modelkit,MIT,2021-05-14 12:10:51.000,2024-06-06 14:34:14.000000,2024-06-06 14:27:44,864.0,,17.0,8.0,184.0,11.0,23.0,153.0,Toolkit for developing and maintaining ML models.,14.0,16,False,2024-02-02 14:57:28.000,0.1.2,35.0,modelkit,,,,,6834.0,,,https://pypi.org/project/modelkit,2024-02-02 14:55:53.000,,6834.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +850,steppy,minerva-ml/steppy,ml-experiments,,https://github.com/minerva-ml/steppy,https://github.com/minerva-ml/steppy,MIT,2018-01-15 09:40:49.000,2018-11-23 09:49:59.000000,2018-11-23 09:47:34,69.0,,32.0,13.0,54.0,16.0,50.0,134.0,"Lightweight, Python library for fast and reproducible experimentation.",7.0,16,False,2018-11-23 09:49:59.000,0.1.16,16.0,steppy,,,,,89.0,63.0,58.0,https://pypi.org/project/steppy,2018-11-23 09:49:59.000,5.0,89.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +851,Collie,ShopRunner/collie,recommender-systems,,https://github.com/ShopRunner/collie,https://github.com/ShopRunner/collie,BSD-3-Clause,2021-04-12 20:54:06.000,2024-02-21 16:29:12.000000,2023-03-31 15:44:32,231.0,,20.0,31.0,53.0,7.0,7.0,107.0,"A library for preparing, training, and evaluating scalable deep learning hybrid recommender systems using PyTorch.",15.0,16,False,2023-03-31 16:09:03.477,1.3.1,10.0,collie,,,['pytorch'],,139.0,49.0,49.0,https://pypi.org/project/collie,2022-01-18 23:07:16.000,,139.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +852,CometML,comet-ml/examples,ml-experiments,,,https://www.comet.com,MIT,,2024-08-28 10:19:32.000000,,,,,,,,,,Supercharging Machine Learning.,,16,True,2024-08-28 10:19:32.000,3.45.0,295.0,comet_ml,comet_ml,,,,768295.0,74.0,,https://pypi.org/project/comet_ml,2024-08-28 10:19:32.000,74.0,768295.0,https://anaconda.org/anaconda/comet_ml,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +853,GraphSAGE,williamleif/GraphSAGE,graph,,https://github.com/williamleif/GraphSAGE,https://github.com/williamleif/GraphSAGE,MIT,2017-05-29 15:36:22.000,2024-08-04 16:33:52.000000,2018-09-19 19:27:00,59.0,,841.0,77.0,35.0,120.0,59.0,3387.0,Representation learning on large graphs using stochastic graph convolutions.,9.0,15,False,,,,,,,['tensorflow'],,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +854,ZhuSuan,thu-ml/zhusuan,probabilistics,,https://github.com/thu-ml/zhusuan,https://github.com/thu-ml/zhusuan,MIT,2016-07-18 13:31:38.000,2022-12-17 20:33:19.000000,2019-08-05 10:00:04,439.0,,420.0,143.0,72.0,12.0,53.0,2199.0,"A probabilistic programming library for Bayesian deep learning, generative models, based on Tensorflow.",20.0,15,False,,,,,,,['tensorflow'],,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +855,BLINK,facebookresearch/BLINK,nlp,,https://github.com/facebookresearch/BLINK,https://github.com/facebookresearch/BLINK,MIT,2019-09-25 21:27:44.000,2023-09-21 16:18:30.000000,2021-04-02 03:03:34,211.0,,232.0,39.0,40.0,73.0,34.0,1158.0,Entity Linker solution.,16.0,15,False,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +856,TextBox,RUCAIBox/TextBox,nlp,,https://github.com/RUCAIBox/TextBox,https://github.com/RUCAIBox/TextBox,MIT,2020-11-08 07:35:46.000,2023-07-27 14:39:30.000000,2023-05-18 02:26:52,1358.0,,117.0,19.0,295.0,3.0,70.0,1069.0,TextBox 2.0 is a text generation library with pre-trained language models.,18.0,15,False,2022-12-28 02:06:22.000,2.0.0,10.0,textbox,,,,,2.0,7.0,7.0,https://pypi.org/project/textbox,2021-04-15 09:35:06.000,,2.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +857,MedicalTorch,perone/medicaltorch,medical-data,,https://github.com/perone/medicaltorch,https://github.com/perone/medicaltorch,Apache-2.0,2018-02-27 02:50:07.000,2024-04-26 17:46:05.000000,2021-04-16 18:50:54,57.0,,121.0,49.0,22.0,15.0,9.0,843.0,A medical imaging framework for Pytorch.,8.0,15,False,2018-11-24 00:33:11.000,0.2,2.0,medicaltorch,,,['pytorch'],,95.0,17.0,17.0,https://pypi.org/project/medicaltorch,2018-11-24 00:29:36.000,,95.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +858,Anchor,marcotcr/anchor,interpretability,,https://github.com/marcotcr/anchor,https://github.com/marcotcr/anchor,BSD-2-Clause,2018-02-02 23:38:50.000,2022-07-19 18:09:12.000000,2022-07-19 18:08:39,47.0,,112.0,27.0,10.0,25.0,51.0,793.0,Code for High-Precision Model-Agnostic Explanations paper.,10.0,15,False,,,10.0,anchor_exp,,,,,1010.0,2.0,,https://pypi.org/project/anchor_exp,2020-09-10 22:52:00.000,2.0,1010.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +859,FlashTorch,MisaOgura/flashtorch,interpretability,,https://github.com/MisaOgura/flashtorch,https://github.com/MisaOgura/flashtorch,MIT,2019-03-22 13:00:57.000,2023-09-21 07:22:50.000000,2023-09-21 07:22:50,127.0,,85.0,16.0,15.0,10.0,22.0,726.0,Visualization toolkit for neural networks in PyTorch! Demo --.,2.0,15,True,2020-05-29 14:39:38.000,0.1.3,12.0,flashtorch,,,['pytorch'],,108.0,22.0,22.0,https://pypi.org/project/flashtorch,2020-05-29 14:38:32.000,,108.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +860,SpeedTorch,Santosh-Gupta/SpeedTorch,gpu-utilities,,https://github.com/Santosh-Gupta/SpeedTorch,https://github.com/Santosh-Gupta/SpeedTorch,MIT,2019-09-07 18:57:52.000,2020-02-21 23:13:29.000000,2020-02-21 23:13:28,170.0,,38.0,24.0,4.0,4.0,2.0,681.0,Library for faster pinned CPU - GPU transfer in Pytorch.,3.0,15,False,2020-01-06 05:27:17.000,0.1.6,14.0,SpeedTorch,,,['pytorch'],,106.0,8.0,6.0,https://pypi.org/project/SpeedTorch,2020-01-06 05:27:17.000,2.0,106.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +861,KD-Lib,SforAiDl/KD_Lib,others,,https://github.com/SforAiDl/KD_Lib,https://github.com/SforAiDl/KD_Lib,MIT,2020-05-10 13:08:42.000,2023-03-01 21:06:37.000000,2023-03-01 21:03:09,298.0,,56.0,16.0,83.0,18.0,49.0,592.0,A Pytorch Knowledge Distillation library for benchmarking and extending works in the domains of Knowledge..,6.0,15,False,2022-05-18 08:35:04.000,0.0.32,8.0,KD-Lib,,,['pytorch'],,139.0,,,https://pypi.org/project/KD-Lib,2022-05-18 08:35:04.000,,139.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +862,atspy,firmai/atspy,time-series-data,,https://github.com/firmai/atspy,https://github.com/firmai/atspy,MIT,2020-01-28 05:00:10.000,2022-11-21 21:55:23.000000,2021-12-18 09:26:18,99.0,,88.0,21.0,18.0,22.0,2.0,512.0,AtsPy: Automated Time Series Models in Python (by @firmai).,5.0,15,False,2020-11-12 16:10:48.000,zen,39.0,atspy,,,,,255.0,12.0,12.0,https://pypi.org/project/atspy,2020-04-24 18:16:15.000,,255.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +863,NeuralCompression,facebookresearch/NeuralCompression,others,,https://github.com/facebookresearch/NeuralCompression,https://github.com/facebookresearch/NeuralCompression,MIT,2021-07-09 15:14:13.000,2024-03-18 22:30:20.000000,2024-03-18 22:30:15,140.0,,42.0,21.0,169.0,6.0,65.0,496.0,A collection of tools for neural compression enthusiasts.,10.0,15,True,2023-10-03 14:26:28.000,0.3.1,6.0,neuralcompression,,,,,109.0,,,https://pypi.org/project/neuralcompression,2023-10-03 14:26:28.000,,109.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +864,caliban,google/caliban,ml-experiments,,https://github.com/google/caliban,https://github.com/google/caliban,Apache-2.0,2020-06-02 18:12:50.000,2024-06-06 22:38:20.000000,2024-01-25 16:57:26,261.0,,66.0,19.0,101.0,19.0,15.0,490.0,"Research workflows made easy, locally and in the Cloud.",10.0,15,True,2023-06-16 17:26:21.434,0.4.2,11.0,caliban,,,,,113.0,3.0,3.0,https://pypi.org/project/caliban,2020-09-12 19:41:23.000,,113.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +865,ExplainX.ai,explainX/explainx,interpretability,,https://github.com/explainX/explainx,https://github.com/explainX/explainx,MIT,2020-06-16 14:27:15.000,2024-08-21 16:55:05.000000,2024-08-21 16:55:05,192.0,1.0,52.0,10.0,17.0,10.0,29.0,404.0,Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line..,5.0,15,True,2021-02-07 11:06:21.000,2.407,56.0,explainx,,,,17.0,208.0,,,https://pypi.org/project/explainx,2021-02-04 16:44:24.000,,208.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +866,Adversary,airbnb/artificial-adversary,adversarial,,https://github.com/airbnb/artificial-adversary,https://github.com/airbnb/artificial-adversary,MIT,2018-08-08 04:42:11.000,2023-06-16 19:21:01.312000,2018-08-29 15:31:30,15.0,,55.0,18.0,6.0,6.0,,394.0,Tool to generate adversarial text examples and test machine learning models against them.,5.0,15,False,2018-08-29 15:14:41.000,1.1.1,3.0,Adversary,conda-forge/artificial-adversary,,,,190.0,11.0,10.0,https://pypi.org/project/Adversary,2018-08-29 15:14:41.000,1.0,54.0,https://anaconda.org/conda-forge/artificial-adversary,2023-06-16 19:21:01.312,6848.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +867,ptgnn,microsoft/ptgnn,graph,,https://github.com/microsoft/ptgnn,https://github.com/microsoft/ptgnn,MIT,2020-05-12 08:42:30.000,2022-02-01 17:31:29.000000,2022-02-01 17:31:29,99.0,,40.0,12.0,17.0,2.0,5.0,372.0,A PyTorch Graph Neural Network Library.,8.0,15,False,2021-10-21 21:43:04.000,0.10.4,18.0,ptgnn,,,['pytorch'],,211.0,4.0,4.0,https://pypi.org/project/ptgnn,2021-10-21 21:43:04.000,,211.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +868,TorchDrift,torchdrift/torchdrift,pytorch-utils,,https://github.com/TorchDrift/TorchDrift,https://github.com/TorchDrift/TorchDrift,Apache-2.0,2021-02-10 09:27:48.000,2022-08-26 08:15:45.000000,2022-08-26 08:15:45,38.0,,15.0,11.0,6.0,9.0,6.0,311.0,Drift Detection for your PyTorch Models.,4.0,15,False,2021-03-08 12:21:48.000,0.1.0,3.0,torchdrift,,,['pytorch'],,195.0,27.0,27.0,https://pypi.org/project/torchdrift,2021-03-08 12:51:05.000,,195.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +869,data-describe,data-describe/data-describe,data-viz,,https://github.com/data-describe/data-describe,https://github.com/data-describe/data-describe,Apache-2.0,2020-05-04 17:58:14.000,2023-02-22 05:20:46.000000,2021-11-19 06:05:15,700.0,,18.0,13.0,271.0,64.0,181.0,295.0,datadescribe: Pythonic EDA Accelerator for Data Science.,13.0,15,False,,,5.0,data-describe,,,,,390.0,,,https://pypi.org/project/data-describe,2020-12-03 23:07:43.000,,390.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +870,Headliner,as-ideas/headliner,nlp,,https://github.com/as-ideas/headliner,https://github.com/as-ideas/headliner,MIT,2019-09-30 11:33:28.000,2021-03-26 07:19:57.000000,2020-02-14 09:03:27,276.0,,41.0,16.0,7.0,2.0,13.0,229.0,Easy training and deployment of seq2seq models.,2.0,15,False,2020-01-24 09:06:29.000,1.0.2,30.0,headliner,,,,,331.0,7.0,6.0,https://pypi.org/project/headliner,2020-01-24 09:06:29.000,1.0,331.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +871,nx-altair,Zsailer/nx_altair,data-viz,,https://github.com/Zsailer/nx_altair,https://github.com/Zsailer/nx_altair,MIT,2018-05-13 00:10:12.000,2023-09-27 23:13:07.000000,2020-06-02 21:10:26,51.0,,27.0,10.0,15.0,9.0,4.0,223.0,Draw interactive NetworkX graphs with Altair.,3.0,15,False,2020-06-02 21:11:12.000,0.1.6,8.0,nx-altair,,,['jupyter'],,348.0,9.0,,https://pypi.org/project/nx-altair,2020-06-02 21:11:12.000,9.0,348.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +872,Parfit,jmcarpenter2/parfit,hyperopt,,https://github.com/jmcarpenter2/parfit,https://github.com/jmcarpenter2/parfit,MIT,2017-11-22 20:17:51.000,2024-02-13 04:16:38.000000,2020-04-04 19:26:37,127.0,,28.0,5.0,5.0,6.0,5.0,198.0,"A package for parallelizing the fit and flexibly scoring of sklearn machine learning models, with visualization..",4.0,15,False,,,23.0,parfit,,,['sklearn'],,428.0,28.0,28.0,https://pypi.org/project/parfit,2018-10-11 22:03:16.000,,428.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +873,HugsVision,qanastek/HugsVision,image,,https://github.com/qanastek/HugsVision,https://github.com/qanastek/HugsVision,MIT,2021-08-12 21:46:08.000,2023-08-13 00:37:26.000000,2023-01-22 01:25:39,75.0,,19.0,5.0,2.0,17.0,23.0,192.0,HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision.,2.0,15,False,2023-01-22 01:21:35.467,0.75.5,78.0,hugsvision,,,['huggingface'],,865.0,13.0,13.0,https://pypi.org/project/hugsvision,2023-01-22 01:21:35.467,,865.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +874,GraphEmbedding,shenweichen/GraphEmbedding,graph,,https://github.com/shenweichen/GraphEmbedding,https://github.com/shenweichen/GraphEmbedding,MIT,2019-02-11 16:27:20.000,2024-03-14 09:28:18.000000,2022-06-21 18:24:09,30.0,,994.0,64.0,13.0,44.0,25.0,3662.0,Implementation and experiments of graph embedding algorithms.,9.0,14,False,,,,,,,['sklearn'],,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +875,OpenNE,thunlp/OpenNE,graph,,https://github.com/thunlp/OpenNE,https://github.com/thunlp/OpenNE,MIT,2017-10-08 04:58:20.000,2024-01-10 11:53:25.000000,2024-01-10 11:53:25,104.0,,488.0,67.0,26.0,10.0,97.0,1683.0,An Open-Source Package for Network Embedding (NE).,12.0,14,True,,,,,,,['tensorflow'],,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +876,Medical Detection Toolkit,MIC-DKFZ/medicaldetectiontoolkit,medical-data,,https://github.com/MIC-DKFZ/medicaldetectiontoolkit,https://github.com/MIC-DKFZ/medicaldetectiontoolkit,Apache-2.0,2018-10-12 12:34:57.000,2024-06-17 22:47:46.000000,2022-04-04 08:29:54,41.0,,294.0,53.0,23.0,42.0,85.0,1289.0,"The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN,..",3.0,14,False,,,,,,,['pytorch'],,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +877,Skater,oracle/Skater,interpretability,,https://github.com/oracle/Skater,https://github.com/oracle/Skater,UPL-1.0,2017-01-26 05:45:42.000,2023-09-18 15:13:22.392000,,,,182.0,,,72.0,,1067.0,Python Library for Model Interpretation/Explanations.,7.0,14,False,2018-09-21 07:03:32.000,1.1.2,23.0,skater,conda-forge/skater,,,,1927.0,1.0,,https://pypi.org/project/skater,2018-09-21 07:03:32.000,1.0,408.0,https://anaconda.org/conda-forge/skater,2023-09-18 15:13:22.392,75987.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +878,rliable,google-research/rliable,reinforcement-learning,,https://github.com/google-research/rliable,https://github.com/google-research/rliable,Apache-2.0,2021-08-20 00:41:06.000,2024-08-12 20:48:27.000000,2024-08-12 20:48:27,72.0,6.0,45.0,11.0,11.0,1.0,15.0,742.0,"[NeurIPS21 Outstanding Paper] Library for reliable evaluation on RL and ML benchmarks, even with only a handful of..",8.0,14,True,,,,rliable`,,,,,,144.0,144.0,https://pypi.org/project/rliable`,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +879,VizSeq,facebookresearch/vizseq,nlp,,https://github.com/facebookresearch/vizseq,https://github.com/facebookresearch/vizseq,MIT,2019-08-26 13:19:38.000,2024-06-18 15:30:37.000000,2024-06-18 15:30:34,80.0,1.0,61.0,16.0,65.0,7.0,9.0,440.0,"An Analysis Toolkit for Natural Language Generation (Translation, Captioning, Summarization, etc.).",4.0,14,True,2020-08-07 01:13:52.000,0.1.15,16.0,vizseq,,,,,109.0,11.0,11.0,https://pypi.org/project/vizseq,2020-08-07 01:13:52.000,,109.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +880,interpret-text,interpretml/interpret-text,interpretability,,https://github.com/interpretml/interpret-text,https://github.com/interpretml/interpret-text,MIT,2019-09-04 16:39:48.000,2024-02-05 16:37:11.000000,2024-02-05 16:37:10,152.0,,68.0,19.0,177.0,87.0,16.0,412.0,A library that incorporates state-of-the-art explainers for text-based machine learning models and visualizes the..,18.0,14,True,2021-12-07 15:12:02.000,0.1.3,5.0,interpret-text,,,['jupyter'],,136.0,,,https://pypi.org/project/interpret-text,2021-12-07 01:57:31.000,,136.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +881,tsaug,arundo/tsaug,time-series-data,,https://github.com/arundo/tsaug,https://github.com/arundo/tsaug,Apache-2.0,2019-09-27 00:38:05.000,2023-01-11 11:16:16.000000,2020-04-17 02:46:38,10.0,,37.0,11.0,8.0,10.0,3.0,347.0,A Python package for time series augmentation.,4.0,14,False,2020-04-17 02:50:25.000,0.2.1,4.0,tsaug,,,,,1497.0,2.0,,https://pypi.org/project/tsaug,2020-04-17 02:50:25.000,2.0,1497.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +882,TransferNLP,feedly/transfer-nlp,nlp,,https://github.com/feedly/transfer-nlp,https://github.com/feedly/transfer-nlp,MIT,2019-03-12 20:00:31.000,2024-07-25 10:16:22.000000,2020-05-28 17:31:53,465.0,,17.0,11.0,58.0,3.0,20.0,291.0,NLP library designed for reproducible experimentation management.,7.0,14,False,2020-05-28 19:00:02.000,0.1.6,8.0,transfer-nlp,,,['pytorch'],,99.0,,,https://pypi.org/project/transfer-nlp,2020-05-28 19:00:02.000,,99.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +883,NeuralQA,victordibia/neuralqa,nlp,,https://github.com/victordibia/neuralqa,https://github.com/victordibia/neuralqa,MIT,2020-05-19 03:55:56.000,2023-06-07 20:12:03.000000,2020-12-16 17:41:37,312.0,,32.0,8.0,72.0,31.0,8.0,233.0,NeuralQA: A Usable Library for Question Answering on Large Datasets with BERT.,3.0,14,False,,,27.0,neuralqa,,,,,124.0,5.0,5.0,https://pypi.org/project/neuralqa,2020-09-18 17:54:50.000,,124.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +884,LazyCluster,ml-tooling/lazycluster,distributed-ml,,https://github.com/ml-tooling/lazycluster,https://github.com/ml-tooling/lazycluster,Apache-2.0,2019-08-07 08:05:13.000,2023-02-16 02:23:02.000000,2021-08-19 13:59:11,444.0,,11.0,7.0,20.0,3.0,,49.0,Distributed machine learning made simple.,2.0,14,False,2020-12-14 15:25:59.000,0.2.4,5.0,lazycluster,,,,,170.0,41.0,41.0,https://pypi.org/project/lazycluster,2020-12-14 14:49:33.000,,170.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +885,OpenKE,thunlp/OpenKE,graph,,https://github.com/thunlp/OpenKE,https://github.com/thunlp/OpenKE,,2017-10-08 11:20:23.000,2024-01-10 11:51:05.000000,2024-01-10 11:51:05,143.0,,984.0,103.0,28.0,28.0,357.0,3801.0,An Open-Source Package for Knowledge Embedding (KE).,14.0,13,False,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +886,ENAS,carpedm20/ENAS-pytorch,hyperopt,,https://github.com/carpedm20/ENAS-pytorch,https://github.com/carpedm20/ENAS-pytorch,Apache-2.0,2018-02-15 04:54:37.000,2023-07-06 21:33:33.000000,2020-06-16 07:23:32,53.0,,484.0,108.0,12.0,39.0,8.0,2690.0,PyTorch implementation of Efficient Neural Architecture Search via Parameters Sharing.,6.0,13,False,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +887,ml-ane-transformers,apple/ml-ane-transformers,model-serialisation,,https://github.com/apple/ml-ane-transformers,https://github.com/apple/ml-ane-transformers,,2022-06-03 16:36:06.000,2023-04-25 09:24:38.000000,2022-08-09 04:03:14,5.0,,84.0,47.0,4.0,3.0,,2529.0,Reference implementation of the Transformer architecture optimized for Apple Neural Engine (ANE).,1.0,13,False,2022-08-09 04:22:55.000,0.1.3,4.0,ane-transformers,,,['pytorch'],70.0,1222.0,1.0,,https://pypi.org/project/ane-transformers,2022-08-09 04:22:00.465,1.0,1220.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +888,traingenerator,jrieke/traingenerator,others,,https://github.com/jrieke/traingenerator,https://github.com/jrieke/traingenerator,MIT,2020-12-03 16:47:16.000,2023-08-23 08:35:09.000000,2022-06-30 14:05:23,118.0,,175.0,37.0,10.0,13.0,3.0,1362.0,A web app to generate template code for machine learning.,3.0,13,False,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +889,GraphVite,DeepGraphLearning/graphvite,graph,,https://github.com/DeepGraphLearning/graphvite,https://github.com/DeepGraphLearning/graphvite,Apache-2.0,2019-07-16 15:48:20.000,2024-06-14 21:18:09.000000,2024-06-14 21:18:09,16.0,1.0,150.0,32.0,,53.0,60.0,1215.0,GraphVite: A General and High-performance Graph Embedding System.,1.0,13,True,,,4.0,,milagraph/graphvite,,,,79.0,,,,,,,https://anaconda.org/milagraph/graphvite,2023-06-16 16:16:18.265,4823.0,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +890,Maze,enlite-ai/maze,reinforcement-learning,,https://github.com/enlite-ai/maze,https://github.com/enlite-ai/maze,Custom,2021-02-11 08:26:37.000,2024-08-13 12:19:40.000000,2022-11-21 12:12:41,1044.0,,13.0,6.0,26.0,1.0,2.0,262.0,Maze Applied Reinforcement Learning Framework.,3.0,13,False,2022-11-21 12:23:00.858,0.2.0,21.0,maze-rl,,,['pytorch'],9.0,154.0,,,https://pypi.org/project/maze-rl,2021-12-13 16:04:42.000,,149.0,,,,3.0,enliteai/maze,https://hub.docker.com/r/enliteai/maze,2021-06-24 21:00:27.801118,,248.0,,,,,,,,,,,,,,,,,,,, +891,ONNX-T5,abelriboulot/onnxt5,nlp,,https://github.com/abelriboulot/onnxt5,https://github.com/abelriboulot/onnxt5,Apache-2.0,2020-08-01 09:38:35.000,2022-11-02 18:43:57.000000,2021-01-28 09:24:52,74.0,,28.0,8.0,6.0,8.0,8.0,250.0,"Summarization, translation, sentiment-analysis, text-generation and more at blazing speed using a T5 version..",4.0,13,False,2021-01-28 09:26:15.000,0.1.8,11.0,onnxt5,,,,,64.0,2.0,2.0,https://pypi.org/project/onnxt5,2021-01-28 09:26:15.000,,64.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +892,textvec,textvec/textvec,nlp,,https://github.com/textvec/textvec,https://github.com/textvec/textvec,MIT,2018-04-12 14:03:53.000,2024-06-17 22:44:04.000000,2024-01-09 14:26:42,74.0,,26.0,8.0,17.0,4.0,6.0,193.0,Text vectorization tool to outperform TFIDF for classification tasks.,11.0,13,False,2019-09-12 07:41:04.000,2.0,4.0,textvec,,,['sklearn'],,56.0,5.0,5.0,https://pypi.org/project/textvec,2020-12-03 14:17:09.000,,56.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +893,DeepNeuro,QTIM-Lab/DeepNeuro,medical-data,,https://github.com/QTIM-Lab/DeepNeuro,https://github.com/QTIM-Lab/DeepNeuro,MIT,2017-06-01 19:36:34.000,2020-06-24 13:00:15.000000,2020-06-24 13:00:14,285.0,,35.0,14.0,18.0,27.0,18.0,122.0,A deep learning python package for neuroimaging data. Made by:.,6.0,13,False,2019-06-10 21:04:04.000,0.2.3,6.0,deepneuro,,,,,44.0,2.0,2.0,https://pypi.org/project/deepneuro,2019-06-10 21:04:04.000,,44.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +894,model_search,google/model_search,hyperopt,,https://github.com/google/model_search,https://github.com/google/model_search,Apache-2.0,2021-01-19 18:26:34.000,2024-07-30 21:36:15.000000,2022-02-09 22:20:11,9.0,,461.0,93.0,22.0,52.0,15.0,3264.0,AutoML algorithms for model architecture search at scale.,1.0,12,False,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +895,MedicalNet,Tencent/MedicalNet,medical-data,,https://github.com/Tencent/MedicalNet,https://github.com/Tencent/MedicalNet,MIT,2019-07-17 09:53:10.000,2023-07-06 21:26:54.000000,2020-08-27 13:37:26,26.0,,404.0,63.0,6.0,63.0,17.0,1910.0,Many studies have shown that the performance on deep learning is significantly affected by volume of training data...,1.0,12,False,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +896,surpriver,tradytics/surpriver,financial-data,,https://github.com/tradytics/surpriver,https://github.com/tradytics/surpriver,GPL-3.0,2020-08-30 07:56:22.000,2021-08-13 08:02:31.000000,2020-09-21 04:32:05,64.0,,321.0,87.0,11.0,12.0,6.0,1755.0,Find big moving stocks before they move using machine learning and anomaly detection.,6.0,12,False,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +897,deltapy,firmai/deltapy,tabular,,https://github.com/firmai/deltapy,https://github.com/firmai/deltapy,MIT,2020-04-08 05:27:53.000,2023-09-19 11:11:53.000000,2022-03-01 16:13:48,42.0,,53.0,17.0,3.0,2.0,1.0,534.0,DeltaPy - Tabular Data Augmentation (by @firmai).,4.0,12,False,2020-11-12 16:13:21.000,zen,11.0,deltapy,,,,,116.0,4.0,4.0,https://pypi.org/project/deltapy,2020-04-09 01:48:32.000,,116.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +898,Auptimizer,LGE-ARC-AdvancedAI/auptimizer,hyperopt,,https://github.com/LGE-ARC-AdvancedAI/auptimizer,https://github.com/LGE-ARC-AdvancedAI/auptimizer,GPL-3.0,2019-09-12 01:08:37.000,2023-01-27 02:15:43.000000,2021-03-03 01:30:06,79.0,,27.0,21.0,44.0,1.0,5.0,200.0,An automatic ML model optimization tool.,11.0,12,False,2021-03-03 02:00:23.000,2.0,7.0,auptimizer,,,,,126.0,,,https://pypi.org/project/auptimizer,2021-03-02 02:40:32.000,,126.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +899,ModelChimp,ModelChimp/modelchimp,ml-experiments,,https://github.com/ModelChimp/modelchimp,https://github.com/ModelChimp/modelchimp,BSD-2-Clause,2018-11-05 08:39:03.000,2023-11-14 18:32:58.000000,2021-08-01 07:11:57,363.0,,12.0,5.0,1238.0,4.0,10.0,126.0,Experiment tracking for machine and deep learning projects.,3.0,12,False,2019-04-09 10:43:15.000,0.4.0,37.0,modelchimp,,,,,136.0,,,https://pypi.org/project/modelchimp,2019-04-09 10:41:20.000,,127.0,,,,3.0,modelchimp/modelchimp-server,https://hub.docker.com/r/modelchimp/modelchimp-server,2019-04-09 10:15:09.532793,,661.0,,,,,,,,,,,,,,,,,,,, +900,Attribution Priors,suinleelab/attributionpriors,interpretability,,https://github.com/suinleelab/attributionpriors,https://github.com/suinleelab/attributionpriors,MIT,2019-06-24 23:54:24.000,2021-03-19 19:43:58.000000,2021-03-19 19:43:51,72.0,,9.0,6.0,,2.0,4.0,121.0,Tools for training explainable models using attribution priors.,6.0,12,False,2021-03-16 17:47:18.000,1.0.0,4.0,attributionpriors,,,"['tensorflow', 'pytorch']",,70.0,5.0,5.0,https://pypi.org/project/attributionpriors,2019-10-31 18:03:05.000,,70.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +901,Hypermax,electricbrainio/hypermax,hyperopt,,https://github.com/genixpro/hypermax,https://github.com/genixpro/hypermax,BSD-3-Clause,2018-07-27 18:43:01.000,2024-01-03 19:06:45.000000,2024-01-03 19:06:45,209.0,,13.0,12.0,5.0,3.0,2.0,111.0,"Better, faster hyper-parameter optimization.",8.0,12,False,2019-10-23 15:40:12.000,0.5.1,11.0,hypermax,,,,,89.0,5.0,5.0,https://pypi.org/project/hypermax,2019-10-23 15:40:12.000,,89.0,,,,3.0,,,,,,,,genixpro/hypermax,,,,,,,,,,,,,,,,, +902,spacy-dbpedia-spotlight,MartinoMensio/spacy-dbpedia-spotlight,nlp,,https://github.com/MartinoMensio/spacy-dbpedia-spotlight,https://github.com/MartinoMensio/spacy-dbpedia-spotlight,MIT,2020-04-29 19:35:04.000,2023-03-24 11:33:01.000000,2023-03-24 11:32:56,55.0,,11.0,8.0,4.0,6.0,14.0,103.0,A spaCy wrapper for DBpedia Spotlight.,5.0,12,False,2023-03-08 10:33:19.000,0.2.6,11.0,spacy-dbpedia-spotlight,,,['spacy'],,986.0,,,https://pypi.org/project/spacy-dbpedia-spotlight,2022-10-07 09:58:11.751,,986.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +903,contextual-ai,SAP/contextual-ai,interpretability,,https://github.com/SAP-archive/contextual-ai,https://github.com/SAP-archive/contextual-ai,Apache-2.0,2020-05-12 07:15:56.000,2023-07-23 16:23:34.000000,2021-11-11 10:53:33,630.0,,11.0,13.0,26.0,4.0,13.0,85.0,"Contextual AI adds explainability to different stages of machine learning pipelines - data, training, and inference -..",12.0,12,False,2021-01-25 04:56:57.000,0.0.2,2.0,contextual-ai,,,,,114.0,,,https://pypi.org/project/contextual-ai,2021-01-25 04:56:57.000,,114.0,,,,3.0,,,,,,,,SAP-archive/contextual-ai,,,,,,,,,,,,,,,,, +904,nylon,Palashio/nylon,others,,https://github.com/Palashio/nylon,https://github.com/Palashio/nylon,MIT,2021-06-04 17:33:49.000,2021-07-29 20:34:04.000000,2021-07-23 19:37:10,185.0,,8.0,7.0,4.0,14.0,18.0,84.0,"An intelligent, flexible grammar of machine learning.",3.0,12,False,2021-06-25 14:27:32.000,0.0.7,8.0,nylon-ai,,,,,69.0,2.0,2.0,https://pypi.org/project/nylon-ai,2021-06-25 14:27:32.000,,69.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +905,bias-detector,intuit/bias-detector,interpretability,,https://github.com/intuit/bias-detector,https://github.com/intuit/bias-detector,MIT,2021-02-02 16:58:52.000,2024-02-04 11:31:27.000000,2024-02-04 11:28:34,124.0,,12.0,12.0,17.0,,,44.0,Bias Detector is a python package for detecting bias in machine learning models.,4.0,12,False,2024-02-04 11:31:27.000,0.0.13,12.0,bias-detector,,,,,151.0,2.0,2.0,https://pypi.org/project/bias-detector,2024-02-04 11:31:27.000,,151.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +906,nptsne,biovault/nptsne,data-viz,,https://github.com/biovault/nptsne,https://github.com/biovault/nptsne,Apache-2.0,2019-06-28 08:40:25.000,2023-07-14 11:30:56.000000,2021-02-03 08:52:27,857.0,,2.0,3.0,3.0,7.0,6.0,32.0,nptsne is a numpy compatible python binary package that offers a number of APIs for fast tSNE calculation.,3.0,12,False,2021-12-23 15:53:08.000,1.2.0,3.0,nptsne,,,,,130.0,7.0,7.0,https://pypi.org/project/nptsne,2021-12-23 15:53:08.000,,130.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +907,Devol,joeddav/devol,hyperopt,,https://github.com/joeddav/devol,https://github.com/joeddav/devol,MIT,2017-02-10 03:07:54.000,2023-05-25 14:45:47.000000,2020-07-05 21:56:58,116.0,,109.0,44.0,13.0,7.0,20.0,948.0,Genetic neural architecture search with Keras.,18.0,11,False,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +908,PySparNN,facebookresearch/pysparnn,nn-search,,https://github.com/facebookresearch/pysparnn,https://github.com/facebookresearch/pysparnn,BSD-3-Clause,2016-03-28 20:43:42.000,2020-10-02 06:01:01.000000,2018-01-31 16:50:23,147.0,,146.0,39.0,7.0,19.0,14.0,915.0,Approximate Nearest Neighbor Search for Sparse Data in Python!.,5.0,11,False,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +909,moolib,facebookresearch/moolib,distributed-ml,,https://github.com/facebookresearch/moolib,https://github.com/facebookresearch/moolib,MIT,2021-08-26 09:15:58.000,2022-12-12 15:07:44.000000,2022-12-12 15:07:38,41.0,,21.0,12.0,41.0,7.0,12.0,365.0,A library for distributed ML training with PyTorch.,6.0,11,False,2022-02-10 16:56:22.000,0.0.9c,1.0,,,,['pytorch'],,,4.0,4.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +910,autodist,petuum/autodist,distributed-ml,,https://github.com/petuum/autodist,https://github.com/petuum/autodist,Apache-2.0,2020-06-29 19:45:38.000,2022-09-23 22:45:06.000000,2021-01-28 00:04:40,208.0,,25.0,16.0,51.0,11.0,1.0,134.0,Simple Distributed Deep Learning on TensorFlow.,11.0,11,False,,,2.0,autodist,,,['tensorflow'],,52.0,2.0,2.0,https://pypi.org/project/autodist,2020-07-16 05:36:19.000,,52.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +911,jaxdf,ucl-bug/jaxdf,jax-utils,,https://github.com/ucl-bug/jaxdf,https://github.com/ucl-bug/jaxdf,LGPL-3.0,2021-09-08 16:38:46.000,2024-02-28 09:09:14.000000,2023-11-24 19:47:45,314.0,,7.0,7.0,126.0,7.0,9.0,117.0,A JAX-based research framework for writing differentiable numerical simulators with arbitrary discretizations.,4.0,11,False,2023-11-24 19:49:33.000,0.2.7,9.0,,,,['jax'],,,5.0,5.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +912,Mozart,aashrafh/Mozart,ocr,,https://github.com/aashrafh/Mozart,https://github.com/aashrafh/Mozart,Apache-2.0,2020-12-14 11:49:14.000,2022-08-24 18:18:43.000000,2022-08-24 18:18:43,62.0,,86.0,17.0,5.0,4.0,12.0,594.0,An optical music recognition (OMR) system. Converts sheet music to a machine-readable version.,6.0,10,False,,,,,,,['sklearn'],,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +913,textlesslib,facebookresearch/textlesslib,audio,,https://github.com/facebookresearch/textlesslib,https://github.com/facebookresearch/textlesslib,MIT,2022-02-09 16:28:00.000,2023-08-29 14:47:49.000000,2023-08-29 14:47:44,37.0,,50.0,15.0,13.0,14.0,11.0,518.0,Library for Textless Spoken Language Processing.,8.0,10,False,,,,,,,['pytorch'],,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +914,Hypertunity,gdikov/hypertunity,hyperopt,,https://github.com/gdikov/hypertunity,https://github.com/gdikov/hypertunity,Apache-2.0,2019-06-02 12:04:55.000,2020-01-26 23:14:49.000000,2020-01-26 22:53:29,64.0,,10.0,9.0,44.0,,2.0,136.0,A toolset for black-box hyperparameter optimisation.,2.0,10,False,2020-01-26 23:08:16.000,1.0.1,7.0,hypertunity,,,,,56.0,3.0,3.0,https://pypi.org/project/hypertunity,2020-01-26 23:08:16.000,,56.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +915,traintool,jrieke/traintool,ml-experiments,,https://github.com/jrieke/traintool,https://github.com/jrieke/traintool,Apache-2.0,2020-09-30 22:23:05.000,2021-03-12 01:44:04.000000,2021-03-12 01:43:14,122.0,,1.0,4.0,,,,12.0,Train off-the-shelf machine learning models in one line of code.,,9,False,2020-11-02 02:25:32.000,0.0.3,3.0,traintool,,,"['pytorch', 'tensorflow', 'sklearn']",,40.0,1.0,1.0,https://pypi.org/project/traintool,2020-11-02 02:25:32.000,,40.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +916,pyrtfolio,alvarobartt/pyrtfolio,financial-data,,https://github.com/alvarobartt/pyrtfolio,https://github.com/alvarobartt/pyrtfolio,GPL-3.0,2019-10-06 20:22:12.000,2022-05-14 21:32:20.000000,2020-11-20 09:58:41,19.0,,25.0,7.0,2.0,2.0,6.0,147.0,Python package to generate stock portfolios.,4.0,8,False,2020-03-13 20:04:08.000,0.2,3.0,pyrtfolio,,,,,19.0,1.0,1.0,https://pypi.org/project/pyrtfolio,2020-03-13 20:31:47.000,,19.0,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, +917,tslumen,hsbc/tslumen,time-series-data,,https://github.com/hsbc/tslumen,https://github.com/hsbc/tslumen,Apache-2.0,2022-11-09 14:06:09.000,2024-08-11 23:52:21.000000,2022-11-22 16:44:39,2.0,,7.0,7.0,2.0,1.0,,67.0,A library for Time Series EDA (exploratory data analysis).,2.0,8,False,2022-11-22 17:50:34.944,0.0.1,1.0,tslumen,conda-forge/tslumen,,,,53.0,1.0,,https://pypi.org/project/tslumen,2022-11-22 17:50:34.944,1.0,53.0,https://anaconda.org/conda-forge/tslumen,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,, diff --git a/latest-changes.md b/latest-changes.md index 6c4c485..1009383 100644 --- a/latest-changes.md +++ b/latest-changes.md @@ -2,29 +2,35 @@ _Projects that have a higher project-quality score compared to the last update. There might be a variety of reasons, such as increased downloads or code activity._ -- SageMaker SDK (πŸ₯‡41 Β· ⭐ 2.1K Β· πŸ“ˆ) - A library for training and deploying machine learning.. Apache-2 -- imageio (πŸ₯‡38 Β· ⭐ 1.4K Β· πŸ“ˆ) - Python library for reading and writing image data. BSD-2 -- deepface (πŸ₯ˆ37 Β· ⭐ 11K Β· πŸ“ˆ) - A Lightweight Face Recognition and Facial Attribute Analysis (Age,.. MIT -- plotnine (πŸ₯ˆ37 Β· ⭐ 3.9K Β· πŸ“ˆ) - A Grammar of Graphics for Python. MIT -- ivy (πŸ₯ˆ36 Β· ⭐ 14K Β· πŸ“ˆ) - The Unified AI Framework. Apache-2 -- ParlAI (πŸ₯ˆ32 Β· ⭐ 10K Β· πŸ’€) - A framework for training and evaluating AI models on a variety of.. MIT -- pygraphistry (πŸ₯ˆ29 Β· ⭐ 2.1K Β· πŸ“ˆ) - PyGraphistry is a Python library to quickly load,.. BSD-3 -- quinn (πŸ₯‰26 Β· ⭐ 580 Β· πŸ“ˆ) - pyspark methods to enhance developer productivity. Apache-2 -- Lucid (πŸ₯‰25 Β· ⭐ 4.6K Β· πŸ’€) - A collection of infrastructure and tools for research in.. Apache-2 -- pymdp (πŸ₯‰19 Β· ⭐ 400 Β· πŸ“ˆ) - A Python implementation of active inference for Markov Decision Processes. MIT +- nltk (πŸ₯‡45 Β· ⭐ 13K Β· πŸ“ˆ) - Suite of libraries and programs for symbolic and statistical natural.. Apache-2 +- Optuna (πŸ₯‡43 Β· ⭐ 10K Β· πŸ“ˆ) - A hyperparameter optimization framework. MIT +- Netron (πŸ₯‡37 Β· ⭐ 27K Β· πŸ“ˆ) - Visualizer for neural network, deep learning and machine.. MIT +- Datasette (πŸ₯‡36 Β· ⭐ 9.2K Β· πŸ“ˆ) - An open source multi-tool for exploring and publishing data. Apache-2 +- Autograd (πŸ₯‡36 Β· ⭐ 6.9K Β· πŸ“ˆ) - Efficiently computes derivatives of NumPy code. MIT +- bt (πŸ₯‡31 Β· ⭐ 2.2K Β· πŸ“ˆ) - bt - flexible backtesting for Python. MIT +- python-soundfile (πŸ₯‰29 Β· ⭐ 700 Β· πŸ“ˆ) - SoundFile is an audio library based on libsndfile, CFFI,.. BSD-3 +- miceforest (πŸ₯‡26 Β· ⭐ 330 Β· πŸ“ˆ) - Multiple Imputation with LightGBM in Python. MIT +- dabl (πŸ₯‰20 Β· ⭐ 720 Β· πŸ’€) - Data Analysis Baseline Library. BSD-3 +- MXBoard (πŸ₯‰20 Β· ⭐ 320 Β· πŸ’€) - Logging MXNet data for visualization in TensorBoard. Apache-2 ## πŸ“‰ Trending Down _Projects that have a lower project-quality score compared to the last update. There might be a variety of reasons such as decreased downloads or code activity._ -- SymPy (πŸ₯‡47 Β· ⭐ 12K Β· πŸ“‰) - A computer algebra system written in pure Python. BSD-3 -- flair (πŸ₯‡37 Β· ⭐ 14K Β· πŸ“‰) - A very simple framework for state-of-the-art Natural Language.. MIT -- wordcloud (πŸ₯ˆ32 Β· ⭐ 10K Β· πŸ“‰) - A little word cloud generator in Python. MIT -- SciSpacy (πŸ₯ˆ28 Β· ⭐ 1.6K Β· πŸ“‰) - A full spaCy pipeline and models for scientific/biomedical.. Apache-2 -- TF-Agents (πŸ₯ˆ26 Β· ⭐ 2.7K Β· πŸ“‰) - TF-Agents: A reliable, scalable and easy to use.. Apache-2 -- TensorForce (πŸ₯‰24 Β· ⭐ 3.3K Β· πŸ“‰) - Tensorforce: a TensorFlow library for applied.. Apache-2 -- Neural Tangents (πŸ₯‰24 Β· ⭐ 2.2K Β· πŸ“‰) - Fast and Easy Infinite Neural Networks in Python. Apache-2 -- AugLy (πŸ₯‰23 Β· ⭐ 4.9K Β· πŸ“‰) - A data augmentations library for audio, image, text, and video. MIT -- ExplainX.ai (πŸ₯‰15 Β· ⭐ 400 Β· πŸ“‰) - Explainable AI framework for data scientists. Explain & debug any.. MIT -- NeuralCompression (πŸ₯‰14 Β· ⭐ 480 Β· πŸ“‰) - A collection of tools for neural compression enthusiasts. MIT +- tensorflow-probability (πŸ₯‡35 Β· ⭐ 4.2K Β· πŸ“‰) - Probabilistic reasoning and statistical analysis in.. Apache-2 +- Graphviz (πŸ₯ˆ34 Β· ⭐ 1.6K Β· πŸ“‰) - Simple Python interface for Graphviz. MIT +- SpeechRecognition (πŸ₯ˆ33 Β· ⭐ 8.3K Β· πŸ“‰) - Speech recognition module for Python, supporting.. BSD-3 +- OpenNMT (πŸ₯ˆ32 Β· ⭐ 6.7K Β· πŸ“‰) - Open Source Neural Machine Translation and (Large) Language.. MIT +- tensorflow-hub (πŸ₯ˆ32 Β· ⭐ 3.5K Β· πŸ“‰) - A library for transfer learning by reusing parts of.. Apache-2 +- TF Model Optimization (πŸ₯ˆ28 Β· ⭐ 1.5K Β· πŸ“‰) - A toolkit to optimize ML models for deployment for.. Apache-2 +- data-validation (πŸ₯‰26 Β· ⭐ 760 Β· πŸ“‰) - Library for exploring and validating machine learning.. Apache-2 +- TF Recommenders (πŸ₯‰24 Β· ⭐ 1.8K Β· πŸ“‰) - TensorFlow Recommenders is a library for building.. Apache-2 +- pandas-ai (πŸ₯‰23 Β· ⭐ 13K Β· πŸ“‰) - Chat with your database (SQL, CSV, pandas, polars,.. ❗Unlicensed +- TensorFrames (πŸ₯‰16 Β· ⭐ 720 Β· πŸ’€) - Tensorflow wrapper for DataFrames on Apache Spark. Apache-2 + +## βž• Added Projects + +_Projects that were recently added to this best-of list._ + +- Runhouse (πŸ₯‰24 Β· ⭐ 960 Β· βž•) - Orchestrate heterogeneous ML workloads in Python, like PyTorch.. Apache-2