From ca69ee21fd510c46610ac4e16724fccb416323d7 Mon Sep 17 00:00:00 2001 From: LukasMasuch Date: Thu, 24 Oct 2024 15:06:23 +0000 Subject: [PATCH] Update best-of list for version 2024.10.24 --- README.md | 3615 ++++++++++++++++--------------- history/2024-10-24_changes.md | 30 + history/2024-10-24_projects.csv | 920 ++++++++ latest-changes.md | 40 +- 4 files changed, 2781 insertions(+), 1824 deletions(-) create mode 100644 history/2024-10-24_changes.md create mode 100644 history/2024-10-24_projects.csv diff --git a/README.md b/README.md index 9d1223d..e167a01 100644 --- a/README.md +++ b/README.md @@ -17,7 +17,7 @@

-This curated list contains 920 awesome open-source projects with a total of 4.6M 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! +This curated list contains 920 awesome open-source projects with a total of 4.7M 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! --- @@ -99,61 +99,61 @@ This curated list contains 920 awesome open-source projects with a total of 4.6M _General-purpose machine learning and deep learning frameworks._ -
PyTorch (πŸ₯‡56 Β· ⭐ 83K) - 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’» 5.2K Β· πŸ”€ 22K Β· πŸ“₯ 60K Β· πŸ“¦ 540K Β· πŸ“‹ 47K - 32% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/tensorflow/tensorflow) (πŸ‘¨β€πŸ’» 4.7K Β· πŸ”€ 74K Β· πŸ“¦ 420K Β· πŸ“‹ 44K - 12% open Β· ⏱️ 24.10.2024): ``` - git clone https://github.com/pytorch/pytorch + git clone https://github.com/tensorflow/tensorflow ``` -- [PyPi](https://pypi.org/project/torch) (πŸ“₯ 34M / month Β· πŸ“¦ 19K Β· ⏱️ 04.09.2024): +- [PyPi](https://pypi.org/project/tensorflow) (πŸ“₯ 19M / month Β· πŸ“¦ 8K Β· ⏱️ 16.10.2024): ``` - pip install torch + pip install tensorflow ``` -- [Conda](https://anaconda.org/pytorch/pytorch) (πŸ“₯ 24M Β· ⏱️ 03.09.2024): +- [Conda](https://anaconda.org/conda-forge/tensorflow) (πŸ“₯ 5M Β· ⏱️ 17.10.2024): ``` - conda install -c pytorch pytorch + conda install -c conda-forge tensorflow + ``` +- [Docker Hub](https://hub.docker.com/r/tensorflow/tensorflow) (πŸ“₯ 78M Β· ⭐ 2.6K Β· ⏱️ 24.10.2024): + ``` + docker pull tensorflow/tensorflow ```
-
Tensorflow (πŸ₯‡55 Β· ⭐ 190K) - An Open Source Machine Learning Framework for Everyone. Apache-2 +
PyTorch (πŸ₯‡55 Β· ⭐ 83K Β· πŸ“‰) - Tensors and Dynamic neural networks in Python with strong GPU.. BSD-3 -- [GitHub](https://github.com/tensorflow/tensorflow) (πŸ‘¨β€πŸ’» 4.7K Β· πŸ”€ 74K Β· πŸ“¦ 420K Β· πŸ“‹ 43K - 11% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/pytorch/pytorch) (πŸ‘¨β€πŸ’» 5.2K Β· πŸ”€ 22K Β· πŸ“₯ 62K Β· πŸ“¦ 550K Β· πŸ“‹ 47K - 32% open Β· ⏱️ 24.10.2024): ``` - git clone https://github.com/tensorflow/tensorflow - ``` -- [PyPi](https://pypi.org/project/tensorflow) (πŸ“₯ 18M / month Β· πŸ“¦ 8K Β· ⏱️ 07.10.2024): - ``` - pip install tensorflow + git clone https://github.com/pytorch/pytorch ``` -- [Conda](https://anaconda.org/conda-forge/tensorflow) (πŸ“₯ 5M Β· ⏱️ 31.08.2024): +- [PyPi](https://pypi.org/project/torch) (πŸ“₯ 35M / month Β· πŸ“¦ 19K Β· ⏱️ 17.10.2024): ``` - conda install -c conda-forge tensorflow + pip install torch ``` -- [Docker Hub](https://hub.docker.com/r/tensorflow/tensorflow) (πŸ“₯ 78M Β· ⭐ 2.6K Β· ⏱️ 10.10.2024): +- [Conda](https://anaconda.org/pytorch/pytorch) (πŸ“₯ 24M Β· ⏱️ 16.10.2024): ``` - docker pull tensorflow/tensorflow + conda install -c pytorch pytorch ```
scikit-learn (πŸ₯‡52 Β· ⭐ 60K) - scikit-learn: machine learning in Python. BSD-3 -- [GitHub](https://github.com/scikit-learn/scikit-learn) (πŸ‘¨β€πŸ’» 3.2K Β· πŸ”€ 25K Β· πŸ“₯ 1K Β· πŸ“¦ 910K Β· πŸ“‹ 12K - 18% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/scikit-learn/scikit-learn) (πŸ‘¨β€πŸ’» 3.2K Β· πŸ”€ 25K Β· πŸ“₯ 1K Β· πŸ“¦ 930K Β· πŸ“‹ 12K - 17% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/scikit-learn/scikit-learn ``` -- [PyPi](https://pypi.org/project/scikit-learn) (πŸ“₯ 79M / month Β· πŸ“¦ 25K Β· ⏱️ 11.09.2024): +- [PyPi](https://pypi.org/project/scikit-learn) (πŸ“₯ 82M / month Β· πŸ“¦ 25K Β· ⏱️ 11.09.2024): ``` pip install scikit-learn ``` -- [Conda](https://anaconda.org/conda-forge/scikit-learn) (πŸ“₯ 31M Β· ⏱️ 11.09.2024): +- [Conda](https://anaconda.org/conda-forge/scikit-learn) (πŸ“₯ 32M Β· ⏱️ 11.09.2024): ``` conda install -c conda-forge scikit-learn ```
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 - 2% open Β· ⏱️ 08.10.2024): +- [GitHub](https://github.com/keras-team/keras) (πŸ‘¨β€πŸ’» 1.3K Β· πŸ”€ 19K Β· πŸ“‹ 12K - 2% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/keras-team/keras @@ -162,58 +162,74 @@ _General-purpose machine learning and deep learning frameworks._ ``` pip install keras ``` -- [Conda](https://anaconda.org/conda-forge/keras) (πŸ“₯ 3.7M Β· ⏱️ 07.10.2024): +- [Conda](https://anaconda.org/conda-forge/keras) (πŸ“₯ 3.8M Β· ⏱️ 07.10.2024): ``` conda install -c conda-forge keras ```
XGBoost (πŸ₯‡46 Β· ⭐ 26K) - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or.. Apache-2 -- [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· ⏱️ 09.10.2024): +- [GitHub](https://github.com/dmlc/xgboost) (πŸ‘¨β€πŸ’» 650 Β· πŸ”€ 8.7K Β· πŸ“₯ 11K Β· πŸ“¦ 110K Β· πŸ“‹ 5.4K - 8% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/dmlc/xgboost ``` -- [PyPi](https://pypi.org/project/xgboost) (πŸ“₯ 27M / month Β· πŸ“¦ 2K Β· ⏱️ 31.07.2024): +- [PyPi](https://pypi.org/project/xgboost) (πŸ“₯ 29M / month Β· πŸ“¦ 2K Β· ⏱️ 23.10.2024): ``` pip install xgboost ``` -- [Conda](https://anaconda.org/conda-forge/xgboost) (πŸ“₯ 5.3M Β· ⏱️ 29.09.2024): +- [Conda](https://anaconda.org/conda-forge/xgboost) (πŸ“₯ 5.4M Β· ⏱️ 29.09.2024): ``` conda install -c conda-forge xgboost ```
+
PySpark (πŸ₯‡45 Β· ⭐ 40K) - Apache Spark Python API. Apache-2 + +- [GitHub](https://github.com/apache/spark) (πŸ‘¨β€πŸ’» 3.1K Β· πŸ”€ 28K Β· ⏱️ 24.10.2024): + + ``` + git clone https://github.com/apache/spark + ``` +- [PyPi](https://pypi.org/project/pyspark) (πŸ“₯ 31M / month Β· πŸ“¦ 1.5K Β· ⏱️ 27.09.2024): + ``` + pip install pyspark + ``` +- [Conda](https://anaconda.org/conda-forge/pyspark) (πŸ“₯ 3.5M Β· ⏱️ 03.03.2024): + ``` + conda install -c conda-forge pyspark + ``` +
jax (πŸ₯‡45 Β· ⭐ 30K) - Composable transformations of Python+NumPy programs: differentiate,.. Apache-2 -- [GitHub](https://github.com/jax-ml/jax) (πŸ‘¨β€πŸ’» 760 Β· πŸ”€ 2.8K Β· πŸ“¦ 31K Β· πŸ“‹ 5.6K - 24% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/jax-ml/jax) (πŸ‘¨β€πŸ’» 770 Β· πŸ”€ 2.8K Β· πŸ“¦ 32K Β· πŸ“‹ 5.7K - 24% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/google/jax ``` -- [PyPi](https://pypi.org/project/jax) (πŸ“₯ 4M / month Β· πŸ“¦ 1.9K Β· ⏱️ 04.10.2024): +- [PyPi](https://pypi.org/project/jax) (πŸ“₯ 4.1M / month Β· πŸ“¦ 1.9K Β· ⏱️ 22.10.2024): ``` pip install jax ``` -- [Conda](https://anaconda.org/conda-forge/jaxlib) (πŸ“₯ 1.7M Β· ⏱️ 02.10.2024): +- [Conda](https://anaconda.org/conda-forge/jaxlib) (πŸ“₯ 1.8M Β· ⏱️ 24.10.2024): ``` conda install -c conda-forge jaxlib ```
-
PaddlePaddle (πŸ₯‡45 Β· ⭐ 22K Β· πŸ“‰) - PArallel Distributed Deep LEarning: Machine Learning.. Apache-2 +
PaddlePaddle (πŸ₯‡45 Β· ⭐ 22K) - PArallel Distributed Deep LEarning: Machine Learning.. Apache-2 -- [GitHub](https://github.com/PaddlePaddle/Paddle) (πŸ‘¨β€πŸ’» 1.3K Β· πŸ”€ 5.6K Β· πŸ“₯ 15K Β· πŸ“¦ 6K Β· πŸ“‹ 19K - 8% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/PaddlePaddle/Paddle) (πŸ‘¨β€πŸ’» 1.3K Β· πŸ”€ 5.6K Β· πŸ“₯ 15K Β· πŸ“¦ 6.1K Β· πŸ“‹ 19K - 8% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/PaddlePaddle/Paddle ``` -- [PyPi](https://pypi.org/project/paddlepaddle) (πŸ“₯ 380K / month Β· πŸ“¦ 180 Β· ⏱️ 13.09.2024): +- [PyPi](https://pypi.org/project/paddlepaddle) (πŸ“₯ 330K / month Β· πŸ“¦ 180 Β· ⏱️ 13.09.2024): ``` pip install paddlepaddle ```
StatsModels (πŸ₯‡45 Β· ⭐ 10K) - Statsmodels: statistical modeling and econometrics in Python. BSD-3 -- [GitHub](https://github.com/statsmodels/statsmodels) (πŸ‘¨β€πŸ’» 440 Β· πŸ”€ 2.9K Β· πŸ“₯ 34 Β· πŸ“¦ 140K Β· πŸ“‹ 5.6K - 50% open Β· ⏱️ 08.10.2024): +- [GitHub](https://github.com/statsmodels/statsmodels) (πŸ‘¨β€πŸ’» 450 Β· πŸ”€ 2.9K Β· πŸ“₯ 35 Β· πŸ“¦ 140K Β· πŸ“‹ 5.6K - 50% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/statsmodels/statsmodels @@ -227,25 +243,9 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge statsmodels ```
-
PySpark (πŸ₯ˆ44 Β· ⭐ 39K Β· πŸ“‰) - Apache Spark Python API. Apache-2 +
pytorch-lightning (πŸ₯ˆ44 Β· ⭐ 28K) - Pretrain, finetune ANY AI model of ANY size on.. Apache-2 -- [GitHub](https://github.com/apache/spark) (πŸ‘¨β€πŸ’» 3.1K Β· πŸ”€ 28K Β· ⏱️ 10.10.2024): - - ``` - git clone https://github.com/apache/spark - ``` -- [PyPi](https://pypi.org/project/pyspark) (πŸ“₯ 30M / month Β· πŸ“¦ 1.5K Β· ⏱️ 27.09.2024): - ``` - pip install pyspark - ``` -- [Conda](https://anaconda.org/conda-forge/pyspark) (πŸ“₯ 3.5M Β· ⏱️ 03.03.2024): - ``` - conda install -c conda-forge pyspark - ``` -
-
pytorch-lightning (πŸ₯ˆ44 Β· ⭐ 28K) - Pretrain, finetune and deploy AI models on multiple.. Apache-2 - -- [GitHub](https://github.com/Lightning-AI/pytorch-lightning) (πŸ‘¨β€πŸ’» 970 Β· πŸ”€ 3.4K Β· πŸ“₯ 9.2K Β· πŸ“¦ 37K Β· πŸ“‹ 7.1K - 11% open Β· ⏱️ 08.10.2024): +- [GitHub](https://github.com/Lightning-AI/pytorch-lightning) (πŸ‘¨β€πŸ’» 980 Β· πŸ”€ 3.4K Β· πŸ“₯ 9.3K Β· πŸ“¦ 38K Β· πŸ“‹ 7.1K - 11% open Β· ⏱️ 21.10.2024): ``` git clone https://github.com/Lightning-AI/lightning @@ -261,23 +261,23 @@ _General-purpose machine learning and deep learning frameworks._
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’» 320 Β· πŸ”€ 3.8K Β· πŸ“₯ 240K Β· πŸ“¦ 38K Β· πŸ“‹ 3.4K - 10% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/microsoft/LightGBM) (πŸ‘¨β€πŸ’» 320 Β· πŸ”€ 3.8K Β· πŸ“₯ 240K Β· πŸ“¦ 39K Β· πŸ“‹ 3.4K - 10% open Β· ⏱️ 21.10.2024): ``` git clone https://github.com/microsoft/LightGBM ``` -- [PyPi](https://pypi.org/project/lightgbm) (πŸ“₯ 9.7M / month Β· πŸ“¦ 1.1K Β· ⏱️ 26.07.2024): +- [PyPi](https://pypi.org/project/lightgbm) (πŸ“₯ 9.6M / month Β· πŸ“¦ 1.1K Β· ⏱️ 26.07.2024): ``` pip install lightgbm ``` -- [Conda](https://anaconda.org/conda-forge/lightgbm) (πŸ“₯ 2.7M Β· ⏱️ 10.10.2024): +- [Conda](https://anaconda.org/conda-forge/lightgbm) (πŸ“₯ 2.8M Β· ⏱️ 10.10.2024): ``` conda install -c conda-forge lightgbm ```
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Catboost (πŸ₯ˆ42 Β· ⭐ 8K) - A fast, scalable, high performance Gradient Boosting on Decision.. Apache-2 +
Catboost (πŸ₯ˆ42 Β· ⭐ 8.1K) - A fast, scalable, high performance Gradient Boosting on Decision.. Apache-2 -- [GitHub](https://github.com/catboost/catboost) (πŸ‘¨β€πŸ’» 1.3K Β· πŸ”€ 1.2K Β· πŸ“₯ 310K Β· πŸ“¦ 15 Β· πŸ“‹ 2.3K - 23% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/catboost/catboost) (πŸ‘¨β€πŸ’» 1.3K Β· πŸ”€ 1.2K Β· πŸ“₯ 320K Β· πŸ“¦ 15 Β· πŸ“‹ 2.3K - 23% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/catboost/catboost @@ -291,14 +291,14 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge catboost ```
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Fastai (πŸ₯ˆ40 Β· ⭐ 26K) - The fastai deep learning library. Apache-2 +
Fastai (πŸ₯ˆ41 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“¦ 19K Β· πŸ“‹ 1.8K - 12% open Β· ⏱️ 25.09.2024): +- [GitHub](https://github.com/fastai/fastai) (πŸ‘¨β€πŸ’» 670 Β· πŸ”€ 7.6K Β· πŸ“¦ 19K Β· πŸ“‹ 1.8K - 12% open Β· ⏱️ 19.10.2024): ``` git clone https://github.com/fastai/fastai ``` -- [PyPi](https://pypi.org/project/fastai) (πŸ“₯ 390K / month Β· πŸ“¦ 300 Β· ⏱️ 27.08.2024): +- [PyPi](https://pypi.org/project/fastai) (πŸ“₯ 460K / month Β· πŸ“¦ 310 Β· ⏱️ 19.10.2024): ``` pip install fastai ``` @@ -310,11 +310,11 @@ _General-purpose machine learning and deep learning frameworks._ ``` git clone https://github.com/jina-ai/jina ``` -- [PyPi](https://pypi.org/project/jina) (πŸ“₯ 130K / month Β· πŸ“¦ 27 Β· ⏱️ 01.10.2024): +- [PyPi](https://pypi.org/project/jina) (πŸ“₯ 160K / month Β· πŸ“¦ 27 Β· ⏱️ 01.10.2024): ``` pip install jina ``` -- [Conda](https://anaconda.org/conda-forge/jina-core) (πŸ“₯ 76K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/jina-core) (πŸ“₯ 77K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge jina-core ``` @@ -325,68 +325,56 @@ _General-purpose machine learning and deep learning frameworks._
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· ⏱️ 10.10.2024): +- [GitHub](https://github.com/apache/flink) (πŸ‘¨β€πŸ’» 1.9K Β· πŸ”€ 13K Β· πŸ“¦ 21 Β· ⏱️ 24.10.2024): ``` git clone https://github.com/apache/flink ``` -- [PyPi](https://pypi.org/project/apache-flink) (πŸ“₯ 220K / month Β· πŸ“¦ 35 Β· ⏱️ 01.08.2024): +- [PyPi](https://pypi.org/project/apache-flink) (πŸ“₯ 300K / month Β· πŸ“¦ 35 Β· ⏱️ 01.08.2024): ``` pip install apache-flink ```
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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“¦ 16K Β· πŸ“‹ 2.8K - 24% open Β· ⏱️ 15.01.2024): - - ``` - git clone https://github.com/Theano/Theano - ``` -- [PyPi](https://pypi.org/project/theano) (πŸ“₯ 95K / month Β· πŸ“¦ 170 Β· ⏱️ 27.07.2020): - ``` - pip install theano - ``` -- [Conda](https://anaconda.org/conda-forge/theano) (πŸ“₯ 2.5M Β· ⏱️ 16.06.2023): - ``` - conda install -c conda-forge theano - ``` -
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Flax (πŸ₯ˆ37 Β· ⭐ 6K) - Flax is a neural network library for JAX that is designed for.. Apache-2 +
Flax (πŸ₯ˆ38 Β· ⭐ 6.1K) - 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“₯ 55 Β· πŸ“¦ 9.5K Β· πŸ“‹ 1K - 26% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/google/flax) (πŸ‘¨β€πŸ’» 240 Β· πŸ”€ 640 Β· πŸ“₯ 55 Β· πŸ“¦ 9.7K Β· πŸ“‹ 1K - 28% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/google/flax ``` -- [PyPi](https://pypi.org/project/flax) (πŸ“₯ 840K / month Β· πŸ“¦ 470 Β· ⏱️ 27.08.2024): +- [PyPi](https://pypi.org/project/flax) (πŸ“₯ 870K / month Β· πŸ“¦ 470 Β· ⏱️ 16.10.2024): ``` pip install flax ``` -- [Conda](https://anaconda.org/conda-forge/flax) (πŸ“₯ 73K Β· ⏱️ 27.08.2024): +- [Conda](https://anaconda.org/conda-forge/flax) (πŸ“₯ 74K Β· ⏱️ 24.10.2024): ``` conda install -c conda-forge flax ```
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ivy (πŸ₯ˆ36 Β· ⭐ 14K) - Convert Machine Learning Code Between Frameworks. Apache-2 +
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/ivy-llc/ivy) (πŸ‘¨β€πŸ’» 1.5K Β· πŸ”€ 5.8K Β· πŸ“‹ 17K - 5% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/Theano/Theano) (πŸ‘¨β€πŸ’» 390 Β· πŸ”€ 2.5K Β· πŸ“¦ 16K Β· πŸ“‹ 2.8K - 25% open Β· ⏱️ 15.01.2024): ``` - git clone https://github.com/unifyai/ivy + git clone https://github.com/Theano/Theano + ``` +- [PyPi](https://pypi.org/project/theano) (πŸ“₯ 92K / month Β· πŸ“¦ 170 Β· ⏱️ 27.07.2020): + ``` + pip install theano ``` -- [PyPi](https://pypi.org/project/ivy) (πŸ“₯ 5.5K / month Β· πŸ“¦ 12 Β· ⏱️ 25.09.2024): +- [Conda](https://anaconda.org/conda-forge/theano) (πŸ“₯ 2.5M Β· ⏱️ 16.06.2023): ``` - pip install ivy + conda install -c conda-forge theano ```
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einops (πŸ₯ˆ36 Β· ⭐ 8.4K) - Flexible and powerful tensor operations for readable and reliable code.. MIT +
einops (πŸ₯ˆ36 Β· ⭐ 8.5K) - Flexible and powerful tensor operations for readable and reliable code.. MIT -- [GitHub](https://github.com/arogozhnikov/einops) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 340 Β· πŸ“¦ 47K Β· πŸ“‹ 180 - 19% open Β· ⏱️ 21.09.2024): +- [GitHub](https://github.com/arogozhnikov/einops) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 340 Β· πŸ“¦ 49K Β· πŸ“‹ 180 - 19% open Β· ⏱️ 13.10.2024): ``` git clone https://github.com/arogozhnikov/einops ``` -- [PyPi](https://pypi.org/project/einops) (πŸ“₯ 5.2M / month Β· πŸ“¦ 2K Β· ⏱️ 28.04.2024): +- [PyPi](https://pypi.org/project/einops) (πŸ“₯ 5.5M / month Β· πŸ“¦ 2K Β· ⏱️ 28.04.2024): ``` pip install einops ``` @@ -397,12 +385,12 @@ _General-purpose machine learning and deep learning frameworks._
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’» 64 Β· πŸ”€ 280 Β· πŸ“₯ 380 Β· πŸ“¦ 54K Β· πŸ“‹ 150 - 12% open Β· ⏱️ 30.09.2024): +- [GitHub](https://github.com/explosion/thinc) (πŸ‘¨β€πŸ’» 64 Β· πŸ”€ 280 Β· πŸ“₯ 390 Β· πŸ“¦ 55K Β· πŸ“‹ 150 - 12% open Β· ⏱️ 30.09.2024): ``` git clone https://github.com/explosion/thinc ``` -- [PyPi](https://pypi.org/project/thinc) (πŸ“₯ 11M / month Β· πŸ“¦ 140 Β· ⏱️ 01.10.2024): +- [PyPi](https://pypi.org/project/thinc) (πŸ“₯ 13M / month Β· πŸ“¦ 140 Β· ⏱️ 01.10.2024): ``` pip install thinc ``` @@ -411,46 +399,30 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge thinc ```
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Vowpal Wabbit (πŸ₯ˆ35 Β· ⭐ 8.5K) - Vowpal Wabbit is a machine learning system which pushes the.. BSD-3 - -- [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/VowpalWabbit/vowpal_wabbit - ``` -- [PyPi](https://pypi.org/project/vowpalwabbit) (πŸ“₯ 56K / month Β· πŸ“¦ 40 Β· ⏱️ 08.08.2024): - ``` - pip install vowpalwabbit - ``` -- [Conda](https://anaconda.org/conda-forge/vowpalwabbit) (πŸ“₯ 230K Β· ⏱️ 05.09.2024): - ``` - conda install -c conda-forge vowpalwabbit - ``` -
mlpack (πŸ₯ˆ35 Β· ⭐ 5.1K) - mlpack: a fast, header-only C++ machine learning library. BSD-3 -- [GitHub](https://github.com/mlpack/mlpack) (πŸ‘¨β€πŸ’» 320 Β· πŸ”€ 1.6K Β· πŸ“‹ 1.6K - 1% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/mlpack/mlpack) (πŸ‘¨β€πŸ’» 320 Β· πŸ”€ 1.6K Β· πŸ“‹ 1.6K - 1% open Β· ⏱️ 22.10.2024): ``` git clone https://github.com/mlpack/mlpack ``` -- [PyPi](https://pypi.org/project/mlpack) (πŸ“₯ 8.4K / month Β· πŸ“¦ 4 Β· ⏱️ 20.09.2024): +- [PyPi](https://pypi.org/project/mlpack) (πŸ“₯ 15K / month Β· πŸ“¦ 4 Β· ⏱️ 20.09.2024): ``` pip install mlpack ``` -- [Conda](https://anaconda.org/conda-forge/mlpack) (πŸ“₯ 250K Β· ⏱️ 22.09.2024): +- [Conda](https://anaconda.org/conda-forge/mlpack) (πŸ“₯ 260K Β· ⏱️ 22.09.2024): ``` conda install -c conda-forge mlpack ```
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’» 660 Β· πŸ”€ 610 Β· πŸ“¦ 3.3K Β· πŸ“‹ 1.4K - 10% open Β· ⏱️ 02.10.2024): +- [GitHub](https://github.com/pytorch/ignite) (πŸ‘¨β€πŸ’» 670 Β· πŸ”€ 620 Β· πŸ“¦ 3.3K Β· πŸ“‹ 1.4K - 10% open Β· ⏱️ 21.10.2024): ``` git clone https://github.com/pytorch/ignite ``` -- [PyPi](https://pypi.org/project/pytorch-ignite) (πŸ“₯ 180K / month Β· πŸ“¦ 98 Β· ⏱️ 10.10.2024): +- [PyPi](https://pypi.org/project/pytorch-ignite) (πŸ“₯ 250K / month Β· πŸ“¦ 98 Β· ⏱️ 24.10.2024): ``` pip install pytorch-ignite ``` @@ -459,14 +431,30 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c pytorch ignite ```
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Vowpal Wabbit (πŸ₯ˆ34 Β· ⭐ 8.5K) - Vowpal Wabbit is a machine learning system which pushes the.. BSD-3 + +- [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/VowpalWabbit/vowpal_wabbit + ``` +- [PyPi](https://pypi.org/project/vowpalwabbit) (πŸ“₯ 59K / month Β· πŸ“¦ 40 Β· ⏱️ 08.08.2024): + ``` + pip install vowpalwabbit + ``` +- [Conda](https://anaconda.org/conda-forge/vowpalwabbit) (πŸ“₯ 230K Β· ⏱️ 05.09.2024): + ``` + conda install -c conda-forge vowpalwabbit + ``` +
Ludwig (πŸ₯‰33 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“¦ 270 Β· πŸ“‹ 1.1K - 32% open Β· ⏱️ 21.08.2024): +- [GitHub](https://github.com/ludwig-ai/ludwig) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 1.2K Β· πŸ“¦ 280 Β· πŸ“‹ 1.4K - 25% open Β· ⏱️ 17.10.2024): ``` git clone https://github.com/ludwig-ai/ludwig ``` -- [PyPi](https://pypi.org/project/ludwig) (πŸ“₯ 4.8K / month Β· πŸ“¦ 6 Β· ⏱️ 30.07.2024): +- [PyPi](https://pypi.org/project/ludwig) (πŸ“₯ 4.7K / month Β· πŸ“¦ 6 Β· ⏱️ 30.07.2024): ``` pip install ludwig ``` @@ -478,16 +466,16 @@ _General-purpose machine learning and deep learning frameworks._ ``` git clone https://github.com/deepmind/sonnet ``` -- [PyPi](https://pypi.org/project/dm-sonnet) (πŸ“₯ 22K / month Β· πŸ“¦ 19 Β· ⏱️ 02.01.2024): +- [PyPi](https://pypi.org/project/dm-sonnet) (πŸ“₯ 25K / month Β· πŸ“¦ 19 Β· ⏱️ 02.01.2024): ``` pip install dm-sonnet ``` -- [Conda](https://anaconda.org/conda-forge/sonnet) (πŸ“₯ 34K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/sonnet) (πŸ“₯ 35K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge sonnet ```
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skorch (πŸ₯‰31 Β· ⭐ 5.8K) - A scikit-learn compatible neural network library that wraps.. BSD-3 +
skorch (πŸ₯‰31 Β· ⭐ 5.9K) - A scikit-learn compatible neural network library that wraps.. BSD-3 - [GitHub](https://github.com/skorch-dev/skorch) (πŸ‘¨β€πŸ’» 62 Β· πŸ”€ 390 Β· πŸ“¦ 1.4K Β· πŸ“‹ 520 - 11% open Β· ⏱️ 20.09.2024): @@ -517,82 +505,82 @@ _General-purpose machine learning and deep learning frameworks._
Determined (πŸ₯‰31 Β· ⭐ 3K) - Determined is an open-source machine learning platform.. Apache-2 -- [GitHub](https://github.com/determined-ai/determined) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 350 Β· πŸ“₯ 12K Β· πŸ“‹ 460 - 23% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/determined-ai/determined) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 350 Β· πŸ“₯ 12K Β· πŸ“‹ 460 - 23% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/determined-ai/determined ``` -- [PyPi](https://pypi.org/project/determined) (πŸ“₯ 29K / month Β· πŸ“¦ 4 Β· ⏱️ 30.09.2024): +- [PyPi](https://pypi.org/project/determined) (πŸ“₯ 55K / month Β· πŸ“¦ 4 Β· ⏱️ 30.09.2024): ``` pip install determined ```
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tensorflow-upstream (πŸ₯‰31 Β· ⭐ 680) - TensorFlow ROCm port. Apache-2 +
Haiku (πŸ₯‰31 Β· ⭐ 2.9K) - JAX-based neural network library. Apache-2 -- [GitHub](https://github.com/ROCm/tensorflow-upstream) (πŸ‘¨β€πŸ’» 4.7K Β· πŸ”€ 94 Β· πŸ“₯ 24 Β· πŸ“‹ 380 - 24% open Β· ⏱️ 01.10.2024): +- [GitHub](https://github.com/google-deepmind/dm-haiku) (πŸ‘¨β€πŸ’» 83 Β· πŸ”€ 230 Β· πŸ“¦ 2.1K Β· πŸ“‹ 250 - 30% open Β· ⏱️ 24.10.2024): ``` - git clone https://github.com/ROCmSoftwarePlatform/tensorflow-upstream + git clone https://github.com/deepmind/dm-haiku ``` -- [PyPi](https://pypi.org/project/tensorflow-rocm) (πŸ“₯ 6.2K / month Β· πŸ“¦ 9 Β· ⏱️ 10.01.2024): +- [PyPi](https://pypi.org/project/dm-haiku) (πŸ“₯ 250K / month Β· πŸ“¦ 180 Β· ⏱️ 16.10.2024): ``` - pip install tensorflow-rocm + pip install dm-haiku + ``` +- [Conda](https://anaconda.org/conda-forge/dm-haiku) (πŸ“₯ 23K Β· ⏱️ 23.10.2024): + ``` + conda install -c conda-forge dm-haiku ```
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Haiku (πŸ₯‰30 Β· ⭐ 2.9K) - JAX-based neural network library. Apache-2 +
tensorflow-upstream (πŸ₯‰31 Β· ⭐ 680) - TensorFlow ROCm port. Apache-2 -- [GitHub](https://github.com/google-deepmind/dm-haiku) (πŸ‘¨β€πŸ’» 83 Β· πŸ”€ 230 Β· πŸ“¦ 2.1K Β· πŸ“‹ 250 - 30% open Β· ⏱️ 25.09.2024): +- [GitHub](https://github.com/ROCm/tensorflow-upstream) (πŸ‘¨β€πŸ’» 4.7K Β· πŸ”€ 94 Β· πŸ“₯ 25 Β· πŸ“‹ 380 - 24% open Β· ⏱️ 18.10.2024): ``` - git clone https://github.com/deepmind/dm-haiku - ``` -- [PyPi](https://pypi.org/project/dm-haiku) (πŸ“₯ 250K / month Β· πŸ“¦ 170 Β· ⏱️ 28.02.2024): - ``` - pip install dm-haiku + git clone https://github.com/ROCmSoftwarePlatform/tensorflow-upstream ``` -- [Conda](https://anaconda.org/conda-forge/dm-haiku) (πŸ“₯ 22K Β· ⏱️ 28.02.2024): +- [PyPi](https://pypi.org/project/tensorflow-rocm) (πŸ“₯ 7.4K / month Β· πŸ“¦ 9 Β· ⏱️ 10.01.2024): ``` - conda install -c conda-forge dm-haiku + pip install tensorflow-rocm ```
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Geomstats (πŸ₯‰30 Β· ⭐ 1.2K) - Computations and statistics on manifolds with geometric structures. MIT +
Geomstats (πŸ₯‰30 Β· ⭐ 1.3K) - Computations and statistics on manifolds with geometric structures. MIT - [GitHub](https://github.com/geomstats/geomstats) (πŸ‘¨β€πŸ’» 93 Β· πŸ”€ 240 Β· πŸ“¦ 120 Β· πŸ“‹ 560 - 37% open Β· ⏱️ 08.10.2024): ``` git clone https://github.com/geomstats/geomstats ``` -- [PyPi](https://pypi.org/project/geomstats) (πŸ“₯ 3.7K / month Β· πŸ“¦ 12 Β· ⏱️ 09.09.2024): +- [PyPi](https://pypi.org/project/geomstats) (πŸ“₯ 5K / month Β· πŸ“¦ 12 Β· ⏱️ 09.09.2024): ``` pip install geomstats ``` -- [Conda](https://anaconda.org/conda-forge/geomstats) (πŸ“₯ 3.8K Β· ⏱️ 10.09.2024): +- [Conda](https://anaconda.org/conda-forge/geomstats) (πŸ“₯ 3.9K Β· ⏱️ 10.09.2024): ``` conda install -c conda-forge geomstats ```
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ktrain (πŸ₯‰29 Β· ⭐ 1.2K) - ktrain is a Python library that makes deep learning and AI more.. Apache-2 +
Neural Network Libraries (πŸ₯‰29 Β· ⭐ 2.7K) - Neural Network Libraries. Apache-2 -- [GitHub](https://github.com/amaiya/ktrain) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 270 Β· πŸ“¦ 560 Β· πŸ“‹ 500 - 0% open Β· ⏱️ 09.07.2024): +- [GitHub](https://github.com/sony/nnabla) (πŸ‘¨β€πŸ’» 76 Β· πŸ”€ 330 Β· πŸ“₯ 980 Β· πŸ“‹ 95 - 36% open Β· ⏱️ 24.09.2024): ``` - git clone https://github.com/amaiya/ktrain + git clone https://github.com/sony/nnabla ``` -- [PyPi](https://pypi.org/project/ktrain) (πŸ“₯ 14K / month Β· πŸ“¦ 4 Β· ⏱️ 19.06.2024): +- [PyPi](https://pypi.org/project/nnabla) (πŸ“₯ 15K / month Β· πŸ“¦ 44 Β· ⏱️ 29.05.2024): ``` - pip install ktrain + pip install nnabla ```
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Neural Network Libraries (πŸ₯‰28 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/sony/nnabla) (πŸ‘¨β€πŸ’» 76 Β· πŸ”€ 330 Β· πŸ“₯ 980 Β· πŸ“‹ 95 - 36% open Β· ⏱️ 24.09.2024): +- [GitHub](https://github.com/amaiya/ktrain) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 270 Β· πŸ“¦ 560 Β· πŸ“‹ 500 - 0% open Β· ⏱️ 09.07.2024): ``` - git clone https://github.com/sony/nnabla + git clone https://github.com/amaiya/ktrain ``` -- [PyPi](https://pypi.org/project/nnabla) (πŸ“₯ 7.5K / month Β· πŸ“¦ 44 Β· ⏱️ 29.05.2024): +- [PyPi](https://pypi.org/project/ktrain) (πŸ“₯ 16K / month Β· πŸ“¦ 4 Β· ⏱️ 19.06.2024): ``` - pip install nnabla + pip install ktrain ```
EvaDB (πŸ₯‰27 Β· ⭐ 2.6K Β· πŸ’€) - Database system for AI-powered apps. Apache-2 @@ -602,27 +590,39 @@ _General-purpose machine learning and deep learning frameworks._ ``` git clone https://github.com/georgia-tech-db/eva ``` -- [PyPi](https://pypi.org/project/evadb) (πŸ“₯ 1.9K / month Β· ⏱️ 19.11.2023): +- [PyPi](https://pypi.org/project/evadb) (πŸ“₯ 3.6K / month Β· ⏱️ 19.11.2023): ``` pip install evadb ```
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pyRiemann (πŸ₯‰27 Β· ⭐ 630 Β· πŸ“ˆ) - Machine learning for multivariate data through the.. BSD-3 +
pyRiemann (πŸ₯‰27 Β· ⭐ 630) - Machine learning for multivariate data through the Riemannian.. BSD-3 -- [GitHub](https://github.com/pyRiemann/pyRiemann) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 160 Β· πŸ“¦ 400 Β· πŸ“‹ 110 - 4% open Β· ⏱️ 05.10.2024): +- [GitHub](https://github.com/pyRiemann/pyRiemann) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 160 Β· πŸ“¦ 400 Β· πŸ“‹ 110 - 4% open Β· ⏱️ 22.10.2024): ``` git clone https://github.com/pyRiemann/pyRiemann ``` -- [PyPi](https://pypi.org/project/pyriemann) (πŸ“₯ 38K / month Β· πŸ“¦ 28 Β· ⏱️ 03.10.2024): +- [PyPi](https://pypi.org/project/pyriemann) (πŸ“₯ 40K / month Β· πŸ“¦ 28 Β· ⏱️ 03.10.2024): ``` pip install pyriemann ``` -- [Conda](https://anaconda.org/conda-forge/pyriemann) (πŸ“₯ 8.1K Β· ⏱️ 04.10.2024): +- [Conda](https://anaconda.org/conda-forge/pyriemann) (πŸ“₯ 8.3K Β· ⏱️ 04.10.2024): ``` conda install -c conda-forge pyriemann ```
+
Towhee (πŸ₯‰26 Β· ⭐ 3.2K) - Towhee is a framework that is dedicated to making neural data.. Apache-2 + +- [GitHub](https://github.com/towhee-io/towhee) (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 250 Β· πŸ“₯ 2.7K Β· πŸ“‹ 660 - 0% open Β· ⏱️ 18.10.2024): + + ``` + git clone https://github.com/towhee-io/towhee + ``` +- [PyPi](https://pypi.org/project/towhee) (πŸ“₯ 16K / month Β· ⏱️ 04.12.2023): + ``` + pip install towhee + ``` +
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): @@ -639,26 +639,14 @@ _General-purpose machine learning and deep learning frameworks._ docker pull shogun/shogun ```
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Towhee (πŸ₯‰25 Β· ⭐ 3.2K) - Towhee is a framework that is dedicated to making neural data.. Apache-2 - -- [GitHub](https://github.com/towhee-io/towhee) (πŸ‘¨β€πŸ’» 37 Β· πŸ”€ 250 Β· πŸ“₯ 2.7K Β· πŸ“‹ 660 - 0% open Β· ⏱️ 10.10.2024): - - ``` - git clone https://github.com/towhee-io/towhee - ``` -- [PyPi](https://pypi.org/project/towhee) (πŸ“₯ 15K / month Β· ⏱️ 04.12.2023): - ``` - pip install towhee - ``` -
Neural Tangents (πŸ₯‰24 Β· ⭐ 2.3K Β· πŸ’€) - 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“₯ 500 Β· πŸ“¦ 110 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“₯ 500 Β· πŸ“¦ 120 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“₯ 3.2K / month Β· πŸ“¦ 1 Β· ⏱️ 11.12.2023): +- [PyPi](https://pypi.org/project/neural-tangents) (πŸ“₯ 3.7K / month Β· πŸ“¦ 1 Β· ⏱️ 11.12.2023): ``` pip install neural-tangents ``` @@ -670,79 +658,79 @@ _General-purpose machine learning and deep learning frameworks._ ``` git clone https://github.com/nubank/fklearn ``` -- [PyPi](https://pypi.org/project/fklearn) (πŸ“₯ 3K / month Β· ⏱️ 14.08.2024): +- [PyPi](https://pypi.org/project/fklearn) (πŸ“₯ 4.4K / month Β· ⏱️ 14.08.2024): ``` pip install fklearn ```
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Runhouse (πŸ₯‰24 Β· ⭐ 960) - Dispatch and distribute your ML training to serverless clusters in.. Apache-2 +
Runhouse (πŸ₯‰24 Β· ⭐ 970) - Dispatch and distribute your ML training to serverless clusters in.. Apache-2 -- [GitHub](https://github.com/run-house/runhouse) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 35 Β· πŸ“₯ 44 Β· πŸ“‹ 51 - 17% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/run-house/runhouse) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 35 Β· πŸ“₯ 52 Β· πŸ“‹ 51 - 17% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/run-house/runhouse ``` -- [PyPi](https://pypi.org/project/runhouse) (πŸ“₯ 21K / month Β· πŸ“¦ 1 Β· ⏱️ 18.09.2024): +- [PyPi](https://pypi.org/project/runhouse) (πŸ“₯ 8.4K / month Β· πŸ“¦ 1 Β· ⏱️ 18.09.2024): ``` pip install runhouse ```
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NeoML (πŸ₯‰23 Β· ⭐ 770) - Machine learning framework for both deep learning and traditional.. Apache-2 +
ThunderSVM (πŸ₯‰22 Β· ⭐ 1.6K) - ThunderSVM: A Fast SVM Library on GPUs and CPUs. Apache-2 -- [GitHub](https://github.com/neoml-lib/neoml) (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 130 Β· πŸ“¦ 2 Β· πŸ“‹ 91 - 40% open Β· ⏱️ 30.09.2024): +- [GitHub](https://github.com/Xtra-Computing/thundersvm) (πŸ‘¨β€πŸ’» 37 Β· πŸ”€ 220 Β· πŸ“₯ 2.9K Β· πŸ“‹ 230 - 35% open Β· ⏱️ 01.04.2024): ``` - git clone https://github.com/neoml-lib/neoml + git clone https://github.com/Xtra-Computing/thundersvm ``` -- [PyPi](https://pypi.org/project/neoml) (πŸ“₯ 2.3K / month Β· ⏱️ 26.12.2023): +- [PyPi](https://pypi.org/project/thundersvm) (πŸ“₯ 1.4K / month Β· ⏱️ 13.03.2020): ``` - pip install neoml + pip install thundersvm ```
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ThunderSVM (πŸ₯‰22 Β· ⭐ 1.6K) - ThunderSVM: A Fast SVM Library on GPUs and CPUs. Apache-2 +
Objax (πŸ₯‰22 Β· ⭐ 770 Β· πŸ’€) - Objax is a machine learning framework that provides an Object.. Apache-2 -- [GitHub](https://github.com/Xtra-Computing/thundersvm) (πŸ‘¨β€πŸ’» 37 Β· πŸ”€ 210 Β· πŸ“₯ 2.9K Β· πŸ“‹ 230 - 34% open Β· ⏱️ 01.04.2024): +- [GitHub](https://github.com/google/objax) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 78 Β· πŸ“¦ 59 Β· πŸ“‹ 110 - 45% open Β· ⏱️ 27.01.2024): ``` - git clone https://github.com/Xtra-Computing/thundersvm + git clone https://github.com/google/objax ``` -- [PyPi](https://pypi.org/project/thundersvm) (πŸ“₯ 1.1K / month Β· ⏱️ 13.03.2020): +- [PyPi](https://pypi.org/project/objax) (πŸ“₯ 1.4K / month Β· πŸ“¦ 4 Β· ⏱️ 06.11.2023): ``` - pip install thundersvm + pip install objax ```
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Objax (πŸ₯‰22 Β· ⭐ 770 Β· πŸ’€) - Objax is a machine learning framework that provides an Object.. Apache-2 +
NeoML (πŸ₯‰22 Β· ⭐ 760) - Machine learning framework for both deep learning and traditional.. Apache-2 -- [GitHub](https://github.com/google/objax) (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 78 Β· πŸ“¦ 57 Β· πŸ“‹ 110 - 45% open Β· ⏱️ 27.01.2024): +- [GitHub](https://github.com/neoml-lib/neoml) (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 130 Β· πŸ“¦ 2 Β· πŸ“‹ 91 - 40% open Β· ⏱️ 30.09.2024): ``` - git clone https://github.com/google/objax + git clone https://github.com/neoml-lib/neoml ``` -- [PyPi](https://pypi.org/project/objax) (πŸ“₯ 1.1K / month Β· πŸ“¦ 4 Β· ⏱️ 06.11.2023): +- [PyPi](https://pypi.org/project/neoml) (πŸ“₯ 3.2K / month Β· ⏱️ 26.12.2023): ``` - pip install objax + pip install neoml ```
Torchbearer (πŸ₯‰22 Β· ⭐ 640 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“¦ 91 Β· πŸ“‹ 250 - 4% open Β· ⏱️ 04.12.2023): +- [GitHub](https://github.com/pytorchbearer/torchbearer) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 68 Β· πŸ“¦ 92 Β· πŸ“‹ 250 - 4% open Β· ⏱️ 04.12.2023): ``` git clone https://github.com/pytorchbearer/torchbearer ``` -- [PyPi](https://pypi.org/project/torchbearer) (πŸ“₯ 1.5K / month Β· πŸ“¦ 4 Β· ⏱️ 01.12.2023): +- [PyPi](https://pypi.org/project/torchbearer) (πŸ“₯ 1.7K / month Β· πŸ“¦ 4 Β· ⏱️ 01.12.2023): ``` pip install torchbearer ```
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chefboost (πŸ₯‰22 Β· ⭐ 450) - A Lightweight Decision Tree Framework supporting regular algorithms:.. MIT +
chefboost (πŸ₯‰22 Β· ⭐ 460) - A Lightweight Decision Tree Framework supporting regular algorithms:.. MIT -- [GitHub](https://github.com/serengil/chefboost) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 100 Β· πŸ“¦ 60 Β· πŸ“‹ 56 - 12% open Β· ⏱️ 12.08.2024): +- [GitHub](https://github.com/serengil/chefboost) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 100 Β· πŸ“¦ 61 Β· πŸ“‹ 56 - 12% open Β· ⏱️ 12.08.2024): ``` git clone https://github.com/serengil/chefboost ``` -- [PyPi](https://pypi.org/project/chefboost) (πŸ“₯ 4.5K / month Β· ⏱️ 08.06.2024): +- [PyPi](https://pypi.org/project/chefboost) (πŸ“₯ 5.7K / month Β· ⏱️ 08.06.2024): ``` pip install chefboost ``` @@ -762,16 +750,17 @@ _General-purpose machine learning and deep learning frameworks._ ``` git clone https://github.com/Xtra-Computing/thundergbm ``` -- [PyPi](https://pypi.org/project/thundergbm) (πŸ“₯ 840 / month Β· ⏱️ 19.09.2022): +- [PyPi](https://pypi.org/project/thundergbm) (πŸ“₯ 1.1K / month Β· ⏱️ 19.09.2022): ``` pip install thundergbm ```
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Show 16 hidden projects... +
Show 17 hidden projects... -- dlib (πŸ₯ˆ40 Β· ⭐ 13K) - A toolkit for making real world machine learning and data analysis.. ❗️BSL-1.0 +- dlib (πŸ₯ˆ40 Β· ⭐ 14K) - 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 -- Chainer (πŸ₯‰34 Β· ⭐ 5.9K Β· πŸ’€) - A flexible framework of neural networks for deep learning. MIT +- ivy (πŸ₯ˆ36 Β· ⭐ 14K) - Convert Machine Learning Code Between Frameworks. ❗️Intel-ACPI +- Chainer (πŸ₯ˆ34 Β· ⭐ 5.9K Β· πŸ’€) - A flexible framework of neural networks for deep learning. MIT - MindsDB (πŸ₯‰33 Β· ⭐ 27K) - The platform for building AI from enterprise data. ❗️libpng-2.0 - Turi Create (πŸ₯‰32 Β· ⭐ 11K Β· πŸ’€) - Turi Create simplifies the development of custom machine.. BSD-3 - tensorpack (πŸ₯‰32 Β· ⭐ 6.3K Β· πŸ’€) - A Neural Net Training Interface on TensorFlow, with.. Apache-2 @@ -796,12 +785,12 @@ _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”€ 7.6K Β· πŸ“¦ 1.4M Β· πŸ“‹ 11K - 14% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/matplotlib/matplotlib) (πŸ‘¨β€πŸ’» 1.7K Β· πŸ”€ 7.6K Β· πŸ“¦ 1.4M Β· πŸ“‹ 11K - 14% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/matplotlib/matplotlib ``` -- [PyPi](https://pypi.org/project/matplotlib) (πŸ“₯ 85M / month Β· πŸ“¦ 50K Β· ⏱️ 13.08.2024): +- [PyPi](https://pypi.org/project/matplotlib) (πŸ“₯ 82M / month Β· πŸ“¦ 50K Β· ⏱️ 13.08.2024): ``` pip install matplotlib ``` @@ -812,48 +801,48 @@ _General-purpose and task-specific data visualization libraries._
Bokeh (πŸ₯‡45 Β· ⭐ 19K) - Interactive Data Visualization in the browser, from Python. BSD-3 -- [GitHub](https://github.com/bokeh/bokeh) (πŸ‘¨β€πŸ’» 700 Β· πŸ”€ 4.2K Β· πŸ“¦ 93K Β· πŸ“‹ 7.7K - 9% open Β· ⏱️ 02.10.2024): +- [GitHub](https://github.com/bokeh/bokeh) (πŸ‘¨β€πŸ’» 700 Β· πŸ”€ 4.2K Β· πŸ“¦ 94K Β· πŸ“‹ 7.7K - 9% open Β· ⏱️ 22.10.2024): ``` git clone https://github.com/bokeh/bokeh ``` -- [PyPi](https://pypi.org/project/bokeh) (πŸ“₯ 4.5M / month Β· πŸ“¦ 1.7K Β· ⏱️ 26.09.2024): +- [PyPi](https://pypi.org/project/bokeh) (πŸ“₯ 4.4M / month Β· πŸ“¦ 1.7K Β· ⏱️ 26.09.2024): ``` pip install bokeh ``` -- [Conda](https://anaconda.org/conda-forge/bokeh) (πŸ“₯ 15M Β· ⏱️ 26.09.2024): +- [Conda](https://anaconda.org/conda-forge/bokeh) (πŸ“₯ 15M Β· ⏱️ 14.10.2024): ``` conda install -c conda-forge bokeh ```
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Plotly (πŸ₯‡44 Β· ⭐ 16K) - The interactive graphing library for Python This project now includes.. MIT +
Plotly (πŸ₯‡45 Β· ⭐ 16K) - The interactive graphing library for Python This project now includes.. MIT -- [GitHub](https://github.com/plotly/plotly.py) (πŸ‘¨β€πŸ’» 270 Β· πŸ”€ 2.5K Β· πŸ“¦ 310K Β· πŸ“‹ 3K - 17% open Β· ⏱️ 04.10.2024): +- [GitHub](https://github.com/plotly/plotly.py) (πŸ‘¨β€πŸ’» 280 Β· πŸ”€ 2.5K Β· πŸ“¦ 320K Β· πŸ“‹ 3K - 17% open Β· ⏱️ 22.10.2024): ``` git clone https://github.com/plotly/plotly.py ``` -- [PyPi](https://pypi.org/project/plotly) (πŸ“₯ 20M / month Β· πŸ“¦ 6.3K Β· ⏱️ 12.09.2024): +- [PyPi](https://pypi.org/project/plotly) (πŸ“₯ 21M / month Β· πŸ“¦ 6.3K Β· ⏱️ 12.09.2024): ``` pip install plotly ``` -- [Conda](https://anaconda.org/conda-forge/plotly) (πŸ“₯ 7.1M Β· ⏱️ 12.09.2024): +- [Conda](https://anaconda.org/conda-forge/plotly) (πŸ“₯ 7.3M Β· ⏱️ 12.09.2024): ``` conda install -c conda-forge plotly ``` -- [npm](https://www.npmjs.com/package/plotlywidget) (πŸ“₯ 6.2K / month Β· πŸ“¦ 9 Β· ⏱️ 12.01.2021): +- [npm](https://www.npmjs.com/package/plotlywidget) (πŸ“₯ 6.1K / month Β· πŸ“¦ 9 Β· ⏱️ 12.01.2021): ``` npm install plotlywidget ```
dash (πŸ₯‡43 Β· ⭐ 21K) - Data Apps & Dashboards for Python. No JavaScript Required. MIT -- [GitHub](https://github.com/plotly/dash) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 2.1K Β· πŸ“₯ 78 Β· πŸ“¦ 70K Β· πŸ“‹ 1.8K - 26% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/plotly/dash) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 2.1K Β· πŸ“₯ 85 Β· πŸ“¦ 71K Β· πŸ“‹ 1.8K - 26% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/plotly/dash ``` -- [PyPi](https://pypi.org/project/dash) (πŸ“₯ 3.4M / month Β· πŸ“¦ 1.3K Β· ⏱️ 12.09.2024): +- [PyPi](https://pypi.org/project/dash) (πŸ“₯ 3.6M / month Β· πŸ“¦ 1.3K Β· ⏱️ 12.09.2024): ``` pip install dash ``` @@ -862,9 +851,25 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge dash ```
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Seaborn (πŸ₯‡42 Β· ⭐ 13K) - Statistical data visualization in Python. BSD-3 + +- [GitHub](https://github.com/mwaskom/seaborn) (πŸ‘¨β€πŸ’» 210 Β· πŸ”€ 1.9K Β· πŸ“₯ 450 Β· πŸ“¦ 490K Β· πŸ“‹ 2.6K - 6% open Β· ⏱️ 22.07.2024): + + ``` + git clone https://github.com/mwaskom/seaborn + ``` +- [PyPi](https://pypi.org/project/seaborn) (πŸ“₯ 19M / month Β· πŸ“¦ 11K Β· ⏱️ 25.01.2024): + ``` + pip install seaborn + ``` +- [Conda](https://anaconda.org/conda-forge/seaborn) (πŸ“₯ 11M Β· ⏱️ 30.04.2024): + ``` + conda install -c conda-forge seaborn + ``` +
Altair (πŸ₯‡42 Β· ⭐ 9.3K) - Declarative statistical visualization library for Python. BSD-3 -- [GitHub](https://github.com/vega/altair) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 790 Β· πŸ“₯ 190 Β· πŸ“¦ 170K Β· πŸ“‹ 2K - 9% open Β· ⏱️ 06.10.2024): +- [GitHub](https://github.com/vega/altair) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 790 Β· πŸ“₯ 200 Β· πŸ“¦ 170K Β· πŸ“‹ 2K - 9% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/altair-viz/altair @@ -873,39 +878,43 @@ _General-purpose and task-specific data visualization libraries._ ``` pip install altair ``` -- [Conda](https://anaconda.org/conda-forge/altair) (πŸ“₯ 2.4M Β· ⏱️ 02.10.2024): +- [Conda](https://anaconda.org/conda-forge/altair) (πŸ“₯ 2.5M Β· ⏱️ 02.10.2024): ``` conda install -c conda-forge altair ```
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Seaborn (πŸ₯‡41 Β· ⭐ 12K) - Statistical data visualization in Python. BSD-3 +
HoloViews (πŸ₯ˆ38 Β· ⭐ 2.7K) - With Holoviews, your data visualizes itself. BSD-3 -- [GitHub](https://github.com/mwaskom/seaborn) (πŸ‘¨β€πŸ’» 210 Β· πŸ”€ 1.9K Β· πŸ“₯ 440 Β· πŸ“¦ 480K Β· πŸ“‹ 2.6K - 6% open Β· ⏱️ 22.07.2024): +- [GitHub](https://github.com/holoviz/holoviews) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 400 Β· πŸ“¦ 12K Β· πŸ“‹ 3.3K - 32% open Β· ⏱️ 23.10.2024): ``` - git clone https://github.com/mwaskom/seaborn + git clone https://github.com/holoviz/holoviews ``` -- [PyPi](https://pypi.org/project/seaborn) (πŸ“₯ 19M / month Β· πŸ“¦ 11K Β· ⏱️ 25.01.2024): +- [PyPi](https://pypi.org/project/holoviews) (πŸ“₯ 680K / month Β· πŸ“¦ 400 Β· ⏱️ 23.10.2024): ``` - pip install seaborn + pip install holoviews ``` -- [Conda](https://anaconda.org/conda-forge/seaborn) (πŸ“₯ 10M Β· ⏱️ 30.04.2024): +- [Conda](https://anaconda.org/conda-forge/holoviews) (πŸ“₯ 1.8M Β· ⏱️ 07.07.2024): ``` - conda install -c conda-forge seaborn + conda install -c conda-forge holoviews + ``` +- [npm](https://www.npmjs.com/package/@pyviz/jupyterlab_pyviz) (πŸ“₯ 290 / month Β· πŸ“¦ 5 Β· ⏱️ 01.08.2024): + ``` + npm install @pyviz/jupyterlab_pyviz ```
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PyVista (πŸ₯ˆ38 Β· ⭐ 2.6K) - 3D plotting and mesh analysis through a streamlined interface for.. MIT +
PyVista (πŸ₯ˆ38 Β· ⭐ 2.7K) - 3D plotting and mesh analysis through a streamlined interface for.. MIT -- [GitHub](https://github.com/pyvista/pyvista) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 480 Β· πŸ“₯ 840 Β· πŸ“¦ 3.5K Β· πŸ“‹ 1.7K - 34% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/pyvista/pyvista) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 490 Β· πŸ“₯ 840 Β· πŸ“¦ 3.6K Β· πŸ“‹ 1.7K - 34% open Β· ⏱️ 21.10.2024): ``` git clone https://github.com/pyvista/pyvista ``` -- [PyPi](https://pypi.org/project/pyvista) (πŸ“₯ 300K / month Β· πŸ“¦ 530 Β· ⏱️ 20.07.2024): +- [PyPi](https://pypi.org/project/pyvista) (πŸ“₯ 350K / month Β· πŸ“¦ 530 Β· ⏱️ 20.07.2024): ``` pip install pyvista ``` -- [Conda](https://anaconda.org/conda-forge/pyvista) (πŸ“₯ 560K Β· ⏱️ 20.07.2024): +- [Conda](https://anaconda.org/conda-forge/pyvista) (πŸ“₯ 570K Β· ⏱️ 20.07.2024): ``` conda install -c conda-forge pyvista ``` @@ -917,19 +926,19 @@ _General-purpose and task-specific data visualization libraries._ ``` git clone https://github.com/pyecharts/pyecharts ``` -- [PyPi](https://pypi.org/project/pyecharts) (πŸ“₯ 130K / month Β· πŸ“¦ 210 Β· ⏱️ 20.06.2024): +- [PyPi](https://pypi.org/project/pyecharts) (πŸ“₯ 160K / month Β· πŸ“¦ 210 Β· ⏱️ 20.06.2024): ``` pip install pyecharts ```
pandas-profiling (πŸ₯ˆ37 Β· ⭐ 12K) - 1 Line of code data quality profiling & exploratory.. MIT -- [GitHub](https://github.com/ydataai/ydata-profiling) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 1.7K Β· πŸ“₯ 190 Β· πŸ“¦ 4.3K Β· πŸ“‹ 810 - 29% open Β· ⏱️ 04.10.2024): +- [GitHub](https://github.com/ydataai/ydata-profiling) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 1.7K Β· πŸ“₯ 200 Β· πŸ“¦ 4.4K Β· πŸ“‹ 810 - 29% open Β· ⏱️ 15.10.2024): ``` git clone https://github.com/ydataai/pandas-profiling ``` -- [PyPi](https://pypi.org/project/pandas-profiling) (πŸ“₯ 330K / month Β· πŸ“¦ 180 Β· ⏱️ 03.02.2023): +- [PyPi](https://pypi.org/project/pandas-profiling) (πŸ“₯ 340K / month Β· πŸ“¦ 180 Β· ⏱️ 03.02.2023): ``` pip install pandas-profiling ``` @@ -938,82 +947,58 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge pandas-profiling ```
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HoloViews (πŸ₯ˆ37 Β· ⭐ 2.7K) - With Holoviews, your data visualizes itself. BSD-3 +
PyQtGraph (πŸ₯ˆ37 Β· ⭐ 3.9K) - Fast data visualization and GUI tools for scientific / engineering.. MIT -- [GitHub](https://github.com/holoviz/holoviews) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 400 Β· πŸ“¦ 12K Β· πŸ“‹ 3.3K - 33% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/pyqtgraph/pyqtgraph) (πŸ‘¨β€πŸ’» 290 Β· πŸ”€ 1.1K Β· πŸ“¦ 10K Β· πŸ“‹ 1.3K - 32% open Β· ⏱️ 13.10.2024): ``` - git clone https://github.com/holoviz/holoviews - ``` -- [PyPi](https://pypi.org/project/holoviews) (πŸ“₯ 680K / month Β· πŸ“¦ 390 Β· ⏱️ 01.10.2024): - ``` - pip install holoviews + git clone https://github.com/pyqtgraph/pyqtgraph ``` -- [Conda](https://anaconda.org/conda-forge/holoviews) (πŸ“₯ 1.8M Β· ⏱️ 07.07.2024): +- [PyPi](https://pypi.org/project/pyqtgraph) (πŸ“₯ 350K / month Β· πŸ“¦ 1K Β· ⏱️ 29.04.2024): ``` - conda install -c conda-forge holoviews + pip install pyqtgraph ``` -- [npm](https://www.npmjs.com/package/@pyviz/jupyterlab_pyviz) (πŸ“₯ 260 / month Β· πŸ“¦ 5 Β· ⏱️ 01.08.2024): +- [Conda](https://anaconda.org/conda-forge/pyqtgraph) (πŸ“₯ 600K Β· ⏱️ 02.05.2024): ``` - npm install @pyviz/jupyterlab_pyviz + conda install -c conda-forge pyqtgraph ```
FiftyOne (πŸ₯ˆ36 Β· ⭐ 8.8K) - Visualize, create, and debug image and video datasets.. Apache-2 -- [GitHub](https://github.com/voxel51/fiftyone) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 550 Β· πŸ“¦ 710 Β· πŸ“‹ 1.6K - 31% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/voxel51/fiftyone) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 550 Β· πŸ“¦ 710 Β· πŸ“‹ 1.6K - 31% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/voxel51/fiftyone ``` -- [PyPi](https://pypi.org/project/fiftyone) (πŸ“₯ 77K / month Β· πŸ“¦ 22 Β· ⏱️ 01.10.2024): +- [PyPi](https://pypi.org/project/fiftyone) (πŸ“₯ 120K / month Β· πŸ“¦ 22 Β· ⏱️ 14.10.2024): ``` pip install fiftyone ```
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PyQtGraph (πŸ₯ˆ36 Β· ⭐ 3.9K) - Fast data visualization and GUI tools for scientific / engineering.. MIT - -- [GitHub](https://github.com/pyqtgraph/pyqtgraph) (πŸ‘¨β€πŸ’» 290 Β· πŸ”€ 1.1K Β· πŸ“¦ 10K Β· πŸ“‹ 1.3K - 31% open Β· ⏱️ 08.09.2024): - - ``` - git clone https://github.com/pyqtgraph/pyqtgraph - ``` -- [PyPi](https://pypi.org/project/pyqtgraph) (πŸ“₯ 350K / month Β· πŸ“¦ 1K Β· ⏱️ 29.04.2024): - ``` - pip install pyqtgraph - ``` -- [Conda](https://anaconda.org/conda-forge/pyqtgraph) (πŸ“₯ 600K Β· ⏱️ 02.05.2024): - ``` - conda install -c conda-forge pyqtgraph - ``` -
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VisPy (πŸ₯ˆ36 Β· ⭐ 3.3K Β· πŸ“ˆ) - High-performance interactive 2D/3D data visualization library. BSD-3 +
cartopy (πŸ₯ˆ36 Β· ⭐ 1.4K Β· πŸ“ˆ) - Cartopy - a cartographic python library with matplotlib support. BSD-3 -- [GitHub](https://github.com/vispy/vispy) (πŸ‘¨β€πŸ’» 200 Β· πŸ”€ 620 Β· πŸ“¦ 1.7K Β· πŸ“‹ 1.5K - 24% open Β· ⏱️ 07.10.2024): +- [GitHub](https://github.com/SciTools/cartopy) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 360 Β· πŸ“¦ 5.8K Β· πŸ“‹ 1.3K - 24% open Β· ⏱️ 23.10.2024): ``` - git clone https://github.com/vispy/vispy - ``` -- [PyPi](https://pypi.org/project/vispy) (πŸ“₯ 450K / month Β· πŸ“¦ 170 Β· ⏱️ 17.06.2024): - ``` - pip install vispy + git clone https://github.com/SciTools/cartopy ``` -- [Conda](https://anaconda.org/conda-forge/vispy) (πŸ“₯ 610K Β· ⏱️ 04.09.2024): +- [PyPi](https://pypi.org/project/cartopy) (πŸ“₯ 410K / month Β· πŸ“¦ 720 Β· ⏱️ 08.10.2024): ``` - conda install -c conda-forge vispy + pip install cartopy ``` -- [npm](https://www.npmjs.com/package/vispy) (πŸ“₯ 3 / month Β· πŸ“¦ 3 Β· ⏱️ 15.03.2020): +- [Conda](https://anaconda.org/conda-forge/cartopy) (πŸ“₯ 4.1M Β· ⏱️ 07.10.2024): ``` - npm install vispy + conda install -c conda-forge cartopy ```
plotnine (πŸ₯ˆ35 Β· ⭐ 4K) - A Grammar of Graphics for Python. MIT -- [GitHub](https://github.com/has2k1/plotnine) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 210 Β· πŸ“¦ 8.9K Β· πŸ“‹ 680 - 13% open Β· ⏱️ 04.10.2024): +- [GitHub](https://github.com/has2k1/plotnine) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 210 Β· πŸ“¦ 9.1K Β· πŸ“‹ 680 - 13% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/has2k1/plotnine ``` -- [PyPi](https://pypi.org/project/plotnine) (πŸ“₯ 3.1M / month Β· πŸ“¦ 310 Β· ⏱️ 09.05.2024): +- [PyPi](https://pypi.org/project/plotnine) (πŸ“₯ 3M / month Β· πŸ“¦ 310 Β· ⏱️ 09.05.2024): ``` pip install plotnine ``` @@ -1022,72 +1007,76 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge plotnine ```
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Graphviz (πŸ₯ˆ34 Β· ⭐ 1.6K) - Simple Python interface for Graphviz. MIT +
Graphviz (πŸ₯ˆ35 Β· ⭐ 1.6K) - Simple Python interface for Graphviz. MIT -- [GitHub](https://github.com/xflr6/graphviz) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 210 Β· πŸ“¦ 74K Β· πŸ“‹ 180 - 7% open Β· ⏱️ 13.05.2024): +- [GitHub](https://github.com/xflr6/graphviz) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 210 Β· πŸ“¦ 75K Β· πŸ“‹ 180 - 7% open Β· ⏱️ 13.05.2024): ``` git clone https://github.com/xflr6/graphviz ``` -- [PyPi](https://pypi.org/project/graphviz) (πŸ“₯ 17M / month Β· πŸ“¦ 2.6K Β· ⏱️ 21.03.2024): +- [PyPi](https://pypi.org/project/graphviz) (πŸ“₯ 16M / month Β· πŸ“¦ 2.6K Β· ⏱️ 21.03.2024): ``` pip install graphviz ``` -- [Conda](https://anaconda.org/anaconda/python-graphviz) (πŸ“₯ 49K Β· ⏱️ 08.04.2024): +- [Conda](https://anaconda.org/anaconda/python-graphviz) (πŸ“₯ 50K Β· ⏱️ 08.04.2024): ``` conda install -c anaconda python-graphviz ```
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cartopy (πŸ₯ˆ34 Β· ⭐ 1.4K) - Cartopy - a cartographic python library with matplotlib support. BSD-3 +
UMAP (πŸ₯ˆ34 Β· ⭐ 7.4K) - Uniform Manifold Approximation and Projection. BSD-3 -- [GitHub](https://github.com/SciTools/cartopy) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 360 Β· πŸ“¦ 5.8K Β· πŸ“‹ 1.3K - 24% open Β· ⏱️ 08.10.2024): +- [GitHub](https://github.com/lmcinnes/umap) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 800 Β· πŸ“¦ 1 Β· πŸ“‹ 810 - 58% open Β· ⏱️ 19.10.2024): ``` - git clone https://github.com/SciTools/cartopy + git clone https://github.com/lmcinnes/umap ``` -- [PyPi](https://pypi.org/project/cartopy) (πŸ“₯ 350K / month Β· πŸ“¦ 720 Β· ⏱️ 08.10.2024): +- [PyPi](https://pypi.org/project/umap-learn) (πŸ“₯ 1.6M / month Β· πŸ“¦ 960 Β· ⏱️ 03.04.2024): ``` - pip install cartopy + pip install umap-learn ``` -- [Conda](https://anaconda.org/conda-forge/cartopy) (πŸ“₯ 4.1M Β· ⏱️ 07.10.2024): +- [Conda](https://anaconda.org/conda-forge/umap-learn) (πŸ“₯ 2.7M Β· ⏱️ 14.08.2024): ``` - conda install -c conda-forge cartopy + conda install -c conda-forge umap-learn ```
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Perspective (πŸ₯ˆ33 Β· ⭐ 8.4K) - A data visualization and analytics component, especially.. Apache-2 +
VisPy (πŸ₯ˆ34 Β· ⭐ 3.3K Β· πŸ“‰) - High-performance interactive 2D/3D data visualization library. BSD-3 -- [GitHub](https://github.com/finos/perspective) (πŸ‘¨β€πŸ’» 94 Β· πŸ”€ 1.2K Β· πŸ“₯ 5.2K Β· πŸ“¦ 150 Β· πŸ“‹ 810 - 12% open Β· ⏱️ 06.10.2024): +- [GitHub](https://github.com/vispy/vispy) (πŸ‘¨β€πŸ’» 200 Β· πŸ”€ 620 Β· πŸ“¦ 1.7K Β· πŸ“‹ 1.5K - 24% open Β· ⏱️ 07.10.2024): ``` - git clone https://github.com/finos/perspective + git clone https://github.com/vispy/vispy ``` -- [PyPi](https://pypi.org/project/perspective-python) (πŸ“₯ 24K / month Β· πŸ“¦ 26 Β· ⏱️ 23.09.2024): +- [PyPi](https://pypi.org/project/vispy) (πŸ“₯ 400K / month Β· πŸ“¦ 170 Β· ⏱️ 17.06.2024): ``` - pip install perspective-python + pip install vispy ``` -- [Conda](https://anaconda.org/conda-forge/perspective) (πŸ“₯ 1.2M Β· ⏱️ 21.09.2024): +- [Conda](https://anaconda.org/conda-forge/vispy) (πŸ“₯ 620K Β· ⏱️ 04.09.2024): ``` - conda install -c conda-forge perspective + conda install -c conda-forge vispy ``` -- [npm](https://www.npmjs.com/package/@finos/perspective-jupyterlab) (πŸ“₯ 4.4K / month Β· πŸ“¦ 6 Β· ⏱️ 23.09.2024): +- [npm](https://www.npmjs.com/package/vispy) (πŸ“₯ 9 / month Β· πŸ“¦ 3 Β· ⏱️ 15.03.2020): ``` - npm install @finos/perspective-jupyterlab + npm install vispy ```
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UMAP (πŸ₯ˆ33 Β· ⭐ 7.4K) - Uniform Manifold Approximation and Projection. BSD-3 +
Perspective (πŸ₯ˆ33 Β· ⭐ 8.4K) - A data visualization and analytics component, especially.. Apache-2 -- [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): +- [GitHub](https://github.com/finos/perspective) (πŸ‘¨β€πŸ’» 96 Β· πŸ”€ 1.2K Β· πŸ“₯ 5.5K Β· πŸ“¦ 150 Β· πŸ“‹ 810 - 12% open Β· ⏱️ 22.10.2024): ``` - git clone https://github.com/lmcinnes/umap + git clone https://github.com/finos/perspective ``` -- [PyPi](https://pypi.org/project/umap-learn) (πŸ“₯ 1.4M / month Β· πŸ“¦ 960 Β· ⏱️ 03.04.2024): +- [PyPi](https://pypi.org/project/perspective-python) (πŸ“₯ 27K / month Β· πŸ“¦ 26 Β· ⏱️ 22.10.2024): ``` - pip install umap-learn + pip install perspective-python ``` -- [Conda](https://anaconda.org/conda-forge/umap-learn) (πŸ“₯ 2.6M Β· ⏱️ 14.08.2024): +- [Conda](https://anaconda.org/conda-forge/perspective) (πŸ“₯ 1.3M Β· ⏱️ 21.09.2024): ``` - conda install -c conda-forge umap-learn + conda install -c conda-forge perspective + ``` +- [npm](https://www.npmjs.com/package/@finos/perspective-jupyterlab) (πŸ“₯ 3.9K / month Β· πŸ“¦ 6 Β· ⏱️ 22.10.2024): + ``` + npm install @finos/perspective-jupyterlab ```
datashader (πŸ₯ˆ33 Β· ⭐ 3.3K) - Quickly and accurately render even the largest data. BSD-3 @@ -1097,7 +1086,7 @@ _General-purpose and task-specific data visualization libraries._ ``` git clone https://github.com/holoviz/datashader ``` -- [PyPi](https://pypi.org/project/datashader) (πŸ“₯ 150K / month Β· πŸ“¦ 200 Β· ⏱️ 04.07.2024): +- [PyPi](https://pypi.org/project/datashader) (πŸ“₯ 140K / month Β· πŸ“¦ 200 Β· ⏱️ 04.07.2024): ``` pip install datashader ``` @@ -1117,47 +1106,47 @@ _General-purpose and task-specific data visualization libraries._ ``` pip install wordcloud ``` -- [Conda](https://anaconda.org/conda-forge/wordcloud) (πŸ“₯ 540K Β· ⏱️ 16.09.2024): +- [Conda](https://anaconda.org/conda-forge/wordcloud) (πŸ“₯ 550K Β· ⏱️ 16.09.2024): ``` conda install -c conda-forge wordcloud ```
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hvPlot (πŸ₯ˆ32 Β· ⭐ 1.1K) - A high-level plotting API for pandas, dask, xarray, and networkx built.. BSD-3 +
lets-plot (πŸ₯ˆ32 Β· ⭐ 1.6K) - Multiplatform plotting library based on the Grammar of Graphics. MIT -- [GitHub](https://github.com/holoviz/hvplot) (πŸ‘¨β€πŸ’» 49 Β· πŸ”€ 110 Β· πŸ“¦ 5.9K Β· πŸ“‹ 810 - 44% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/JetBrains/lets-plot) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 51 Β· πŸ“₯ 1.3K Β· πŸ“¦ 130 Β· πŸ“‹ 630 - 24% open Β· ⏱️ 24.10.2024): ``` - git clone https://github.com/holoviz/hvplot - ``` -- [PyPi](https://pypi.org/project/hvplot) (πŸ“₯ 230K / month Β· πŸ“¦ 200 Β· ⏱️ 27.09.2024): - ``` - pip install hvplot + git clone https://github.com/JetBrains/lets-plot ``` -- [Conda](https://anaconda.org/conda-forge/hvplot) (πŸ“₯ 650K Β· ⏱️ 30.09.2024): +- [PyPi](https://pypi.org/project/lets-plot) (πŸ“₯ 57K / month Β· πŸ“¦ 13 Β· ⏱️ 23.10.2024): ``` - conda install -c conda-forge hvplot + pip install lets-plot ```
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lets-plot (πŸ₯ˆ31 Β· ⭐ 1.6K) - Multiplatform plotting library based on the Grammar of Graphics. MIT +
hvPlot (πŸ₯ˆ32 Β· ⭐ 1.1K) - A high-level plotting API for pandas, dask, xarray, and networkx built.. BSD-3 -- [GitHub](https://github.com/JetBrains/lets-plot) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 49 Β· πŸ“₯ 1.1K Β· πŸ“¦ 130 Β· πŸ“‹ 610 - 24% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/holoviz/hvplot) (πŸ‘¨β€πŸ’» 50 Β· πŸ”€ 110 Β· πŸ“¦ 6K Β· πŸ“‹ 820 - 44% open Β· ⏱️ 16.10.2024): ``` - git clone https://github.com/JetBrains/lets-plot + git clone https://github.com/holoviz/hvplot ``` -- [PyPi](https://pypi.org/project/lets-plot) (πŸ“₯ 42K / month Β· πŸ“¦ 13 Β· ⏱️ 21.08.2024): +- [PyPi](https://pypi.org/project/hvplot) (πŸ“₯ 230K / month Β· πŸ“¦ 200 Β· ⏱️ 16.10.2024): ``` - pip install lets-plot + pip install hvplot + ``` +- [Conda](https://anaconda.org/conda-forge/hvplot) (πŸ“₯ 660K Β· ⏱️ 17.10.2024): + ``` + conda install -c conda-forge hvplot ```
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D-Tale (πŸ₯‰30 Β· ⭐ 4.7K) - Visualizer for pandas data structures. ❗️LGPL-2.1 +
D-Tale (πŸ₯‰30 Β· ⭐ 4.8K) - Visualizer for pandas data structures. ❗️LGPL-2.1 - [GitHub](https://github.com/man-group/dtale) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 400 Β· πŸ“¦ 1.2K Β· πŸ“‹ 590 - 10% open Β· ⏱️ 10.09.2024): ``` git clone https://github.com/man-group/dtale ``` -- [PyPi](https://pypi.org/project/dtale) (πŸ“₯ 72K / month Β· πŸ“¦ 44 Β· ⏱️ 10.09.2024): +- [PyPi](https://pypi.org/project/dtale) (πŸ“₯ 120K / month Β· πŸ“¦ 44 Β· ⏱️ 10.09.2024): ``` pip install dtale ``` @@ -1168,12 +1157,12 @@ _General-purpose and task-specific data visualization libraries._
bqplot (πŸ₯‰29 Β· ⭐ 3.6K) - Plotting library for IPython/Jupyter notebooks. Apache-2 -- [GitHub](https://github.com/bqplot/bqplot) (πŸ‘¨β€πŸ’» 65 Β· πŸ”€ 460 Β· πŸ“¦ 58 Β· πŸ“‹ 630 - 41% open Β· ⏱️ 09.09.2024): +- [GitHub](https://github.com/bqplot/bqplot) (πŸ‘¨β€πŸ’» 65 Β· πŸ”€ 460 Β· πŸ“¦ 59 Β· πŸ“‹ 630 - 41% open Β· ⏱️ 22.10.2024): ``` git clone https://github.com/bqplot/bqplot ``` -- [PyPi](https://pypi.org/project/bqplot) (πŸ“₯ 190K / month Β· πŸ“¦ 99 Β· ⏱️ 25.03.2024): +- [PyPi](https://pypi.org/project/bqplot) (πŸ“₯ 200K / month Β· πŸ“¦ 99 Β· ⏱️ 25.03.2024): ``` pip install bqplot ``` @@ -1181,19 +1170,19 @@ _General-purpose and task-specific data visualization libraries._ ``` conda install -c conda-forge bqplot ``` -- [npm](https://www.npmjs.com/package/bqplot) (πŸ“₯ 2.3K / month Β· πŸ“¦ 21 Β· ⏱️ 25.03.2024): +- [npm](https://www.npmjs.com/package/bqplot) (πŸ“₯ 2.6K / month Β· πŸ“¦ 21 Β· ⏱️ 25.03.2024): ``` npm install bqplot ```
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mpld3 (πŸ₯‰29 Β· ⭐ 2.4K Β· πŸ’€) - An interactive data visualization tool which brings matplotlib.. BSD-3 +
mpld3 (πŸ₯‰29 Β· ⭐ 2.4K) - An interactive data visualization tool which brings matplotlib graphics to.. BSD-3 -- [GitHub](https://github.com/mpld3/mpld3) (πŸ‘¨β€πŸ’» 52 Β· πŸ”€ 360 Β· πŸ“¦ 6.6K Β· πŸ“‹ 360 - 59% open Β· ⏱️ 23.12.2023): +- [GitHub](https://github.com/mpld3/mpld3) (πŸ‘¨β€πŸ’» 52 Β· πŸ”€ 360 Β· πŸ“¦ 6.6K Β· πŸ“‹ 360 - 59% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/mpld3/mpld3 ``` -- [PyPi](https://pypi.org/project/mpld3) (πŸ“₯ 370K / month Β· πŸ“¦ 150 Β· ⏱️ 23.12.2023): +- [PyPi](https://pypi.org/project/mpld3) (πŸ“₯ 350K / month Β· πŸ“¦ 150 Β· ⏱️ 23.12.2023): ``` pip install mpld3 ``` @@ -1201,19 +1190,19 @@ _General-purpose and task-specific data visualization libraries._ ``` conda install -c conda-forge mpld3 ``` -- [npm](https://www.npmjs.com/package/mpld3) (πŸ“₯ 760 / month Β· πŸ“¦ 9 Β· ⏱️ 23.12.2023): +- [npm](https://www.npmjs.com/package/mpld3) (πŸ“₯ 840 / month Β· πŸ“¦ 9 Β· ⏱️ 23.12.2023): ``` npm install mpld3 ```
openTSNE (πŸ₯‰28 Β· ⭐ 1.5K) - Extensible, parallel implementations of t-SNE. BSD-3 -- [GitHub](https://github.com/pavlin-policar/openTSNE) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 160 Β· πŸ“¦ 890 Β· πŸ“‹ 140 - 3% open Β· ⏱️ 13.08.2024): +- [GitHub](https://github.com/pavlin-policar/openTSNE) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 160 Β· πŸ“¦ 900 Β· πŸ“‹ 140 - 3% open Β· ⏱️ 13.08.2024): ``` git clone https://github.com/pavlin-policar/openTSNE ``` -- [PyPi](https://pypi.org/project/opentsne) (πŸ“₯ 37K / month Β· πŸ“¦ 47 Β· ⏱️ 13.08.2024): +- [PyPi](https://pypi.org/project/opentsne) (πŸ“₯ 42K / month Β· πŸ“¦ 47 Β· ⏱️ 13.08.2024): ``` pip install opentsne ``` @@ -1222,6 +1211,22 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge opentsne ```
+
Chartify (πŸ₯‰27 Β· ⭐ 3.5K Β· πŸ“ˆ) - Python library that makes it easy for data scientists to create.. Apache-2 + +- [GitHub](https://github.com/spotify/chartify) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 320 Β· πŸ“¦ 80 Β· πŸ“‹ 83 - 61% open Β· ⏱️ 16.10.2024): + + ``` + git clone https://github.com/spotify/chartify + ``` +- [PyPi](https://pypi.org/project/chartify) (πŸ“₯ 4.4K / month Β· πŸ“¦ 9 Β· ⏱️ 16.10.2024): + ``` + pip install chartify + ``` +- [Conda](https://anaconda.org/conda-forge/chartify) (πŸ“₯ 33K Β· ⏱️ 16.06.2023): + ``` + conda install -c conda-forge chartify + ``` +
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”€ 280 Β· πŸ“¦ 2.6K Β· πŸ“‹ 140 - 31% open Β· ⏱️ 29.11.2023): @@ -1229,7 +1234,7 @@ _General-purpose and task-specific data visualization libraries._ ``` git clone https://github.com/fbdesignpro/sweetviz ``` -- [PyPi](https://pypi.org/project/sweetviz) (πŸ“₯ 81K / month Β· πŸ“¦ 30 Β· ⏱️ 29.11.2023): +- [PyPi](https://pypi.org/project/sweetviz) (πŸ“₯ 78K / month Β· πŸ“¦ 30 Β· ⏱️ 29.11.2023): ``` pip install sweetviz ``` @@ -1240,72 +1245,56 @@ _General-purpose and task-specific data visualization libraries._
HyperTools (πŸ₯‰26 Β· ⭐ 1.8K Β· πŸ’€) - A Python toolbox for gaining geometric insights into high-.. MIT -- [GitHub](https://github.com/ContextLab/hypertools) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 160 Β· πŸ“₯ 49 Β· πŸ“¦ 480 Β· πŸ“‹ 200 - 34% open Β· ⏱️ 19.03.2024): +- [GitHub](https://github.com/ContextLab/hypertools) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 160 Β· πŸ“₯ 51 Β· πŸ“¦ 480 Β· πŸ“‹ 200 - 34% open Β· ⏱️ 19.03.2024): ``` git clone https://github.com/ContextLab/hypertools ``` -- [PyPi](https://pypi.org/project/hypertools) (πŸ“₯ 1.6K / month Β· πŸ“¦ 2 Β· ⏱️ 12.02.2022): +- [PyPi](https://pypi.org/project/hypertools) (πŸ“₯ 2.4K / month Β· πŸ“¦ 2 Β· ⏱️ 12.02.2022): ``` pip install hypertools ```
AutoViz (πŸ₯‰26 Β· ⭐ 1.7K) - Automatically Visualize any dataset, any size with a single line of.. Apache-2 -- [GitHub](https://github.com/AutoViML/AutoViz) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 200 Β· πŸ“¦ 760 Β· πŸ“‹ 94 - 3% open Β· ⏱️ 10.06.2024): +- [GitHub](https://github.com/AutoViML/AutoViz) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 200 Β· πŸ“¦ 770 Β· πŸ“‹ 94 - 3% open Β· ⏱️ 10.06.2024): ``` git clone https://github.com/AutoViML/AutoViz ``` -- [PyPi](https://pypi.org/project/autoviz) (πŸ“₯ 45K / month Β· πŸ“¦ 11 Β· ⏱️ 10.06.2024): - ``` - pip install autoviz - ``` -- [Conda](https://anaconda.org/conda-forge/autoviz) (πŸ“₯ 65K Β· ⏱️ 26.04.2024): - ``` - conda install -c conda-forge autoviz +- [PyPi](https://pypi.org/project/autoviz) (πŸ“₯ 43K / month Β· πŸ“¦ 11 Β· ⏱️ 10.06.2024): ``` -
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data-validation (πŸ₯‰26 Β· ⭐ 760) - Library for exploring and validating machine learning.. Apache-2 - -- [GitHub](https://github.com/tensorflow/data-validation) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 170 Β· πŸ“₯ 870 Β· πŸ“‹ 180 - 20% open Β· ⏱️ 03.10.2024): - - ``` - git clone https://github.com/tensorflow/data-validation + pip install autoviz ``` -- [PyPi](https://pypi.org/project/tensorflow-data-validation) (πŸ“₯ 190K / month Β· πŸ“¦ 31 Β· ⏱️ 03.10.2024): +- [Conda](https://anaconda.org/conda-forge/autoviz) (πŸ“₯ 66K Β· ⏱️ 26.04.2024): ``` - pip install tensorflow-data-validation + conda install -c conda-forge autoviz ```
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Chartify (πŸ₯‰24 Β· ⭐ 3.5K Β· πŸ’€) - Python library that makes it easy for data scientists to create.. Apache-2 +
data-validation (πŸ₯‰26 Β· ⭐ 760) - Library for exploring and validating machine learning.. Apache-2 -- [GitHub](https://github.com/spotify/chartify) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 320 Β· πŸ“¦ 79 Β· πŸ“‹ 83 - 61% open Β· ⏱️ 12.10.2023): +- [GitHub](https://github.com/tensorflow/data-validation) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 170 Β· πŸ“₯ 880 Β· πŸ“‹ 180 - 20% open Β· ⏱️ 23.10.2024): ``` - git clone https://github.com/spotify/chartify - ``` -- [PyPi](https://pypi.org/project/chartify) (πŸ“₯ 3.5K / month Β· πŸ“¦ 9 Β· ⏱️ 12.10.2023): - ``` - pip install chartify + git clone https://github.com/tensorflow/data-validation ``` -- [Conda](https://anaconda.org/conda-forge/chartify) (πŸ“₯ 33K Β· ⏱️ 16.06.2023): +- [PyPi](https://pypi.org/project/tensorflow-data-validation) (πŸ“₯ 170K / month Β· πŸ“¦ 31 Β· ⏱️ 15.10.2024): ``` - conda install -c conda-forge chartify + pip install tensorflow-data-validation ```
Plotly-Resampler (πŸ₯‰24 Β· ⭐ 1K) - Visualize large time series data with plotly.py. MIT -- [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): +- [GitHub](https://github.com/predict-idlab/plotly-resampler) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 68 Β· πŸ“¦ 1.5K Β· πŸ“‹ 170 - 30% open Β· ⏱️ 24.08.2024): ``` git clone https://github.com/predict-idlab/plotly-resampler ``` -- [PyPi](https://pypi.org/project/plotly-resampler) (πŸ“₯ 350K / month Β· πŸ“¦ 24 Β· ⏱️ 27.03.2024): +- [PyPi](https://pypi.org/project/plotly-resampler) (πŸ“₯ 360K / month Β· πŸ“¦ 24 Β· ⏱️ 27.03.2024): ``` pip install plotly-resampler ``` -- [Conda](https://anaconda.org/conda-forge/plotly-resampler) (πŸ“₯ 70K Β· ⏱️ 29.03.2024): +- [Conda](https://anaconda.org/conda-forge/plotly-resampler) (πŸ“₯ 72K Β· ⏱️ 29.03.2024): ``` conda install -c conda-forge plotly-resampler ``` @@ -1321,7 +1310,7 @@ _General-purpose and task-specific data visualization libraries._ ``` pip install python-ternary ``` -- [Conda](https://anaconda.org/conda-forge/python-ternary) (πŸ“₯ 90K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/python-ternary) (πŸ“₯ 91K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge python-ternary ``` @@ -1333,11 +1322,11 @@ _General-purpose and task-specific data visualization libraries._ ``` git clone https://github.com/vega/ipyvega ``` -- [PyPi](https://pypi.org/project/vega) (πŸ“₯ 14K / month Β· πŸ“¦ 17 Β· ⏱️ 25.09.2024): +- [PyPi](https://pypi.org/project/vega) (πŸ“₯ 12K / month Β· πŸ“¦ 17 Β· ⏱️ 25.09.2024): ``` pip install vega ``` -- [Conda](https://anaconda.org/conda-forge/vega) (πŸ“₯ 650K Β· ⏱️ 25.09.2024): +- [Conda](https://anaconda.org/conda-forge/vega) (πŸ“₯ 660K Β· ⏱️ 25.09.2024): ``` conda install -c conda-forge vega ``` @@ -1349,7 +1338,7 @@ _General-purpose and task-specific data visualization libraries._ ``` git clone https://github.com/beringresearch/ivis ``` -- [PyPi](https://pypi.org/project/ivis) (πŸ“₯ 1.9K / month Β· πŸ“¦ 2 Β· ⏱️ 13.06.2024): +- [PyPi](https://pypi.org/project/ivis) (πŸ“₯ 2.6K / month Β· πŸ“¦ 2 Β· ⏱️ 13.06.2024): ``` pip install ivis ``` @@ -1361,27 +1350,27 @@ _General-purpose and task-specific data visualization libraries._ ``` git clone https://github.com/DmitryUlyanov/Multicore-TSNE ``` -- [PyPi](https://pypi.org/project/MulticoreTSNE) (πŸ“₯ 1.8K / month Β· πŸ“¦ 22 Β· ⏱️ 09.01.2019): +- [PyPi](https://pypi.org/project/MulticoreTSNE) (πŸ“₯ 2K / month Β· πŸ“¦ 22 Β· ⏱️ 09.01.2019): ``` pip install MulticoreTSNE ``` -- [Conda](https://anaconda.org/conda-forge/multicore-tsne) (πŸ“₯ 51K Β· ⏱️ 11.10.2023): +- [Conda](https://anaconda.org/conda-forge/multicore-tsne) (πŸ“₯ 53K Β· ⏱️ 11.10.2023): ``` conda install -c conda-forge multicore-tsne ```
-
PyWaffle (πŸ₯‰21 Β· ⭐ 580) - Make Waffle Charts in Python. MIT +
PyWaffle (πŸ₯‰22 Β· ⭐ 580) - Make Waffle Charts in Python. MIT - [GitHub](https://github.com/gyli/PyWaffle) (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 100 Β· πŸ“¦ 410 Β· πŸ“‹ 22 - 27% open Β· ⏱️ 16.06.2024): ``` git clone https://github.com/gyli/PyWaffle ``` -- [PyPi](https://pypi.org/project/pywaffle) (πŸ“₯ 7.8K / month Β· πŸ“¦ 6 Β· ⏱️ 16.06.2024): +- [PyPi](https://pypi.org/project/pywaffle) (πŸ“₯ 10K / month Β· πŸ“¦ 6 Β· ⏱️ 16.06.2024): ``` pip install pywaffle ``` -- [Conda](https://anaconda.org/conda-forge/pywaffle) (πŸ“₯ 13K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/pywaffle) (πŸ“₯ 14K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge pywaffle ``` @@ -1393,7 +1382,7 @@ _General-purpose and task-specific data visualization libraries._ ``` git clone https://github.com/t-makaro/animatplot ``` -- [PyPi](https://pypi.org/project/animatplot) (πŸ“₯ 990 / month Β· πŸ“¦ 4 Β· ⏱️ 29.08.2024): +- [PyPi](https://pypi.org/project/animatplot) (πŸ“₯ 2.3K / month Β· πŸ“¦ 4 Β· ⏱️ 29.08.2024): ``` pip install animatplot ``` @@ -1404,20 +1393,20 @@ _General-purpose and task-specific data visualization libraries._
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“₯ 7.5K Β· πŸ“‹ 140 - 36% open Β· ⏱️ 14.08.2024): +- [GitHub](https://github.com/vega/vegafusion) (πŸ‘¨β€πŸ’» 4 Β· πŸ”€ 18 Β· πŸ“₯ 7.7K Β· πŸ“‹ 140 - 36% open Β· ⏱️ 14.08.2024): ``` git clone https://github.com/vegafusion/vegafusion ``` -- [PyPi](https://pypi.org/project/vegafusion-jupyter) (πŸ“₯ 1.6K / month Β· πŸ“¦ 2 Β· ⏱️ 09.05.2024): +- [PyPi](https://pypi.org/project/vegafusion-jupyter) (πŸ“₯ 3.9K / month Β· πŸ“¦ 2 Β· ⏱️ 09.05.2024): ``` pip install vegafusion-jupyter ``` -- [Conda](https://anaconda.org/conda-forge/vegafusion-python-embed) (πŸ“₯ 240K Β· ⏱️ 10.05.2024): +- [Conda](https://anaconda.org/conda-forge/vegafusion-python-embed) (πŸ“₯ 250K Β· ⏱️ 10.05.2024): ``` conda install -c conda-forge vegafusion-python-embed ``` -- [npm](https://www.npmjs.com/package/vegafusion-jupyter) (πŸ“₯ 250 / month Β· πŸ“¦ 3 Β· ⏱️ 09.05.2024): +- [npm](https://www.npmjs.com/package/vegafusion-jupyter) (πŸ“₯ 170 / month Β· πŸ“¦ 3 Β· ⏱️ 09.05.2024): ``` npm install vegafusion-jupyter ``` @@ -1427,8 +1416,8 @@ _General-purpose and task-specific data visualization libraries._ - 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· ⭐ 7.4K Β· πŸ’€) - Visualizations for machine learning datasets. Apache-2 -- 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 +- pythreejs (πŸ₯‰28 Β· ⭐ 950 Β· πŸ’€) - A Jupyter - Three.js bridge. BSD-3 +- HiPlot (πŸ₯‰25 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· ⭐ 690 Β· πŸ’€) - Dragndrop Pivot Tables and Charts for Jupyter/IPython.. MIT @@ -1450,44 +1439,44 @@ _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’» 2.9K Β· πŸ”€ 27K Β· πŸ“¦ 230K Β· πŸ“‹ 16K - 8% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/huggingface/transformers) (πŸ‘¨β€πŸ’» 2.9K Β· πŸ”€ 27K Β· πŸ“¦ 230K Β· πŸ“‹ 16K - 8% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/huggingface/transformers ``` -- [PyPi](https://pypi.org/project/transformers) (πŸ“₯ 38M / month Β· πŸ“¦ 6.4K Β· ⏱️ 07.10.2024): +- [PyPi](https://pypi.org/project/transformers) (πŸ“₯ 45M / month Β· πŸ“¦ 6.5K Β· ⏱️ 24.10.2024): ``` pip install transformers ``` -- [Conda](https://anaconda.org/conda-forge/transformers) (πŸ“₯ 2.1M Β· ⏱️ 07.10.2024): +- [Conda](https://anaconda.org/conda-forge/transformers) (πŸ“₯ 2.1M Β· ⏱️ 24.10.2024): ``` conda install -c conda-forge transformers ```
spaCy (πŸ₯‡45 Β· ⭐ 30K) - Industrial-strength Natural Language Processing (NLP) in Python. MIT -- [GitHub](https://github.com/explosion/spaCy) (πŸ‘¨β€πŸ’» 760 Β· πŸ”€ 4.4K Β· πŸ“₯ 200 Β· πŸ“¦ 100K Β· πŸ“‹ 5.7K - 2% open Β· ⏱️ 01.10.2024): +- [GitHub](https://github.com/explosion/spaCy) (πŸ‘¨β€πŸ’» 760 Β· πŸ”€ 4.4K Β· πŸ“₯ 290 Β· πŸ“¦ 100K Β· πŸ“‹ 5.7K - 2% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/explosion/spaCy ``` -- [PyPi](https://pypi.org/project/spacy) (πŸ“₯ 13M / month Β· πŸ“¦ 2.7K Β· ⏱️ 01.10.2024): +- [PyPi](https://pypi.org/project/spacy) (πŸ“₯ 14M / month Β· πŸ“¦ 2.7K Β· ⏱️ 01.10.2024): ``` pip install spacy ``` -- [Conda](https://anaconda.org/conda-forge/spacy) (πŸ“₯ 4.2M Β· ⏱️ 22.09.2024): +- [Conda](https://anaconda.org/conda-forge/spacy) (πŸ“₯ 4.3M Β· ⏱️ 22.09.2024): ``` conda install -c conda-forge spacy ```
nltk (πŸ₯‡45 Β· ⭐ 14K) - 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“¦ 310K Β· πŸ“‹ 1.8K - 15% open Β· ⏱️ 25.09.2024): +- [GitHub](https://github.com/nltk/nltk) (πŸ‘¨β€πŸ’» 460 Β· πŸ”€ 2.9K Β· πŸ“¦ 320K Β· πŸ“‹ 1.8K - 15% open Β· ⏱️ 25.09.2024): ``` git clone https://github.com/nltk/nltk ``` -- [PyPi](https://pypi.org/project/nltk) (πŸ“₯ 22M / month Β· πŸ“¦ 4.7K Β· ⏱️ 18.08.2024): +- [PyPi](https://pypi.org/project/nltk) (πŸ“₯ 23M / month Β· πŸ“¦ 4.7K Β· ⏱️ 18.08.2024): ``` pip install nltk ``` @@ -1496,80 +1485,80 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge nltk ```
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litellm (πŸ₯‡42 Β· ⭐ 13K Β· πŸ“‰) - Python SDK, Proxy Server (LLM Gateway) to call 100+.. MIT o t h e r s +
litellm (πŸ₯‡42 Β· ⭐ 13K) - Python SDK, Proxy Server (LLM Gateway) to call 100+.. MIT o t h e r s -- [GitHub](https://github.com/BerriAI/litellm) (πŸ‘¨β€πŸ’» 340 Β· πŸ”€ 1.5K Β· πŸ“₯ 420 Β· πŸ“¦ 3.7K Β· πŸ“‹ 3.4K - 18% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/BerriAI/litellm) (πŸ‘¨β€πŸ’» 350 Β· πŸ”€ 1.5K Β· πŸ“₯ 370 Β· πŸ“¦ 4K Β· πŸ“‹ 3.5K - 19% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/BerriAI/litellm ``` -- [PyPi](https://pypi.org/project/litellm) (πŸ“₯ 2.3M / month Β· πŸ“¦ 450 Β· ⏱️ 09.10.2024): +- [PyPi](https://pypi.org/project/litellm) (πŸ“₯ 3M / month Β· πŸ“¦ 470 Β· ⏱️ 22.10.2024): ``` pip install litellm ```
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gensim (πŸ₯‡40 Β· ⭐ 16K) - Topic Modelling for Humans. ❗️LGPL-2.1 +
sentence-transformers (πŸ₯‡41 Β· ⭐ 15K) - State-of-the-Art Text Embeddings. Apache-2 -- [GitHub](https://github.com/piskvorky/gensim) (πŸ‘¨β€πŸ’» 460 Β· πŸ”€ 4.4K Β· πŸ“₯ 4.9K Β· πŸ“¦ 65K Β· πŸ“‹ 1.8K - 20% open Β· ⏱️ 10.08.2024): +- [GitHub](https://github.com/UKPLab/sentence-transformers) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 2.5K Β· πŸ“¦ 52K Β· πŸ“‹ 2.2K - 53% open Β· ⏱️ 21.10.2024): ``` - git clone https://github.com/RaRe-Technologies/gensim + git clone https://github.com/UKPLab/sentence-transformers ``` -- [PyPi](https://pypi.org/project/gensim) (πŸ“₯ 4.6M / month Β· πŸ“¦ 1.4K Β· ⏱️ 19.07.2024): +- [PyPi](https://pypi.org/project/sentence-transformers) (πŸ“₯ 6.1M / month Β· πŸ“¦ 1.7K Β· ⏱️ 21.10.2024): ``` - pip install gensim + pip install sentence-transformers ``` -- [Conda](https://anaconda.org/conda-forge/gensim) (πŸ“₯ 1.4M Β· ⏱️ 03.09.2024): +- [Conda](https://anaconda.org/conda-forge/sentence-transformers) (πŸ“₯ 420K Β· ⏱️ 21.10.2024): ``` - conda install -c conda-forge gensim + conda install -c conda-forge sentence-transformers ```
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sentence-transformers (πŸ₯‡40 Β· ⭐ 15K Β· πŸ“‰) - State-of-the-Art Text Embeddings. Apache-2 +
Tokenizers (πŸ₯‡40 Β· ⭐ 9K) - Fast State-of-the-Art Tokenizers optimized for Research and.. Apache-2 -- [GitHub](https://github.com/UKPLab/sentence-transformers) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 2.4K Β· πŸ“¦ 50K Β· πŸ“‹ 2.2K - 53% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/huggingface/tokenizers) (πŸ‘¨β€πŸ’» 95 Β· πŸ”€ 790 Β· πŸ“₯ 66 Β· πŸ“¦ 110K Β· πŸ“‹ 1K - 5% open Β· ⏱️ 14.10.2024): ``` - git clone https://github.com/UKPLab/sentence-transformers + git clone https://github.com/huggingface/tokenizers ``` -- [PyPi](https://pypi.org/project/sentence-transformers) (πŸ“₯ 5.5M / month Β· πŸ“¦ 1.6K Β· ⏱️ 19.09.2024): +- [PyPi](https://pypi.org/project/tokenizers) (πŸ“₯ 33M / month Β· πŸ“¦ 1K Β· ⏱️ 10.10.2024): ``` - pip install sentence-transformers + pip install tokenizers ``` -- [Conda](https://anaconda.org/conda-forge/sentence-transformers) (πŸ“₯ 410K Β· ⏱️ 24.09.2024): +- [Conda](https://anaconda.org/conda-forge/tokenizers) (πŸ“₯ 2.1M Β· ⏱️ 10.10.2024): ``` - conda install -c conda-forge sentence-transformers + conda install -c conda-forge tokenizers ```
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Tokenizers (πŸ₯‡40 Β· ⭐ 9K) - Fast State-of-the-Art Tokenizers optimized for Research and.. Apache-2 +
gensim (πŸ₯‡39 Β· ⭐ 16K Β· πŸ“‰) - Topic Modelling for Humans. ❗️LGPL-2.1 -- [GitHub](https://github.com/huggingface/tokenizers) (πŸ‘¨β€πŸ’» 94 Β· πŸ”€ 780 Β· πŸ“₯ 65 Β· πŸ“¦ 110K Β· πŸ“‹ 1K - 4% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/piskvorky/gensim) (πŸ‘¨β€πŸ’» 460 Β· πŸ”€ 4.4K Β· πŸ“₯ 4.9K Β· πŸ“¦ 66K Β· πŸ“‹ 1.8K - 20% open Β· ⏱️ 10.08.2024): ``` - git clone https://github.com/huggingface/tokenizers + git clone https://github.com/RaRe-Technologies/gensim ``` -- [PyPi](https://pypi.org/project/tokenizers) (πŸ“₯ 31M / month Β· πŸ“¦ 1K Β· ⏱️ 10.10.2024): +- [PyPi](https://pypi.org/project/gensim) (πŸ“₯ 4.6M / month Β· πŸ“¦ 1.4K Β· ⏱️ 19.07.2024): ``` - pip install tokenizers + pip install gensim ``` -- [Conda](https://anaconda.org/conda-forge/tokenizers) (πŸ“₯ 2.1M Β· ⏱️ 12.08.2024): +- [Conda](https://anaconda.org/conda-forge/gensim) (πŸ“₯ 1.4M Β· ⏱️ 03.09.2024): ``` - conda install -c conda-forge tokenizers + conda install -c conda-forge gensim ```
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flair (πŸ₯‡39 Β· ⭐ 14K) - A very simple framework for state-of-the-art Natural Language Processing.. MIT +
sentencepiece (πŸ₯‡39 Β· ⭐ 10K) - Unsupervised text tokenizer for Neural Network-based text.. Apache-2 -- [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): +- [GitHub](https://github.com/google/sentencepiece) (πŸ‘¨β€πŸ’» 89 Β· πŸ”€ 1.2K Β· πŸ“₯ 45K Β· πŸ“¦ 81K Β· πŸ“‹ 750 - 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“₯ 98K / month Β· πŸ“¦ 140 Β· ⏱️ 25.07.2024): +- [PyPi](https://pypi.org/project/sentencepiece) (πŸ“₯ 25M / month Β· πŸ“¦ 1.7K Β· ⏱️ 19.02.2024): ``` - pip install flair + pip install sentencepiece ``` -- [Conda](https://anaconda.org/conda-forge/python-flair) (πŸ“₯ 32K Β· ⏱️ 05.01.2024): +- [Conda](https://anaconda.org/conda-forge/sentencepiece) (πŸ“₯ 1.1M Β· ⏱️ 22.10.2024): ``` - conda install -c conda-forge python-flair + conda install -c conda-forge sentencepiece ```
Rasa (πŸ₯‡38 Β· ⭐ 19K Β· πŸ’€) - Open source machine learning framework to automate text- and.. Apache-2 @@ -1579,46 +1568,46 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we ``` git clone https://github.com/RasaHQ/rasa ``` -- [PyPi](https://pypi.org/project/rasa) (πŸ“₯ 160K / month Β· πŸ“¦ 60 Β· ⏱️ 18.04.2024): +- [PyPi](https://pypi.org/project/rasa) (πŸ“₯ 190K / month Β· πŸ“¦ 60 Β· ⏱️ 18.04.2024): ``` pip install rasa ```
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sentencepiece (πŸ₯‡38 Β· ⭐ 10K) - Unsupervised text tokenizer for Neural Network-based text.. Apache-2 +
flair (πŸ₯‡38 Β· ⭐ 14K Β· πŸ“‰) - A very simple framework for state-of-the-art Natural Language.. MIT -- [GitHub](https://github.com/google/sentencepiece) (πŸ‘¨β€πŸ’» 89 Β· πŸ”€ 1.2K Β· πŸ“₯ 45K Β· πŸ“¦ 79K Β· πŸ“‹ 750 - 4% open Β· ⏱️ 18.08.2024): +- [GitHub](https://github.com/flairNLP/flair) (πŸ‘¨β€πŸ’» 270 Β· πŸ”€ 2.1K Β· πŸ“¦ 3.6K Β· πŸ“‹ 2.3K - 4% open Β· ⏱️ 11.10.2024): ``` - git clone https://github.com/google/sentencepiece + git clone https://github.com/flairNLP/flair ``` -- [PyPi](https://pypi.org/project/sentencepiece) (πŸ“₯ 23M / month Β· πŸ“¦ 1.7K Β· ⏱️ 19.02.2024): +- [PyPi](https://pypi.org/project/flair) (πŸ“₯ 110K / month Β· πŸ“¦ 140 Β· ⏱️ 25.07.2024): ``` - pip install sentencepiece + pip install flair ``` -- [Conda](https://anaconda.org/conda-forge/sentencepiece) (πŸ“₯ 1.1M Β· ⏱️ 28.09.2024): +- [Conda](https://anaconda.org/conda-forge/python-flair) (πŸ“₯ 33K Β· ⏱️ 05.01.2024): ``` - conda install -c conda-forge sentencepiece + conda install -c conda-forge python-flair ```
fairseq (πŸ₯‡36 Β· ⭐ 30K) - Facebook AI Research Sequence-to-Sequence Toolkit written in Python. MIT -- [GitHub](https://github.com/facebookresearch/fairseq) (πŸ‘¨β€πŸ’» 430 Β· πŸ”€ 6.4K Β· πŸ“₯ 360 Β· πŸ“¦ 3.6K Β· πŸ“‹ 4.3K - 29% open Β· ⏱️ 03.10.2024): +- [GitHub](https://github.com/facebookresearch/fairseq) (πŸ‘¨β€πŸ’» 430 Β· πŸ”€ 6.4K Β· πŸ“₯ 360 Β· πŸ“¦ 3.6K Β· πŸ“‹ 4.3K - 29% open Β· ⏱️ 18.10.2024): ``` git clone https://github.com/facebookresearch/fairseq ``` -- [PyPi](https://pypi.org/project/fairseq) (πŸ“₯ 150K / month Β· πŸ“¦ 120 Β· ⏱️ 27.06.2022): +- [PyPi](https://pypi.org/project/fairseq) (πŸ“₯ 140K / month Β· πŸ“¦ 120 Β· ⏱️ 27.06.2022): ``` pip install fairseq ``` -- [Conda](https://anaconda.org/conda-forge/fairseq) (πŸ“₯ 95K Β· ⏱️ 22.09.2024): +- [Conda](https://anaconda.org/conda-forge/fairseq) (πŸ“₯ 97K Β· ⏱️ 22.09.2024): ``` conda install -c conda-forge fairseq ```
NeMo (πŸ₯‡36 Β· ⭐ 12K) - A scalable generative AI framework built for researchers and.. Apache-2 -- [GitHub](https://github.com/NVIDIA/NeMo) (πŸ‘¨β€πŸ’» 350 Β· πŸ”€ 2.4K Β· πŸ“₯ 270K Β· πŸ“¦ 21 Β· πŸ“‹ 2.4K - 6% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/NVIDIA/NeMo) (πŸ‘¨β€πŸ’» 360 Β· πŸ”€ 2.5K Β· πŸ“₯ 280K Β· πŸ“¦ 21 Β· πŸ“‹ 2.4K - 7% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/NVIDIA/NeMo @@ -1630,7 +1619,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we
TextBlob (πŸ₯‡36 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“¦ 43K Β· πŸ“‹ 280 - 38% open Β· ⏱️ 07.08.2024): +- [GitHub](https://github.com/sloria/TextBlob) (πŸ‘¨β€πŸ’» 37 Β· πŸ”€ 1.1K Β· πŸ“₯ 120 Β· πŸ“¦ 44K Β· πŸ“‹ 280 - 39% open Β· ⏱️ 07.08.2024): ``` git clone https://github.com/sloria/TextBlob @@ -1644,18 +1633,6 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge textblob ```
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spark-nlp (πŸ₯‡36 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”€ 710 Β· πŸ“¦ 510 Β· πŸ“‹ 890 - 4% open Β· ⏱️ 28.09.2024): - - ``` - git clone https://github.com/JohnSnowLabs/spark-nlp - ``` -- [PyPi](https://pypi.org/project/spark-nlp) (πŸ“₯ 4M / month Β· πŸ“¦ 37 Β· ⏱️ 25.09.2024): - ``` - pip install spark-nlp - ``` -
fastText (πŸ₯ˆ35 Β· ⭐ 26K Β· πŸ’€) - Library for fast text representation and classification. MIT - [GitHub](https://github.com/facebookresearch/fastText) (πŸ‘¨β€πŸ’» 68 Β· πŸ”€ 4.7K Β· πŸ“¦ 6.7K Β· πŸ“‹ 1.2K - 47% open Β· ⏱️ 13.03.2024): @@ -1663,51 +1640,63 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we ``` git clone https://github.com/facebookresearch/fastText ``` -- [PyPi](https://pypi.org/project/fasttext) (πŸ“₯ 1.8M / month Β· πŸ“¦ 250 Β· ⏱️ 12.06.2024): +- [PyPi](https://pypi.org/project/fasttext) (πŸ“₯ 1.6M / month Β· πŸ“¦ 250 Β· ⏱️ 12.06.2024): ``` pip install fasttext ``` -- [Conda](https://anaconda.org/conda-forge/fasttext) (πŸ“₯ 100K Β· ⏱️ 19.05.2024): +- [Conda](https://anaconda.org/conda-forge/fasttext) (πŸ“₯ 110K Β· ⏱️ 19.05.2024): ``` conda install -c conda-forge fasttext ```
haystack (πŸ₯ˆ35 Β· ⭐ 17K) - AI orchestration framework to build customizable, production-ready.. Apache-2 -- [GitHub](https://github.com/deepset-ai/haystack) (πŸ‘¨β€πŸ’» 270 Β· πŸ”€ 1.9K Β· πŸ“¦ 550 Β· πŸ“‹ 3.5K - 3% open Β· ⏱️ 08.10.2024): +- [GitHub](https://github.com/deepset-ai/haystack) (πŸ‘¨β€πŸ’» 270 Β· πŸ”€ 1.9K Β· πŸ“¦ 580 Β· πŸ“‹ 3.6K - 3% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/deepset-ai/haystack ``` -- [PyPi](https://pypi.org/project/haystack) (πŸ“₯ 6.4K / month Β· πŸ“¦ 5 Β· ⏱️ 15.12.2021): +- [PyPi](https://pypi.org/project/haystack) (πŸ“₯ 7.3K / month Β· πŸ“¦ 5 Β· ⏱️ 15.12.2021): ``` pip install haystack ```
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spark-nlp (πŸ₯ˆ35 Β· ⭐ 3.9K Β· πŸ“‰) - State of the Art Natural Language Processing. Apache-2 + +- [GitHub](https://github.com/JohnSnowLabs/spark-nlp) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 710 Β· πŸ“¦ 510 Β· πŸ“‹ 890 - 4% open Β· ⏱️ 18.10.2024): + + ``` + git clone https://github.com/JohnSnowLabs/spark-nlp + ``` +- [PyPi](https://pypi.org/project/spark-nlp) (πŸ“₯ 3.7M / month Β· πŸ“¦ 37 Β· ⏱️ 25.09.2024): + ``` + pip install spark-nlp + ``` +
stanza (πŸ₯ˆ34 Β· ⭐ 7.3K) - Stanford NLP Python library for tokenization, sentence segmentation,.. Apache-2 -- [GitHub](https://github.com/stanfordnlp/stanza) (πŸ‘¨β€πŸ’» 68 Β· πŸ”€ 880 Β· πŸ“¦ 3.1K Β· πŸ“‹ 900 - 10% open Β· ⏱️ 12.09.2024): +- [GitHub](https://github.com/stanfordnlp/stanza) (πŸ‘¨β€πŸ’» 68 Β· πŸ”€ 890 Β· πŸ“¦ 3.2K Β· πŸ“‹ 900 - 10% open Β· ⏱️ 12.09.2024): ``` git clone https://github.com/stanfordnlp/stanza ``` -- [PyPi](https://pypi.org/project/stanza) (πŸ“₯ 280K / month Β· πŸ“¦ 180 Β· ⏱️ 12.09.2024): +- [PyPi](https://pypi.org/project/stanza) (πŸ“₯ 260K / month Β· πŸ“¦ 180 Β· ⏱️ 12.09.2024): ``` pip install stanza ``` -- [Conda](https://anaconda.org/stanfordnlp/stanza) (πŸ“₯ 7.9K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/stanfordnlp/stanza) (πŸ“₯ 8.1K Β· ⏱️ 16.06.2023): ``` conda install -c stanfordnlp stanza ```
rubrix (πŸ₯ˆ34 Β· ⭐ 3.9K) - Argilla is a collaboration tool for AI engineers and domain experts.. Apache-2 -- [GitHub](https://github.com/argilla-io/argilla) (πŸ‘¨β€πŸ’» 96 Β· πŸ”€ 360 Β· πŸ“¦ 2.7K Β· πŸ“‹ 2.1K - 5% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/argilla-io/argilla) (πŸ‘¨β€πŸ’» 97 Β· πŸ”€ 360 Β· πŸ“¦ 2.8K Β· πŸ“‹ 2.1K - 5% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/recognai/rubrix ``` -- [PyPi](https://pypi.org/project/rubrix) (πŸ“₯ 1.8K / month Β· ⏱️ 24.10.2022): +- [PyPi](https://pypi.org/project/rubrix) (πŸ“₯ 3.7K / month Β· ⏱️ 24.10.2022): ``` pip install rubrix ``` @@ -1716,58 +1705,42 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge rubrix ```
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jellyfish (πŸ₯ˆ34 Β· ⭐ 2K) - a python library for doing approximate and phonetic matching of strings. MIT +
jellyfish (πŸ₯ˆ34 Β· ⭐ 2.1K) - a python library for doing approximate and phonetic matching of strings. MIT -- [GitHub](https://github.com/jamesturk/jellyfish) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 160 Β· πŸ“¦ 11K Β· πŸ“‹ 140 - 5% open Β· ⏱️ 07.09.2024): +- [GitHub](https://github.com/jamesturk/jellyfish) (πŸ‘¨β€πŸ’» 33 Β· πŸ”€ 160 Β· πŸ“¦ 11K Β· πŸ“‹ 140 - 5% open Β· ⏱️ 19.10.2024): ``` git clone https://github.com/jamesturk/jellyfish ``` -- [PyPi](https://pypi.org/project/jellyfish) (πŸ“₯ 5.8M / month Β· πŸ“¦ 270 Β· ⏱️ 28.07.2024): +- [PyPi](https://pypi.org/project/jellyfish) (πŸ“₯ 6.1M / month Β· πŸ“¦ 270 Β· ⏱️ 28.07.2024): ``` pip install jellyfish ``` -- [Conda](https://anaconda.org/conda-forge/jellyfish) (πŸ“₯ 1M Β· ⏱️ 06.09.2024): +- [Conda](https://anaconda.org/conda-forge/jellyfish) (πŸ“₯ 1.1M Β· ⏱️ 06.09.2024): ``` conda install -c conda-forge jellyfish ```
TensorFlow Text (πŸ₯ˆ34 Β· ⭐ 1.2K) - Making text a first-class citizen in TensorFlow. Apache-2 -- [GitHub](https://github.com/tensorflow/text) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 340 Β· πŸ“¦ 7.4K Β· πŸ“‹ 360 - 52% open Β· ⏱️ 05.09.2024): +- [GitHub](https://github.com/tensorflow/text) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 340 Β· πŸ“¦ 7.5K Β· πŸ“‹ 360 - 52% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/tensorflow/text ``` -- [PyPi](https://pypi.org/project/tensorflow-text) (πŸ“₯ 7.7M / month Β· πŸ“¦ 220 Β· ⏱️ 30.09.2024): +- [PyPi](https://pypi.org/project/tensorflow-text) (πŸ“₯ 8.3M / month Β· πŸ“¦ 220 Β· ⏱️ 30.09.2024): ``` pip install tensorflow-text ```
qdrant (πŸ₯ˆ33 Β· ⭐ 20K) - Qdrant - High-performance, massive-scale Vector Database for the next.. Apache-2 -- [GitHub](https://github.com/qdrant/qdrant) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 1.4K Β· πŸ“₯ 210K Β· πŸ“¦ 110 Β· πŸ“‹ 1.3K - 23% open Β· ⏱️ 08.10.2024): +- [GitHub](https://github.com/qdrant/qdrant) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 1.4K Β· πŸ“₯ 240K Β· πŸ“¦ 120 Β· πŸ“‹ 1.3K - 23% open Β· ⏱️ 11.10.2024): ``` git clone https://github.com/qdrant/qdrant ```
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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’» 20 Β· πŸ”€ 120 Β· πŸ“₯ 15 Β· πŸ“¦ 23K Β· πŸ“‹ 140 - 8% open Β· ⏱️ 10.10.2024): - - ``` - git clone https://github.com/rspeer/python-ftfy - ``` -- [PyPi](https://pypi.org/project/ftfy) (πŸ“₯ 5.5M / month Β· πŸ“¦ 560 Β· ⏱️ 06.08.2024): - ``` - pip install ftfy - ``` -- [Conda](https://anaconda.org/conda-forge/ftfy) (πŸ“₯ 300K Β· ⏱️ 06.08.2024): - ``` - conda install -c conda-forge ftfy - ``` -
ParlAI (πŸ₯ˆ32 Β· ⭐ 10K Β· πŸ’€) - A framework for training and evaluating AI models on a variety of.. MIT - [GitHub](https://github.com/facebookresearch/ParlAI) (πŸ‘¨β€πŸ’» 220 Β· πŸ”€ 2.1K Β· πŸ“¦ 260 Β· πŸ“‹ 1.5K - 3% open Β· ⏱️ 03.11.2023): @@ -1775,19 +1748,19 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we ``` git clone https://github.com/facebookresearch/ParlAI ``` -- [PyPi](https://pypi.org/project/parlai) (πŸ“₯ 3.8K / month Β· πŸ“¦ 5 Β· ⏱️ 20.09.2022): +- [PyPi](https://pypi.org/project/parlai) (πŸ“₯ 4.3K / month Β· πŸ“¦ 5 Β· ⏱️ 20.09.2022): ``` pip install parlai ```
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OpenNMT (πŸ₯ˆ32 Β· ⭐ 6.7K) - Open Source Neural Machine Translation and (Large) Language Models.. MIT +
OpenNMT (πŸ₯ˆ32 Β· ⭐ 6.8K) - Open Source Neural Machine Translation and (Large) Language Models.. MIT - [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/OpenNMT/OpenNMT-py ``` -- [PyPi](https://pypi.org/project/OpenNMT-py) (πŸ“₯ 9.8K / month Β· πŸ“¦ 23 Β· ⏱️ 18.03.2024): +- [PyPi](https://pypi.org/project/OpenNMT-py) (πŸ“₯ 11K / month Β· πŸ“¦ 23 Β· ⏱️ 18.03.2024): ``` pip install OpenNMT-py ``` @@ -1799,11 +1772,11 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we ``` git clone https://github.com/dedupeio/dedupe ``` -- [PyPi](https://pypi.org/project/dedupe) (πŸ“₯ 150K / month Β· πŸ“¦ 19 Β· ⏱️ 15.08.2024): +- [PyPi](https://pypi.org/project/dedupe) (πŸ“₯ 180K / month Β· πŸ“¦ 19 Β· ⏱️ 15.08.2024): ``` pip install dedupe ``` -- [Conda](https://anaconda.org/conda-forge/dedupe) (πŸ“₯ 75K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/dedupe) (πŸ“₯ 78K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge dedupe ``` @@ -1815,7 +1788,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we ``` git clone https://github.com/pytorch/text ``` -- [PyPi](https://pypi.org/project/torchtext) (πŸ“₯ 1.4M / month Β· πŸ“¦ 280 Β· ⏱️ 24.04.2024): +- [PyPi](https://pypi.org/project/torchtext) (πŸ“₯ 1.5M / month Β· πŸ“¦ 280 Β· ⏱️ 24.04.2024): ``` pip install torchtext ``` @@ -1827,7 +1800,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we ``` git clone https://github.com/deepmipt/DeepPavlov ``` -- [PyPi](https://pypi.org/project/deeppavlov) (πŸ“₯ 13K / month Β· πŸ“¦ 4 Β· ⏱️ 12.08.2024): +- [PyPi](https://pypi.org/project/deeppavlov) (πŸ“₯ 15K / month Β· πŸ“¦ 4 Β· ⏱️ 12.08.2024): ``` pip install deeppavlov ``` @@ -1839,101 +1812,101 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we ``` git clone https://github.com/life4/textdistance ``` -- [PyPi](https://pypi.org/project/textdistance) (πŸ“₯ 910K / month Β· πŸ“¦ 99 Β· ⏱️ 16.07.2024): +- [PyPi](https://pypi.org/project/textdistance) (πŸ“₯ 880K / month Β· πŸ“¦ 99 Β· ⏱️ 16.07.2024): ``` pip install textdistance ``` -- [Conda](https://anaconda.org/conda-forge/textdistance) (πŸ“₯ 640K Β· ⏱️ 17.07.2024): +- [Conda](https://anaconda.org/conda-forge/textdistance) (πŸ“₯ 650K Β· ⏱️ 17.07.2024): ``` conda install -c conda-forge textdistance ```
snowballstemmer (πŸ₯ˆ30 Β· ⭐ 760) - Snowball compiler and stemming algorithms. BSD-3 -- [GitHub](https://github.com/snowballstem/snowball) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 170 Β· πŸ“¦ 10 Β· πŸ“‹ 89 - 30% open Β· ⏱️ 10.09.2024): +- [GitHub](https://github.com/snowballstem/snowball) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 170 Β· πŸ“¦ 10 Β· πŸ“‹ 92 - 29% open Β· ⏱️ 16.10.2024): ``` git clone https://github.com/snowballstem/snowball ``` -- [PyPi](https://pypi.org/project/snowballstemmer) (πŸ“₯ 24M / month Β· πŸ“¦ 450 Β· ⏱️ 16.11.2021): +- [PyPi](https://pypi.org/project/snowballstemmer) (πŸ“₯ 23M / month Β· πŸ“¦ 450 Β· ⏱️ 16.11.2021): ``` pip install snowballstemmer ``` -- [Conda](https://anaconda.org/conda-forge/snowballstemmer) (πŸ“₯ 8.7M Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/snowballstemmer) (πŸ“₯ 8.8M Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge snowballstemmer ```
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Sumy (πŸ₯ˆ29 Β· ⭐ 3.5K) - Module for automatic summarization of text documents and HTML pages. Apache-2 +
SciSpacy (πŸ₯ˆ29 Β· ⭐ 1.7K) - A full spaCy pipeline and models for scientific/biomedical documents. Apache-2 -- [GitHub](https://github.com/miso-belica/sumy) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 530 Β· πŸ“¦ 3.1K Β· πŸ“‹ 120 - 18% open Β· ⏱️ 16.05.2024): +- [GitHub](https://github.com/allenai/scispacy) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 220 Β· πŸ“¦ 980 Β· πŸ“‹ 320 - 9% open Β· ⏱️ 15.09.2024): ``` - git clone https://github.com/miso-belica/sumy - ``` -- [PyPi](https://pypi.org/project/sumy) (πŸ“₯ 450K / month Β· πŸ“¦ 31 Β· ⏱️ 23.10.2022): - ``` - pip install sumy + git clone https://github.com/allenai/scispacy ``` -- [Conda](https://anaconda.org/conda-forge/sumy) (πŸ“₯ 9.4K Β· ⏱️ 16.06.2023): +- [PyPi](https://pypi.org/project/scispacy) (πŸ“₯ 26K / month Β· πŸ“¦ 34 Β· ⏱️ 08.03.2024): ``` - conda install -c conda-forge sumy + pip install scispacy ```
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SciSpacy (πŸ₯ˆ29 Β· ⭐ 1.7K) - A full spaCy pipeline and models for scientific/biomedical documents. Apache-2 +
CLTK (πŸ₯ˆ29 Β· ⭐ 840) - The Classical Language Toolkit. MIT -- [GitHub](https://github.com/allenai/scispacy) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 220 Β· πŸ“¦ 970 Β· πŸ“‹ 320 - 9% open Β· ⏱️ 15.09.2024): +- [GitHub](https://github.com/cltk/cltk) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 330 Β· πŸ“₯ 98 Β· πŸ“¦ 270 Β· πŸ“‹ 570 - 6% open Β· ⏱️ 12.05.2024): ``` - git clone https://github.com/allenai/scispacy + git clone https://github.com/cltk/cltk ``` -- [PyPi](https://pypi.org/project/scispacy) (πŸ“₯ 24K / month Β· πŸ“¦ 34 Β· ⏱️ 08.03.2024): +- [PyPi](https://pypi.org/project/cltk) (πŸ“₯ 14K / month Β· πŸ“¦ 15 Β· ⏱️ 12.05.2024): ``` - pip install scispacy + pip install cltk ```
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spacy-transformers (πŸ₯ˆ29 Β· ⭐ 1.3K) - Use pretrained transformers like BERT, XLNet and GPT-2.. MIT spacy +
Ciphey (πŸ₯ˆ28 Β· ⭐ 18K Β· πŸ’€) - Automatically decrypt encryptions without knowing the key or cipher,.. MIT -- [GitHub](https://github.com/explosion/spacy-transformers) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 160 Β· πŸ“¦ 1.9K Β· ⏱️ 05.06.2024): +- [GitHub](https://github.com/Ciphey/Ciphey) (πŸ‘¨β€πŸ’» 48 Β· πŸ”€ 1.2K Β· πŸ“‹ 340 - 22% open Β· ⏱️ 12.10.2023): ``` - git clone https://github.com/explosion/spacy-transformers + git clone https://github.com/Ciphey/Ciphey ``` -- [PyPi](https://pypi.org/project/spacy-transformers) (πŸ“₯ 560K / month Β· πŸ“¦ 87 Β· ⏱️ 25.04.2024): +- [PyPi](https://pypi.org/project/ciphey) (πŸ“₯ 190K / month Β· ⏱️ 06.06.2021): ``` - pip install spacy-transformers + pip install ciphey ``` -- [Conda](https://anaconda.org/conda-forge/spacy-transformers) (πŸ“₯ 66K Β· ⏱️ 19.12.2023): +- [Docker Hub](https://hub.docker.com/r/remnux/ciphey) (πŸ“₯ 26K Β· ⭐ 17 Β· ⏱️ 14.10.2023): ``` - conda install -c conda-forge spacy-transformers + docker pull remnux/ciphey ```
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CLTK (πŸ₯ˆ29 Β· ⭐ 840) - The Classical Language Toolkit. MIT +
Sumy (πŸ₯ˆ28 Β· ⭐ 3.5K) - Module for automatic summarization of text documents and HTML pages. Apache-2 -- [GitHub](https://github.com/cltk/cltk) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 330 Β· πŸ“₯ 95 Β· πŸ“¦ 270 Β· πŸ“‹ 570 - 6% open Β· ⏱️ 12.05.2024): +- [GitHub](https://github.com/miso-belica/sumy) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 530 Β· πŸ“¦ 3.2K Β· πŸ“‹ 120 - 18% open Β· ⏱️ 16.05.2024): ``` - git clone https://github.com/cltk/cltk + git clone https://github.com/miso-belica/sumy ``` -- [PyPi](https://pypi.org/project/cltk) (πŸ“₯ 8.8K / month Β· πŸ“¦ 15 Β· ⏱️ 12.05.2024): +- [PyPi](https://pypi.org/project/sumy) (πŸ“₯ 400K / month Β· πŸ“¦ 31 Β· ⏱️ 23.10.2022): ``` - pip install cltk + pip install sumy + ``` +- [Conda](https://anaconda.org/conda-forge/sumy) (πŸ“₯ 9.6K Β· ⏱️ 16.06.2023): + ``` + conda install -c conda-forge sumy ```
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Ciphey (πŸ₯‰27 Β· ⭐ 18K Β· πŸ’€) - Automatically decrypt encryptions without knowing the key or cipher,.. MIT +
spacy-transformers (πŸ₯ˆ28 Β· ⭐ 1.3K) - Use pretrained transformers like BERT, XLNet and GPT-2.. MIT spacy -- [GitHub](https://github.com/Ciphey/Ciphey) (πŸ‘¨β€πŸ’» 48 Β· πŸ”€ 1.1K Β· πŸ“‹ 340 - 21% open Β· ⏱️ 12.10.2023): +- [GitHub](https://github.com/explosion/spacy-transformers) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 160 Β· πŸ“¦ 1.9K Β· ⏱️ 05.06.2024): ``` - git clone https://github.com/Ciphey/Ciphey + git clone https://github.com/explosion/spacy-transformers ``` -- [PyPi](https://pypi.org/project/ciphey) (πŸ“₯ 50K / month Β· ⏱️ 06.06.2021): +- [PyPi](https://pypi.org/project/spacy-transformers) (πŸ“₯ 400K / month Β· πŸ“¦ 87 Β· ⏱️ 25.04.2024): ``` - pip install ciphey + pip install spacy-transformers ``` -- [Docker Hub](https://hub.docker.com/r/remnux/ciphey) (πŸ“₯ 26K Β· ⭐ 17 Β· ⏱️ 14.10.2023): +- [Conda](https://anaconda.org/conda-forge/spacy-transformers) (πŸ“₯ 68K Β· ⏱️ 19.12.2023): ``` - docker pull remnux/ciphey + conda install -c conda-forge spacy-transformers ```
english-words (πŸ₯‰27 Β· ⭐ 11K) - A text file containing 479k English words for all your.. Unlicense @@ -1943,19 +1916,19 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we ``` git clone https://github.com/dwyl/english-words ``` -- [PyPi](https://pypi.org/project/english-words) (πŸ“₯ 81K / month Β· πŸ“¦ 14 Β· ⏱️ 24.05.2023): +- [PyPi](https://pypi.org/project/english-words) (πŸ“₯ 190K / month Β· πŸ“¦ 14 Β· ⏱️ 24.05.2023): ``` pip install english-words ```
DeepKE (πŸ₯‰27 Β· ⭐ 3.5K) - [EMNLP 2022] An Open Toolkit for Knowledge Graph Extraction and.. MIT -- [GitHub](https://github.com/zjunlp/DeepKE) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 670 Β· πŸ“¦ 24 Β· πŸ“‹ 560 - 1% open Β· ⏱️ 14.09.2024): +- [GitHub](https://github.com/zjunlp/DeepKE) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 680 Β· πŸ“¦ 24 Β· πŸ“‹ 570 - 1% open Β· ⏱️ 22.10.2024): ``` git clone https://github.com/zjunlp/deepke ``` -- [PyPi](https://pypi.org/project/deepke) (πŸ“₯ 4.1K / month Β· ⏱️ 21.09.2023): +- [PyPi](https://pypi.org/project/deepke) (πŸ“₯ 5.4K / month Β· ⏱️ 21.09.2023): ``` pip install deepke ``` @@ -1967,11 +1940,11 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we ``` git clone https://github.com/JasonKessler/scattertext ``` -- [PyPi](https://pypi.org/project/scattertext) (πŸ“₯ 19K / month Β· πŸ“¦ 5 Β· ⏱️ 23.09.2024): +- [PyPi](https://pypi.org/project/scattertext) (πŸ“₯ 22K / month Β· πŸ“¦ 5 Β· ⏱️ 23.09.2024): ``` pip install scattertext ``` -- [Conda](https://anaconda.org/conda-forge/scattertext) (πŸ“₯ 99K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/scattertext) (πŸ“₯ 100K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge scattertext ``` @@ -1983,19 +1956,31 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we ``` git clone https://github.com/DerwenAI/pytextrank ``` -- [PyPi](https://pypi.org/project/pytextrank) (πŸ“₯ 70K / month Β· πŸ“¦ 19 Β· ⏱️ 21.02.2024): +- [PyPi](https://pypi.org/project/pytextrank) (πŸ“₯ 66K / month Β· πŸ“¦ 19 Β· ⏱️ 21.02.2024): ``` pip install pytextrank ```
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T5 (πŸ₯‰25 Β· ⭐ 6.1K) - Code for the paper Exploring the Limits of Transfer Learning with a.. Apache-2 +
Opik (πŸ₯‰25 Β· ⭐ 1.8K) - Open-source end-to-end LLM Development Platform. Apache-2 + +- [GitHub](https://github.com/comet-ml/opik) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 110 Β· πŸ“‹ 34 - 29% open Β· ⏱️ 24.10.2024): + + ``` + git clone https://github.com/comet-ml/opik + ``` +- [PyPi](https://pypi.org/project/opik) (πŸ“₯ 5.5K / month Β· ⏱️ 23.10.2024): + ``` + pip install opik + ``` +
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T5 (πŸ₯‰24 Β· ⭐ 6.1K) - Code for the paper Exploring the Limits of Transfer Learning with a.. Apache-2 - [GitHub](https://github.com/google-research/text-to-text-transfer-transformer) (πŸ‘¨β€πŸ’» 59 Β· πŸ”€ 750 Β· πŸ“‹ 450 - 23% open Β· ⏱️ 28.06.2024): ``` git clone https://github.com/google-research/text-to-text-transfer-transformer ``` -- [PyPi](https://pypi.org/project/t5) (πŸ“₯ 60K / month Β· πŸ“¦ 2 Β· ⏱️ 18.10.2021): +- [PyPi](https://pypi.org/project/t5) (πŸ“₯ 47K / month Β· πŸ“¦ 2 Β· ⏱️ 18.10.2021): ``` pip install t5 ``` @@ -2012,16 +1997,16 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install promptsource ```
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Opik (πŸ₯‰24 Β· ⭐ 1.6K) - Open-source end-to-end LLM Development Platform. Apache-2 +
detoxify (πŸ₯‰23 Β· ⭐ 940) - Trained models & code to predict toxic comments on all 3 Jigsaw.. Apache-2 -- [GitHub](https://github.com/comet-ml/opik) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 96 Β· πŸ“‹ 20 - 15% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/unitaryai/detoxify) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 120 Β· πŸ“₯ 710K Β· πŸ“¦ 710 Β· πŸ“‹ 67 - 56% open Β· ⏱️ 19.09.2024): ``` - git clone https://github.com/comet-ml/opik + git clone https://github.com/unitaryai/detoxify ``` -- [PyPi](https://pypi.org/project/opik) (πŸ“₯ 3.2K / month Β· ⏱️ 10.10.2024): +- [PyPi](https://pypi.org/project/detoxify) (πŸ“₯ 55K / month Β· πŸ“¦ 30 Β· ⏱️ 01.02.2024): ``` - pip install opik + pip install detoxify ```
finetune (πŸ₯‰23 Β· ⭐ 700) - Scikit-learn style model finetuning for NLP. MPL-2.0 @@ -2031,27 +2016,11 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we ``` git clone https://github.com/IndicoDataSolutions/finetune ``` -- [PyPi](https://pypi.org/project/finetune) (πŸ“₯ 1.6K / month Β· πŸ“¦ 2 Β· ⏱️ 29.09.2023): +- [PyPi](https://pypi.org/project/finetune) (πŸ“₯ 2.3K / month Β· πŸ“¦ 2 Β· ⏱️ 29.09.2023): ``` pip install finetune ```
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small-text (πŸ₯‰23 Β· ⭐ 550) - Active Learning for Text Classification in Python. MIT - -- [GitHub](https://github.com/webis-de/small-text) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 60 Β· πŸ“¦ 32 Β· πŸ“‹ 57 - 22% open Β· ⏱️ 18.08.2024): - - ``` - git clone https://github.com/webis-de/small-text - ``` -- [PyPi](https://pypi.org/project/small-text) (πŸ“₯ 1.6K / month Β· ⏱️ 18.08.2024): - ``` - pip install small-text - ``` -- [Conda](https://anaconda.org/conda-forge/small-text) (πŸ“₯ 9.5K Β· ⏱️ 18.08.2024): - ``` - conda install -c conda-forge small-text - ``` -
happy-transformer (πŸ₯‰23 Β· ⭐ 520 Β· πŸ’€) - 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”€ 66 Β· πŸ“¦ 290 Β· πŸ“‹ 130 - 15% open Β· ⏱️ 19.03.2024): @@ -2059,7 +2028,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we ``` git clone https://github.com/EricFillion/happy-transformer ``` -- [PyPi](https://pypi.org/project/happytransformer) (πŸ“₯ 2.9K / month Β· πŸ“¦ 5 Β· ⏱️ 05.08.2023): +- [PyPi](https://pypi.org/project/happytransformer) (πŸ“₯ 4.1K / month Β· πŸ“¦ 5 Β· ⏱️ 05.08.2023): ``` pip install happytransformer ``` @@ -2071,43 +2040,47 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we ``` git clone https://github.com/utterworks/fast-bert ``` -- [PyPi](https://pypi.org/project/fast-bert) (πŸ“₯ 4K / month Β· ⏱️ 19.08.2024): +- [PyPi](https://pypi.org/project/fast-bert) (πŸ“₯ 7.2K / month Β· ⏱️ 19.08.2024): ``` pip install fast-bert ```
Sockeye (πŸ₯‰22 Β· ⭐ 1.2K) - Sequence-to-sequence framework with a focus on Neural Machine.. Apache-2 -- [GitHub](https://github.com/awslabs/sockeye) (πŸ‘¨β€πŸ’» 60 Β· πŸ”€ 320 Β· πŸ“₯ 21 Β· πŸ“‹ 310 - 3% open Β· ⏱️ 07.06.2024): +- [GitHub](https://github.com/awslabs/sockeye) (πŸ‘¨β€πŸ’» 60 Β· πŸ”€ 320 Β· πŸ“₯ 21 Β· πŸ“‹ 310 - 3% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/awslabs/sockeye ``` -- [PyPi](https://pypi.org/project/sockeye) (πŸ“₯ 3.7K / month Β· ⏱️ 03.03.2023): +- [PyPi](https://pypi.org/project/sockeye) (πŸ“₯ 5.4K / month Β· ⏱️ 03.03.2023): ``` pip install sockeye ```
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detoxify (πŸ₯‰22 Β· ⭐ 940) - Trained models & code to predict toxic comments on all 3 Jigsaw.. Apache-2 +
small-text (πŸ₯‰22 Β· ⭐ 550) - Active Learning for Text Classification in Python. MIT -- [GitHub](https://github.com/unitaryai/detoxify) (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 120 Β· πŸ“₯ 690K Β· πŸ“¦ 700 Β· πŸ“‹ 67 - 56% open Β· ⏱️ 19.09.2024): +- [GitHub](https://github.com/webis-de/small-text) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 60 Β· πŸ“¦ 32 Β· πŸ“‹ 58 - 24% open Β· ⏱️ 18.08.2024): ``` - git clone https://github.com/unitaryai/detoxify + git clone https://github.com/webis-de/small-text ``` -- [PyPi](https://pypi.org/project/detoxify) (πŸ“₯ 39K / month Β· πŸ“¦ 30 Β· ⏱️ 01.02.2024): +- [PyPi](https://pypi.org/project/small-text) (πŸ“₯ 2.2K / month Β· ⏱️ 18.08.2024): ``` - pip install detoxify + pip install small-text + ``` +- [Conda](https://anaconda.org/conda-forge/small-text) (πŸ“₯ 9.8K Β· ⏱️ 18.08.2024): + ``` + conda install -c conda-forge small-text ```
UForm (πŸ₯‰20 Β· ⭐ 1K) - Pocket-Sized Multimodal AI for content understanding and generation.. Apache-2 -- [GitHub](https://github.com/unum-cloud/uform) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 62 Β· πŸ“₯ 410 Β· πŸ“¦ 6 Β· πŸ“‹ 30 - 30% open Β· ⏱️ 01.10.2024): +- [GitHub](https://github.com/unum-cloud/uform) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 62 Β· πŸ“₯ 430 Β· πŸ“¦ 6 Β· πŸ“‹ 30 - 30% open Β· ⏱️ 01.10.2024): ``` git clone https://github.com/unum-cloud/uform ``` -- [PyPi](https://pypi.org/project/uform) (πŸ“₯ 1.9K / month Β· πŸ“¦ 2 Β· ⏱️ 01.10.2024): +- [PyPi](https://pypi.org/project/uform) (πŸ“₯ 2.8K / month Β· πŸ“¦ 2 Β· ⏱️ 01.10.2024): ``` pip install uform ``` @@ -2119,7 +2092,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we ``` git clone https://github.com/dsfsi/textaugment ``` -- [PyPi](https://pypi.org/project/textaugment) (πŸ“₯ 5.6K / month Β· πŸ“¦ 4 Β· ⏱️ 16.11.2023): +- [PyPi](https://pypi.org/project/textaugment) (πŸ“₯ 5.3K / month Β· πŸ“¦ 4 Β· ⏱️ 16.11.2023): ``` pip install textaugment ``` @@ -2139,55 +2112,56 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we ``` git clone https://github.com/facebookresearch/vizseq ``` -- [PyPi](https://pypi.org/project/vizseq) (πŸ“₯ 290 / month Β· ⏱️ 07.08.2020): +- [PyPi](https://pypi.org/project/vizseq) (πŸ“₯ 550 / month Β· ⏱️ 07.08.2020): ``` pip install vizseq ```
-
Show 52 hidden projects... +
Show 53 hidden projects... - AllenNLP (πŸ₯‡36 Β· ⭐ 12K Β· πŸ’€) - An open-source NLP research library, built on PyTorch. Apache-2 - ChatterBot (πŸ₯ˆ35 Β· ⭐ 14K Β· πŸ’€) - ChatterBot is a machine learning, conversational dialog engine.. BSD-3 +- ftfy (πŸ₯ˆ32 Β· ⭐ 3.8K) - Fixes mojibake and other glitches in Unicode text, after the fact. ❗Unlicensed - 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 - langid (πŸ₯ˆ28 Β· ⭐ 2.3K Β· πŸ’€) - Stand-alone language identification system. BSD-3 +- FARM (πŸ₯ˆ28 Β· ⭐ 1.7K Β· πŸ’€) - Fast & easy transfer learning for NLP. Harvesting language.. Apache-2 - underthesea (πŸ₯ˆ28 Β· ⭐ 1.4K) - Underthesea - Vietnamese NLP Toolkit. ❗️GPL-3.0 - vaderSentiment (πŸ₯‰27 Β· ⭐ 4.4K Β· πŸ’€) - VADER Sentiment Analysis. VADER (Valence Aware Dictionary.. MIT - textacy (πŸ₯‰27 Β· ⭐ 2.2K Β· πŸ’€) - NLP, before and after spaCy. ❗Unlicensed -- FARM (πŸ₯‰27 Β· ⭐ 1.7K Β· πŸ’€) - Fast & easy transfer learning for NLP. Harvesting language.. Apache-2 -- pySBD (πŸ₯‰27 Β· ⭐ 790 Β· πŸ’€) - pySBD (Python Sentence Boundary Disambiguation) is a rule-based sentence.. MIT +- pySBD (πŸ₯‰27 Β· ⭐ 800 Β· πŸ’€) - pySBD (Python Sentence Boundary Disambiguation) is a rule-based sentence.. MIT - flashtext (πŸ₯‰26 Β· ⭐ 5.6K Β· πŸ’€) - Extract Keywords from sentence or Replace keywords in sentences. MIT +- Snips NLU (πŸ₯‰26 Β· ⭐ 3.9K Β· πŸ’€) - Snips Python library to extract meaning from text. Apache-2 - MatchZoo (πŸ₯‰26 Β· ⭐ 3.8K Β· πŸ’€) - Facilitating the design, comparison and sharing of deep.. Apache-2 - polyglot (πŸ₯‰26 Β· ⭐ 2.3K Β· πŸ’€) - Multilingual text (NLP) processing toolkit. ❗️GPL-3.0 - PyText (πŸ₯‰25 Β· ⭐ 6.3K Β· πŸ’€) - A natural language modeling framework based on PyTorch. BSD-3 -- Snips NLU (πŸ₯‰25 Β· ⭐ 3.9K Β· πŸ’€) - Snips Python library to extract meaning from text. Apache-2 +- textgenrnn (πŸ₯‰25 Β· ⭐ 4.9K Β· πŸ’€) - Easily train your own text-generating neural network of any.. MIT - neuralcoref (πŸ₯‰25 Β· ⭐ 2.9K Β· πŸ’€) - Fast Coreference Resolution in spaCy with Neural Networks. MIT - Kashgari (πŸ₯‰25 Β· ⭐ 2.4K Β· πŸ’€) - Kashgari is a production-level NLP Transfer learning.. Apache-2 - pytorch-nlp (πŸ₯‰25 Β· ⭐ 2.2K Β· πŸ’€) - Basic Utilities for PyTorch Natural Language Processing.. 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· ⭐ 4.3K Β· πŸ’€) - An Open-Source Framework for Prompt-Learning. Apache-2 - sense2vec (πŸ₯‰24 Β· ⭐ 1.6K Β· πŸ’€) - Contextually-keyed word vectors. MIT -- whoosh (πŸ₯‰24 Β· ⭐ 570 Β· πŸ’€) - Pure-Python full-text search library. ❗️BSD-1-Clause +- whoosh (πŸ₯‰24 Β· ⭐ 580 Β· πŸ’€) - Pure-Python full-text search library. ❗️BSD-1-Clause - Texar (πŸ₯‰23 Β· ⭐ 2.4K Β· πŸ’€) - Toolkit for Machine Learning, Natural Language Processing, and.. Apache-2 - jiant (πŸ₯‰23 Β· ⭐ 1.6K Β· πŸ’€) - jiant is an nlp toolkit. MIT - YouTokenToMe (πŸ₯‰23 Β· ⭐ 950 Β· πŸ’€) - Unsupervised text tokenizer focused on computational efficiency. MIT - 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 +- anaGo (πŸ₯‰22 Β· ⭐ 1.5K Β· πŸ’€) - Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition,.. MIT - stop-words (πŸ₯‰22 Β· ⭐ 160 Β· πŸ’€) - Get list of common stop words in various languages in Python. BSD-3 -- anaGo (πŸ₯‰21 Β· ⭐ 1.5K Β· πŸ’€) - Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition,.. MIT -- numerizer (πŸ₯‰21 Β· ⭐ 210) - A Python module to convert natural language numerics into ints and.. MIT +- textpipe (πŸ₯‰21 Β· ⭐ 300 Β· πŸ’€) - Textpipe: clean and extract metadata from text. MIT +- numerizer (πŸ₯‰21 Β· ⭐ 220) - A Python module to convert natural language numerics into ints and.. 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 +- nboost (πŸ₯‰19 Β· ⭐ 680 Β· πŸ’€) - NBoost is a scalable, search-api-boosting platform for deploying.. Apache-2 - fastT5 (πŸ₯‰19 Β· ⭐ 560 Β· πŸ’€) - boost inference speed of T5 models by 5x & reduce the model size.. Apache-2 - Camphr (πŸ₯‰19 Β· ⭐ 340 Β· πŸ’€) - Camphr - NLP libary for creating pipeline components. Apache-2 spacy - NeuroNER (πŸ₯‰18 Β· ⭐ 1.7K Β· πŸ’€) - Named-entity recognition using neural networks. Easy-to-use and.. MIT -- nboost (πŸ₯‰18 Β· ⭐ 680 Β· πŸ’€) - NBoost is a scalable, search-api-boosting platform for deploying.. Apache-2 - skift (πŸ₯‰17 Β· ⭐ 240 Β· πŸ’€) - scikit-learn wrappers for Python fastText. 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 @@ -2196,7 +2170,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we - ONNX-T5 (πŸ₯‰15 Β· ⭐ 250 Β· πŸ’€) - Summarization, translation, sentiment-analysis, text-generation.. Apache-2 - NeuralQA (πŸ₯‰15 Β· ⭐ 230 Β· πŸ’€) - NeuralQA: A Usable Library for Question Answering on Large Datasets.. MIT - TransferNLP (πŸ₯‰14 Β· ⭐ 290 Β· πŸ’€) - NLP library designed for reproducible experimentation.. MIT -- textvec (πŸ₯‰13 Β· ⭐ 190 Β· πŸ’€) - Text vectorization tool to outperform TFIDF for classification.. MIT +- textvec (πŸ₯‰14 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

@@ -2209,60 +2183,60 @@ _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’» 480 Β· πŸ”€ 2.2K Β· πŸ“¦ 1.9M Β· πŸ“‹ 3.2K - 4% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/python-pillow/Pillow) (πŸ‘¨β€πŸ’» 480 Β· πŸ”€ 2.2K Β· πŸ“¦ 1.9M Β· πŸ“‹ 3.2K - 3% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/python-pillow/Pillow ``` -- [PyPi](https://pypi.org/project/Pillow) (πŸ“₯ 130M / month Β· πŸ“¦ 7.7K Β· ⏱️ 01.07.2024): +- [PyPi](https://pypi.org/project/Pillow) (πŸ“₯ 130M / month Β· πŸ“¦ 8.9K Β· ⏱️ 15.10.2024): ``` pip install Pillow ``` -- [Conda](https://anaconda.org/conda-forge/pillow) (πŸ“₯ 45M Β· ⏱️ 11.09.2024): +- [Conda](https://anaconda.org/conda-forge/pillow) (πŸ“₯ 45M Β· ⏱️ 18.10.2024): ``` conda install -c conda-forge pillow ```
PyTorch Image Models (πŸ₯‡42 Β· ⭐ 32K) - The largest collection of PyTorch image encoders /.. Apache-2 -- [GitHub](https://github.com/huggingface/pytorch-image-models) (πŸ‘¨β€πŸ’» 150 Β· πŸ”€ 4.7K Β· πŸ“₯ 7.1M Β· πŸ“¦ 38K Β· πŸ“‹ 920 - 5% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/huggingface/pytorch-image-models) (πŸ‘¨β€πŸ’» 150 Β· πŸ”€ 4.7K Β· πŸ“₯ 7.1M Β· πŸ“¦ 39K Β· πŸ“‹ 920 - 5% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/rwightman/pytorch-image-models ``` -- [PyPi](https://pypi.org/project/timm) (πŸ“₯ 6.1M / month Β· πŸ“¦ 930 Β· ⏱️ 23.08.2024): +- [PyPi](https://pypi.org/project/timm) (πŸ“₯ 6M / month Β· πŸ“¦ 950 Β· ⏱️ 16.10.2024): ``` pip install timm ``` -- [Conda](https://anaconda.org/conda-forge/timm) (πŸ“₯ 240K Β· ⏱️ 24.08.2024): +- [Conda](https://anaconda.org/conda-forge/timm) (πŸ“₯ 250K Β· ⏱️ 17.10.2024): ``` conda install -c conda-forge timm ```
torchvision (πŸ₯‡42 Β· ⭐ 16K) - Datasets, Transforms and Models specific to Computer Vision. BSD-3 -- [GitHub](https://github.com/pytorch/vision) (πŸ‘¨β€πŸ’» 610 Β· πŸ”€ 6.9K Β· πŸ“₯ 39K Β· πŸ“¦ 21 Β· πŸ“‹ 3.5K - 29% open Β· ⏱️ 03.10.2024): +- [GitHub](https://github.com/pytorch/vision) (πŸ‘¨β€πŸ’» 610 Β· πŸ”€ 6.9K Β· πŸ“₯ 39K Β· πŸ“¦ 21 Β· πŸ“‹ 3.5K - 29% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/pytorch/vision ``` -- [PyPi](https://pypi.org/project/torchvision) (πŸ“₯ 14M / month Β· πŸ“¦ 5.6K Β· ⏱️ 04.09.2024): +- [PyPi](https://pypi.org/project/torchvision) (πŸ“₯ 14M / month Β· πŸ“¦ 5.8K Β· ⏱️ 17.10.2024): ``` pip install torchvision ``` -- [Conda](https://anaconda.org/conda-forge/torchvision) (πŸ“₯ 1.7M Β· ⏱️ 07.10.2024): +- [Conda](https://anaconda.org/conda-forge/torchvision) (πŸ“₯ 1.7M Β· ⏱️ 14.10.2024): ``` conda install -c conda-forge torchvision ```
Albumentations (πŸ₯‡40 Β· ⭐ 14K) - Fast and flexible image augmentation library. Paper about.. MIT -- [GitHub](https://github.com/albumentations-team/albumentations) (πŸ‘¨β€πŸ’» 150 Β· πŸ”€ 1.6K Β· πŸ“¦ 28K Β· πŸ“‹ 1.1K - 31% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/albumentations-team/albumentations) (πŸ‘¨β€πŸ’» 150 Β· πŸ”€ 1.6K Β· πŸ“¦ 28K Β· πŸ“‹ 1K - 26% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/albumentations-team/albumentations ``` -- [PyPi](https://pypi.org/project/albumentations) (πŸ“₯ 4.6M / month Β· πŸ“¦ 580 Β· ⏱️ 08.10.2024): +- [PyPi](https://pypi.org/project/albumentations) (πŸ“₯ 4.6M / month Β· πŸ“¦ 600 Β· ⏱️ 23.10.2024): ``` pip install albumentations ``` @@ -2271,9 +2245,21 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge albumentations ```
+
deepface (πŸ₯‡39 Β· ⭐ 14K) - A Lightweight Face Recognition and Facial Attribute Analysis (Age,.. MIT + +- [GitHub](https://github.com/serengil/deepface) (πŸ‘¨β€πŸ’» 70 Β· πŸ”€ 2.1K Β· πŸ“¦ 4.3K Β· πŸ“‹ 1.1K - 0% open Β· ⏱️ 22.10.2024): + + ``` + git clone https://github.com/serengil/deepface + ``` +- [PyPi](https://pypi.org/project/deepface) (πŸ“₯ 160K / month Β· πŸ“¦ 44 Β· ⏱️ 17.08.2024): + ``` + pip install deepface + ``` +
MoviePy (πŸ₯‡38 Β· ⭐ 12K) - Video editing with Python. MIT -- [GitHub](https://github.com/Zulko/moviepy) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 1.6K Β· πŸ“¦ 46K Β· πŸ“‹ 1.5K - 31% open Β· ⏱️ 27.05.2024): +- [GitHub](https://github.com/Zulko/moviepy) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 1.6K Β· πŸ“¦ 47K Β· πŸ“‹ 1.5K - 31% open Β· ⏱️ 27.05.2024): ``` git clone https://github.com/Zulko/moviepy @@ -2287,26 +2273,14 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge moviepy ```
-
deepface (πŸ₯‡38 Β· ⭐ 12K) - A Lightweight Face Recognition and Facial Attribute Analysis (Age,.. MIT - -- [GitHub](https://github.com/serengil/deepface) (πŸ‘¨β€πŸ’» 67 Β· πŸ”€ 2K Β· πŸ“¦ 4.2K Β· πŸ“‹ 1.1K - 0% open Β· ⏱️ 10.10.2024): - - ``` - git clone https://github.com/serengil/deepface - ``` -- [PyPi](https://pypi.org/project/deepface) (πŸ“₯ 110K / month Β· πŸ“¦ 44 Β· ⏱️ 17.08.2024): - ``` - pip install deepface - ``` -
Kornia (πŸ₯‡38 Β· ⭐ 9.9K) - Geometric Computer Vision Library for Spatial AI. Apache-2 -- [GitHub](https://github.com/kornia/kornia) (πŸ‘¨β€πŸ’» 270 Β· πŸ”€ 960 Β· πŸ“₯ 1.5K Β· πŸ“¦ 12K Β· πŸ“‹ 950 - 30% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/kornia/kornia) (πŸ‘¨β€πŸ’» 270 Β· πŸ”€ 960 Β· πŸ“₯ 1.5K Β· πŸ“¦ 12K Β· πŸ“‹ 950 - 30% open Β· ⏱️ 21.10.2024): ``` git clone https://github.com/kornia/kornia ``` -- [PyPi](https://pypi.org/project/kornia) (πŸ“₯ 1.9M / month Β· πŸ“¦ 260 Β· ⏱️ 28.06.2024): +- [PyPi](https://pypi.org/project/kornia) (πŸ“₯ 2M / month Β· πŸ“¦ 260 Β· ⏱️ 28.06.2024): ``` pip install kornia ``` @@ -2317,59 +2291,59 @@ _Libraries for image & video processing, manipulation, and augmentation as well
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’» 120 Β· πŸ”€ 290 Β· πŸ“₯ 1.3K Β· πŸ“¦ 140K Β· πŸ“‹ 600 - 16% open Β· ⏱️ 19.08.2024): +- [GitHub](https://github.com/imageio/imageio) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 290 Β· πŸ“₯ 1.3K Β· πŸ“¦ 140K Β· πŸ“‹ 610 - 16% open Β· ⏱️ 14.10.2024): ``` git clone https://github.com/imageio/imageio ``` -- [PyPi](https://pypi.org/project/imageio) (πŸ“₯ 38M / month Β· πŸ“¦ 2.4K Β· ⏱️ 19.08.2024): +- [PyPi](https://pypi.org/project/imageio) (πŸ“₯ 36M / month Β· πŸ“¦ 2.4K Β· ⏱️ 14.10.2024): ``` pip install imageio ``` -- [Conda](https://anaconda.org/conda-forge/imageio) (πŸ“₯ 7M Β· ⏱️ 19.08.2024): +- [Conda](https://anaconda.org/conda-forge/imageio) (πŸ“₯ 7.1M Β· ⏱️ 17.10.2024): ``` conda install -c conda-forge imageio ```
MMDetection (πŸ₯ˆ37 Β· ⭐ 29K Β· πŸ’€) - OpenMMLab Detection Toolbox and Benchmark. Apache-2 -- [GitHub](https://github.com/open-mmlab/mmdetection) (πŸ‘¨β€πŸ’» 480 Β· πŸ”€ 9.4K Β· πŸ“¦ 3K Β· πŸ“‹ 8.5K - 20% open Β· ⏱️ 05.02.2024): +- [GitHub](https://github.com/open-mmlab/mmdetection) (πŸ‘¨β€πŸ’» 480 Β· πŸ”€ 9.4K Β· πŸ“¦ 3.1K Β· πŸ“‹ 8.5K - 21% open Β· ⏱️ 05.02.2024): ``` git clone https://github.com/open-mmlab/mmdetection ``` -- [PyPi](https://pypi.org/project/mmdet) (πŸ“₯ 180K / month Β· πŸ“¦ 82 Β· ⏱️ 05.01.2024): +- [PyPi](https://pypi.org/project/mmdet) (πŸ“₯ 190K / month Β· πŸ“¦ 82 Β· ⏱️ 05.01.2024): ``` pip install mmdet ```
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’» 61 Β· πŸ”€ 5.4K Β· πŸ“₯ 4.9M Β· πŸ“¦ 2.8K Β· πŸ“‹ 2.5K - 45% open Β· ⏱️ 30.09.2024): +- [GitHub](https://github.com/deepinsight/insightface) (πŸ‘¨β€πŸ’» 61 Β· πŸ”€ 5.4K Β· πŸ“₯ 5.1M Β· πŸ“¦ 2.8K Β· πŸ“‹ 2.5K - 45% open Β· ⏱️ 11.10.2024): ``` git clone https://github.com/deepinsight/insightface ``` -- [PyPi](https://pypi.org/project/insightface) (πŸ“₯ 280K / month Β· πŸ“¦ 30 Β· ⏱️ 17.12.2022): +- [PyPi](https://pypi.org/project/insightface) (πŸ“₯ 270K / month Β· πŸ“¦ 30 Β· ⏱️ 17.12.2022): ``` pip install insightface ```
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opencv-python (πŸ₯ˆ35 Β· ⭐ 4.5K) - Automated CI toolchain to produce precompiled opencv-python,.. MIT +
opencv-python (πŸ₯ˆ36 Β· ⭐ 4.5K) - Automated CI toolchain to produce precompiled opencv-python,.. MIT -- [GitHub](https://github.com/opencv/opencv-python) (πŸ‘¨β€πŸ’» 49 Β· πŸ”€ 830 Β· πŸ“¦ 450K Β· πŸ“‹ 810 - 15% open Β· ⏱️ 24.07.2024): +- [GitHub](https://github.com/opencv/opencv-python) (πŸ‘¨β€πŸ’» 49 Β· πŸ”€ 840 Β· πŸ“¦ 460K Β· πŸ“‹ 820 - 16% open Β· ⏱️ 24.07.2024): ``` git clone https://github.com/opencv/opencv-python ``` -- [PyPi](https://pypi.org/project/opencv-python) (πŸ“₯ 17M / month Β· πŸ“¦ 10K Β· ⏱️ 17.06.2024): +- [PyPi](https://pypi.org/project/opencv-python) (πŸ“₯ 16M / month Β· πŸ“¦ 10K Β· ⏱️ 17.06.2024): ``` pip install opencv-python ```
detectron2 (πŸ₯ˆ34 Β· ⭐ 30K) - Detectron2 is a platform for object detection, segmentation.. Apache-2 -- [GitHub](https://github.com/facebookresearch/detectron2) (πŸ‘¨β€πŸ’» 270 Β· πŸ”€ 7.4K Β· πŸ“¦ 2K Β· πŸ“‹ 3.6K - 14% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/facebookresearch/detectron2) (πŸ‘¨β€πŸ’» 270 Β· πŸ”€ 7.4K Β· πŸ“¦ 2.1K Β· πŸ“‹ 3.6K - 14% open Β· ⏱️ 14.10.2024): ``` git clone https://github.com/facebookresearch/detectron2 @@ -2378,30 +2352,30 @@ _Libraries for image & video processing, manipulation, and augmentation as well ``` pip install detectron2 ``` -- [Conda](https://anaconda.org/conda-forge/detectron2) (πŸ“₯ 430K Β· ⏱️ 26.08.2024): +- [Conda](https://anaconda.org/conda-forge/detectron2) (πŸ“₯ 450K Β· ⏱️ 26.08.2024): ``` conda install -c conda-forge detectron2 ```
Wand (πŸ₯ˆ34 Β· ⭐ 1.4K) - The ctypes-based simple ImageMagick binding for Python. MIT -- [GitHub](https://github.com/emcconville/wand) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 200 Β· πŸ“₯ 50K Β· πŸ“¦ 20K Β· πŸ“‹ 430 - 6% open Β· ⏱️ 01.10.2024): +- [GitHub](https://github.com/emcconville/wand) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 200 Β· πŸ“₯ 51K Β· πŸ“¦ 20K Β· πŸ“‹ 430 - 6% open Β· ⏱️ 01.10.2024): ``` git clone https://github.com/emcconville/wand ``` -- [PyPi](https://pypi.org/project/wand) (πŸ“₯ 950K / month Β· πŸ“¦ 260 Β· ⏱️ 03.11.2023): +- [PyPi](https://pypi.org/project/wand) (πŸ“₯ 960K / month Β· πŸ“¦ 260 Β· ⏱️ 03.11.2023): ``` pip install wand ``` -- [Conda](https://anaconda.org/conda-forge/wand) (πŸ“₯ 77K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/wand) (πŸ“₯ 80K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge wand ```
PaddleSeg (πŸ₯ˆ33 Β· ⭐ 8.6K) - Easy-to-use image segmentation library with awesome pre-.. Apache-2 -- [GitHub](https://github.com/PaddlePaddle/PaddleSeg) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 1.7K Β· πŸ“¦ 1.3K Β· πŸ“‹ 2.1K - 11% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/PaddlePaddle/PaddleSeg) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 1.7K Β· πŸ“¦ 1.3K Β· πŸ“‹ 2.1K - 11% open Β· ⏱️ 18.10.2024): ``` git clone https://github.com/PaddlePaddle/PaddleSeg @@ -2413,24 +2387,24 @@ _Libraries for image & video processing, manipulation, and augmentation as well
vit-pytorch (πŸ₯ˆ32 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”€ 3K Β· πŸ“¦ 530 Β· πŸ“‹ 280 - 48% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/lucidrains/vit-pytorch) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 3K Β· πŸ“¦ 540 Β· πŸ“‹ 280 - 48% open Β· ⏱️ 11.10.2024): ``` git clone https://github.com/lucidrains/vit-pytorch ``` -- [PyPi](https://pypi.org/project/vit-pytorch) (πŸ“₯ 22K / month Β· πŸ“¦ 13 Β· ⏱️ 09.10.2024): +- [PyPi](https://pypi.org/project/vit-pytorch) (πŸ“₯ 28K / month Β· πŸ“¦ 13 Β· ⏱️ 11.10.2024): ``` pip install vit-pytorch ```
lightly (πŸ₯ˆ32 Β· ⭐ 3.1K) - A python library for self-supervised learning on images. MIT -- [GitHub](https://github.com/lightly-ai/lightly) (πŸ‘¨β€πŸ’» 53 Β· πŸ”€ 270 Β· πŸ“¦ 320 Β· πŸ“‹ 570 - 12% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/lightly-ai/lightly) (πŸ‘¨β€πŸ’» 56 Β· πŸ”€ 280 Β· πŸ“¦ 320 Β· πŸ“‹ 580 - 12% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/lightly-ai/lightly ``` -- [PyPi](https://pypi.org/project/lightly) (πŸ“₯ 35K / month Β· πŸ“¦ 14 Β· ⏱️ 24.09.2024): +- [PyPi](https://pypi.org/project/lightly) (πŸ“₯ 34K / month Β· πŸ“¦ 14 Β· ⏱️ 24.09.2024): ``` pip install lightly ``` @@ -2442,23 +2416,23 @@ _Libraries for image & video processing, manipulation, and augmentation as well ``` git clone https://github.com/OlafenwaMoses/ImageAI ``` -- [PyPi](https://pypi.org/project/imageai) (πŸ“₯ 9.2K / month Β· πŸ“¦ 19 Β· ⏱️ 02.01.2023): +- [PyPi](https://pypi.org/project/imageai) (πŸ“₯ 10K / month Β· πŸ“¦ 19 Β· ⏱️ 02.01.2023): ``` pip install imageai ``` -- [Conda](https://anaconda.org/conda-forge/imageai) (πŸ“₯ 8K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/imageai) (πŸ“₯ 8.1K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge imageai ```
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ImageHash (πŸ₯ˆ31 Β· ⭐ 3.1K) - A Python Perceptual Image Hashing Module. BSD-2 +
ImageHash (πŸ₯ˆ31 Β· ⭐ 3.2K) - A Python Perceptual Image Hashing Module. BSD-2 -- [GitHub](https://github.com/JohannesBuchner/imagehash) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 330 Β· πŸ“¦ 14K Β· πŸ“‹ 140 - 13% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/JohannesBuchner/imagehash) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 330 Β· πŸ“¦ 15K Β· πŸ“‹ 140 - 13% open Β· ⏱️ 09.10.2024): ``` git clone https://github.com/JohannesBuchner/imagehash ``` -- [PyPi](https://pypi.org/project/ImageHash) (πŸ“₯ 1.5M / month Β· πŸ“¦ 240 Β· ⏱️ 28.09.2022): +- [PyPi](https://pypi.org/project/ImageHash) (πŸ“₯ 1.6M / month Β· πŸ“¦ 240 Β· ⏱️ 28.09.2022): ``` pip install ImageHash ``` @@ -2467,26 +2441,26 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge imagehash ```
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CellProfiler (πŸ₯ˆ30 Β· ⭐ 900) - An open-source application for biological image analysis. BSD-3 +
CellProfiler (πŸ₯ˆ30 Β· ⭐ 910) - An open-source application for biological image analysis. BSD-3 -- [GitHub](https://github.com/CellProfiler/CellProfiler) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 380 Β· πŸ“₯ 7.8K Β· πŸ“¦ 23 Β· πŸ“‹ 3.3K - 9% open Β· ⏱️ 24.09.2024): +- [GitHub](https://github.com/CellProfiler/CellProfiler) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 380 Β· πŸ“₯ 7.9K Β· πŸ“¦ 24 Β· πŸ“‹ 3.3K - 9% open Β· ⏱️ 24.09.2024): ``` git clone https://github.com/CellProfiler/CellProfiler ``` -- [PyPi](https://pypi.org/project/cellprofiler) (πŸ“₯ 2.2K / month Β· πŸ“¦ 2 Β· ⏱️ 16.09.2024): +- [PyPi](https://pypi.org/project/cellprofiler) (πŸ“₯ 3.5K / month Β· πŸ“¦ 2 Β· ⏱️ 16.09.2024): ``` pip install cellprofiler ```
PaddleDetection (πŸ₯ˆ29 Β· ⭐ 13K) - Object Detection toolkit based on PaddlePaddle. It.. Apache-2 -- [GitHub](https://github.com/PaddlePaddle/PaddleDetection) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 2.8K Β· πŸ“‹ 5.4K - 22% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/PaddlePaddle/PaddleDetection) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 2.9K Β· πŸ“‹ 5.4K - 22% open Β· ⏱️ 18.10.2024): ``` git clone https://github.com/PaddlePaddle/PaddleDetection ``` -- [PyPi](https://pypi.org/project/paddledet) (πŸ“₯ 550 / month Β· πŸ“¦ 2 Β· ⏱️ 19.09.2022): +- [PyPi](https://pypi.org/project/paddledet) (πŸ“₯ 740 / month Β· πŸ“¦ 2 Β· ⏱️ 19.09.2022): ``` pip install paddledet ``` @@ -2498,47 +2472,47 @@ _Libraries for image & video processing, manipulation, and augmentation as well ``` git clone https://github.com/obss/sahi ``` -- [PyPi](https://pypi.org/project/sahi) (πŸ“₯ 180K / month Β· πŸ“¦ 26 Β· ⏱️ 10.07.2024): +- [PyPi](https://pypi.org/project/sahi) (πŸ“₯ 140K / month Β· πŸ“¦ 26 Β· ⏱️ 10.07.2024): ``` pip install sahi ``` -- [Conda](https://anaconda.org/conda-forge/sahi) (πŸ“₯ 74K Β· ⏱️ 24.07.2024): +- [Conda](https://anaconda.org/conda-forge/sahi) (πŸ“₯ 76K Β· ⏱️ 24.07.2024): ``` conda install -c conda-forge sahi ```
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doctr (πŸ₯ˆ29 Β· ⭐ 3.7K) - docTR (Document Text Recognition) - a seamless, high-.. Apache-2 +
doctr (πŸ₯ˆ29 Β· ⭐ 3.8K) - docTR (Document Text Recognition) - a seamless, high-.. Apache-2 -- [GitHub](https://github.com/mindee/doctr) (πŸ‘¨β€πŸ’» 51 Β· πŸ”€ 420 Β· πŸ“₯ 3.9M Β· πŸ“‹ 370 - 10% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/mindee/doctr) (πŸ‘¨β€πŸ’» 52 Β· πŸ”€ 430 Β· πŸ“₯ 4M Β· πŸ“‹ 370 - 7% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/mindee/doctr ``` -- [PyPi](https://pypi.org/project/python-doctr) (πŸ“₯ 52K / month Β· πŸ“¦ 12 Β· ⏱️ 08.08.2024): +- [PyPi](https://pypi.org/project/python-doctr) (πŸ“₯ 50K / month Β· πŸ“¦ 12 Β· ⏱️ 21.10.2024): ``` pip install python-doctr ```
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vidgear (πŸ₯ˆ29 Β· ⭐ 3.3K) - A High-performance cross-platform Video Processing Python framework.. Apache-2 +
vidgear (πŸ₯ˆ29 Β· ⭐ 3.4K) - A High-performance cross-platform Video Processing Python framework.. Apache-2 -- [GitHub](https://github.com/abhiTronix/vidgear) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 250 Β· πŸ“₯ 1.7K Β· πŸ“¦ 610 Β· πŸ“‹ 300 - 2% open Β· ⏱️ 22.06.2024): +- [GitHub](https://github.com/abhiTronix/vidgear) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 250 Β· πŸ“₯ 1.8K Β· πŸ“¦ 620 Β· πŸ“‹ 300 - 2% open Β· ⏱️ 22.06.2024): ``` git clone https://github.com/abhiTronix/vidgear ``` -- [PyPi](https://pypi.org/project/vidgear) (πŸ“₯ 26K / month Β· πŸ“¦ 15 Β· ⏱️ 22.06.2024): +- [PyPi](https://pypi.org/project/vidgear) (πŸ“₯ 24K / month Β· πŸ“¦ 15 Β· ⏱️ 22.06.2024): ``` pip install vidgear ```
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mtcnn (πŸ₯ˆ29 Β· ⭐ 2.2K Β· πŸ“ˆ) - MTCNN face detection implementation for TensorFlow, as a PIP.. MIT +
mtcnn (πŸ₯ˆ29 Β· ⭐ 2.2K) - MTCNN face detection implementation for TensorFlow, as a PIP package. MIT -- [GitHub](https://github.com/ipazc/mtcnn) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 530 Β· πŸ“¦ 6.2K Β· πŸ“‹ 130 - 37% open Β· ⏱️ 08.10.2024): +- [GitHub](https://github.com/ipazc/mtcnn) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 530 Β· πŸ“₯ 4 Β· πŸ“¦ 6.3K Β· πŸ“‹ 130 - 37% open Β· ⏱️ 08.10.2024): ``` git clone https://github.com/ipazc/mtcnn ``` -- [PyPi](https://pypi.org/project/mtcnn) (πŸ“₯ 110K / month Β· πŸ“¦ 73 Β· ⏱️ 08.10.2024): +- [PyPi](https://pypi.org/project/mtcnn) (πŸ“₯ 120K / month Β· πŸ“¦ 73 Β· ⏱️ 08.10.2024): ``` pip install mtcnn ``` @@ -2547,14 +2521,14 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge mtcnn ```
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Face Alignment (πŸ₯‰28 Β· ⭐ 7K) - 2D and 3D Face alignment library build using pytorch. BSD-3 +
Face Alignment (πŸ₯‰28 Β· ⭐ 7.1K) - 2D and 3D Face alignment library build using pytorch. BSD-3 - [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/1adrianb/face-alignment ``` -- [PyPi](https://pypi.org/project/face-alignment) (πŸ“₯ 64K / month Β· πŸ“¦ 10 Β· ⏱️ 17.08.2023): +- [PyPi](https://pypi.org/project/face-alignment) (πŸ“₯ 60K / month Β· πŸ“¦ 10 Β· ⏱️ 17.08.2023): ``` pip install face-alignment ``` @@ -2566,43 +2540,55 @@ _Libraries for image & video processing, manipulation, and augmentation as well ``` git clone https://github.com/luispedro/mahotas ``` -- [PyPi](https://pypi.org/project/mahotas) (πŸ“₯ 27K / month Β· πŸ“¦ 63 Β· ⏱️ 17.07.2024): +- [PyPi](https://pypi.org/project/mahotas) (πŸ“₯ 30K / month Β· πŸ“¦ 63 Β· ⏱️ 17.07.2024): ``` pip install mahotas ``` -- [Conda](https://anaconda.org/conda-forge/mahotas) (πŸ“₯ 500K Β· ⏱️ 18.07.2024): +- [Conda](https://anaconda.org/conda-forge/mahotas) (πŸ“₯ 510K Β· ⏱️ 18.07.2024): ``` conda install -c conda-forge mahotas ```
facenet-pytorch (πŸ₯‰27 Β· ⭐ 4.5K) - Pretrained Pytorch face detection (MTCNN) and facial.. MIT -- [GitHub](https://github.com/timesler/facenet-pytorch) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 940 Β· πŸ“₯ 1.3M Β· πŸ“¦ 2.3K Β· πŸ“‹ 180 - 41% open Β· ⏱️ 02.08.2024): +- [GitHub](https://github.com/timesler/facenet-pytorch) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 940 Β· πŸ“₯ 1.4M Β· πŸ“¦ 2.3K Β· πŸ“‹ 180 - 41% open Β· ⏱️ 02.08.2024): ``` git clone https://github.com/timesler/facenet-pytorch ``` -- [PyPi](https://pypi.org/project/facenet-pytorch) (πŸ“₯ 70K / month Β· πŸ“¦ 51 Β· ⏱️ 29.04.2024): +- [PyPi](https://pypi.org/project/facenet-pytorch) (πŸ“₯ 73K / month Β· πŸ“¦ 51 Β· ⏱️ 29.04.2024): ``` pip install facenet-pytorch ```
pyvips (πŸ₯‰26 Β· ⭐ 640) - python binding for libvips using cffi. MIT -- [GitHub](https://github.com/libvips/pyvips) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 49 Β· πŸ“¦ 810 Β· πŸ“‹ 440 - 42% open Β· ⏱️ 21.09.2024): +- [GitHub](https://github.com/libvips/pyvips) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 49 Β· πŸ“¦ 820 Β· πŸ“‹ 450 - 42% open Β· ⏱️ 12.10.2024): ``` git clone https://github.com/libvips/pyvips ``` -- [PyPi](https://pypi.org/project/pyvips) (πŸ“₯ 73K / month Β· πŸ“¦ 77 Β· ⏱️ 28.04.2024): +- [PyPi](https://pypi.org/project/pyvips) (πŸ“₯ 70K / month Β· πŸ“¦ 77 Β· ⏱️ 28.04.2024): ``` pip install pyvips ``` -- [Conda](https://anaconda.org/conda-forge/pyvips) (πŸ“₯ 130K Β· ⏱️ 06.09.2024): +- [Conda](https://anaconda.org/conda-forge/pyvips) (πŸ“₯ 140K Β· ⏱️ 06.09.2024): ``` conda install -c conda-forge pyvips ```
+
MMF (πŸ₯‰25 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“¦ 21 Β· πŸ“‹ 690 - 21% open Β· ⏱️ 25.05.2024): + + ``` + git clone https://github.com/facebookresearch/mmf + ``` +- [PyPi](https://pypi.org/project/mmf) (πŸ“₯ 2.1K / month Β· πŸ“¦ 1 Β· ⏱️ 12.06.2020): + ``` + pip install mmf + ``` +
pytorchvideo (πŸ₯‰25 Β· ⭐ 3.3K) - A deep learning library for video understanding research. Apache-2 - [GitHub](https://github.com/facebookresearch/pytorchvideo) (πŸ‘¨β€πŸ’» 56 Β· πŸ”€ 410 Β· πŸ“‹ 210 - 50% open Β· ⏱️ 13.08.2024): @@ -2615,28 +2601,28 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install pytorchvideo ```
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Norfair (πŸ₯‰25 Β· ⭐ 2.4K) - Lightweight Python library for adding real-time multi-object tracking.. BSD-3 +
ffcv (πŸ₯‰25 Β· ⭐ 2.9K) - FFCV: Fast Forward Computer Vision (and other ML workloads!). Apache-2 -- [GitHub](https://github.com/tryolabs/norfair) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 240 Β· πŸ“₯ 330 Β· πŸ“¦ 230 Β· πŸ“‹ 170 - 14% open Β· ⏱️ 27.07.2024): +- [GitHub](https://github.com/libffcv/ffcv) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 180 Β· πŸ“¦ 54 Β· πŸ“‹ 290 - 38% open Β· ⏱️ 06.05.2024): ``` - git clone https://github.com/tryolabs/norfair + git clone https://github.com/libffcv/ffcv ``` -- [PyPi](https://pypi.org/project/norfair) (πŸ“₯ 23K / month Β· πŸ“¦ 9 Β· ⏱️ 30.05.2022): +- [PyPi](https://pypi.org/project/ffcv) (πŸ“₯ 1.1K / month Β· πŸ“¦ 1 Β· ⏱️ 28.01.2022): ``` - pip install norfair + pip install ffcv ```
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MMF (πŸ₯‰24 Β· ⭐ 5.5K) - A modular framework for vision & language multimodal research from.. BSD-3 +
Norfair (πŸ₯‰25 Β· ⭐ 2.4K) - Lightweight Python library for adding real-time multi-object tracking.. BSD-3 -- [GitHub](https://github.com/facebookresearch/mmf) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 920 Β· πŸ“¦ 21 Β· πŸ“‹ 690 - 21% open Β· ⏱️ 25.05.2024): +- [GitHub](https://github.com/tryolabs/norfair) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 240 Β· πŸ“₯ 340 Β· πŸ“¦ 230 Β· πŸ“‹ 170 - 14% open Β· ⏱️ 27.07.2024): ``` - git clone https://github.com/facebookresearch/mmf + git clone https://github.com/tryolabs/norfair ``` -- [PyPi](https://pypi.org/project/mmf) (πŸ“₯ 1.1K / month Β· πŸ“¦ 1 Β· ⏱️ 12.06.2020): +- [PyPi](https://pypi.org/project/norfair) (πŸ“₯ 24K / month Β· πŸ“¦ 9 Β· ⏱️ 30.05.2022): ``` - pip install mmf + pip install norfair ```
segmentation_models (πŸ₯‰24 Β· ⭐ 4.7K) - Segmentation models with pretrained backbones. Keras.. MIT @@ -2646,23 +2632,11 @@ _Libraries for image & video processing, manipulation, and augmentation as well ``` git clone https://github.com/qubvel/segmentation_models ``` -- [PyPi](https://pypi.org/project/segmentation_models) (πŸ“₯ 27K / month Β· πŸ“¦ 28 Β· ⏱️ 10.01.2020): +- [PyPi](https://pypi.org/project/segmentation_models) (πŸ“₯ 28K / month Β· πŸ“¦ 28 Β· ⏱️ 10.01.2020): ``` pip install segmentation_models ```
-
ffcv (πŸ₯‰24 Β· ⭐ 2.8K) - FFCV: Fast Forward Computer Vision (and other ML workloads!). Apache-2 - -- [GitHub](https://github.com/libffcv/ffcv) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 170 Β· πŸ“¦ 54 Β· πŸ“‹ 280 - 36% open Β· ⏱️ 06.05.2024): - - ``` - git clone https://github.com/libffcv/ffcv - ``` -- [PyPi](https://pypi.org/project/ffcv) (πŸ“₯ 1K / month Β· πŸ“¦ 1 Β· ⏱️ 28.01.2022): - ``` - pip install ffcv - ``` -
tensorflow-graphics (πŸ₯‰24 Β· ⭐ 2.7K) - TensorFlow Graphics: Differentiable Graphics Layers.. Apache-2 - [GitHub](https://github.com/tensorflow/graphics) (πŸ‘¨β€πŸ’» 39 Β· πŸ”€ 360 Β· πŸ“‹ 240 - 60% open Β· ⏱️ 01.08.2024): @@ -2670,36 +2644,36 @@ _Libraries for image & video processing, manipulation, and augmentation as well ``` git clone https://github.com/tensorflow/graphics ``` -- [PyPi](https://pypi.org/project/tensorflow-graphics) (πŸ“₯ 17K / month Β· πŸ“¦ 11 Β· ⏱️ 03.12.2021): +- [PyPi](https://pypi.org/project/tensorflow-graphics) (πŸ“₯ 57K / month Β· πŸ“¦ 11 Β· ⏱️ 03.12.2021): ``` pip install tensorflow-graphics ```
-
vissl (πŸ₯‰23 Β· ⭐ 3.3K Β· πŸ’€) - VISSL is FAIRs library of extensible, modular and scalable.. MIT +
kubric (πŸ₯‰24 Β· ⭐ 2.3K) - A data generation pipeline for creating semi-realistic synthetic.. Apache-2 -- [GitHub](https://github.com/facebookresearch/vissl) (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 330 Β· πŸ“¦ 53 Β· πŸ“‹ 190 - 43% open Β· ⏱️ 03.03.2024): +- [GitHub](https://github.com/google-research/kubric) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 220 Β· πŸ“¦ 7 Β· πŸ“‹ 190 - 33% open Β· ⏱️ 07.10.2024): ``` - git clone https://github.com/facebookresearch/vissl + git clone https://github.com/google-research/kubric ``` -- [PyPi](https://pypi.org/project/vissl) (πŸ“₯ 200 / month Β· πŸ“¦ 1 Β· ⏱️ 02.11.2021): +- [PyPi](https://pypi.org/project/kubric-nightly) (πŸ“₯ 68K / month Β· ⏱️ 27.12.2023): ``` - pip install vissl + pip install kubric-nightly ```
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kubric (πŸ₯‰23 Β· ⭐ 2.3K) - A data generation pipeline for creating semi-realistic synthetic.. Apache-2 +
vissl (πŸ₯‰23 Β· ⭐ 3.3K Β· πŸ’€) - VISSL is FAIRs library of extensible, modular and scalable.. MIT -- [GitHub](https://github.com/google-research/kubric) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 220 Β· πŸ“¦ 7 Β· πŸ“‹ 190 - 33% open Β· ⏱️ 07.10.2024): +- [GitHub](https://github.com/facebookresearch/vissl) (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 330 Β· πŸ“¦ 53 Β· πŸ“‹ 190 - 43% open Β· ⏱️ 03.03.2024): ``` - git clone https://github.com/google-research/kubric + git clone https://github.com/facebookresearch/vissl ``` -- [PyPi](https://pypi.org/project/kubric-nightly) (πŸ“₯ 39K / month Β· ⏱️ 27.12.2023): +- [PyPi](https://pypi.org/project/vissl) (πŸ“₯ 240 / month Β· πŸ“¦ 1 Β· ⏱️ 02.11.2021): ``` - pip install kubric-nightly + pip install vissl ```
-
DEβ«ΆTR (πŸ₯‰21 Β· ⭐ 13K Β· πŸ’€) - End-to-End Object Detection with Transformers. Apache-2 +
DEβ«ΆTR (πŸ₯‰21 Β· ⭐ 14K Β· πŸ’€) - 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): @@ -2709,19 +2683,19 @@ _Libraries for image & video processing, manipulation, and augmentation as well
PySlowFast (πŸ₯‰21 Β· ⭐ 6.6K) - PySlowFast: video understanding codebase from FAIR for.. Apache-2 -- [GitHub](https://github.com/facebookresearch/SlowFast) (πŸ‘¨β€πŸ’» 33 Β· πŸ”€ 1.2K Β· πŸ“¦ 20 Β· πŸ“‹ 680 - 57% open Β· ⏱️ 13.08.2024): +- [GitHub](https://github.com/facebookresearch/SlowFast) (πŸ‘¨β€πŸ’» 33 Β· πŸ”€ 1.2K Β· πŸ“¦ 20 Β· πŸ“‹ 700 - 58% open Β· ⏱️ 13.08.2024): ``` git clone https://github.com/facebookresearch/SlowFast ``` -- [PyPi](https://pypi.org/project/pyslowfast) (πŸ“₯ 60 / month Β· ⏱️ 15.01.2020): +- [PyPi](https://pypi.org/project/pyslowfast) (πŸ“₯ 110 / month Β· ⏱️ 15.01.2020): ``` pip install pyslowfast ```
scenic (πŸ₯‰18 Β· ⭐ 3.3K) - Scenic: A Jax Library for Computer Vision Research and Beyond. Apache-2 -- [GitHub](https://github.com/google-research/scenic) (πŸ‘¨β€πŸ’» 85 Β· πŸ”€ 420 Β· πŸ“‹ 270 - 55% open Β· ⏱️ 08.10.2024): +- [GitHub](https://github.com/google-research/scenic) (πŸ‘¨β€πŸ’» 88 Β· πŸ”€ 430 Β· πŸ“‹ 270 - 55% open Β· ⏱️ 19.10.2024): ``` git clone https://github.com/google-research/scenic @@ -2736,7 +2710,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well - PyTorch3D (πŸ₯ˆ33 Β· ⭐ 8.7K) - 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 -- layout-parser (πŸ₯‰28 Β· ⭐ 4.8K Β· πŸ’€) - A Unified Toolkit for Deep Learning Based Document Image.. Apache-2 +- layout-parser (πŸ₯‰28 Β· ⭐ 4.9K Β· πŸ’€) - A Unified Toolkit for Deep Learning Based Document Image.. Apache-2 - Pillow-SIMD (πŸ₯‰27 Β· ⭐ 2.2K) - 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· ⭐ 5.1K Β· πŸ’€) - Image augmentation library in Python for machine learning. MIT @@ -2746,13 +2720,13 @@ _Libraries for image & video processing, manipulation, and augmentation as well - Classy Vision (πŸ₯‰22 Β· ⭐ 1.6K Β· πŸ’€) - An end-to-end PyTorch framework for image and video.. MIT - icevision (πŸ₯‰22 Β· ⭐ 850 Β· πŸ’€) - An Agnostic Computer Vision Framework - Pluggable to any.. Apache-2 - Image Super-Resolution (πŸ₯‰21 Β· ⭐ 4.6K Β· πŸ’€) - Super-scale your images and run experiments with.. Apache-2 -- image-match (πŸ₯‰20 Β· ⭐ 2.9K Β· πŸ’€) - Quickly search over billions of images. Apache-2 +- image-match (πŸ₯‰21 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 +- nude.py (πŸ₯‰20 Β· ⭐ 930 Β· πŸ’€) - Nudity detection with Python. MIT - detecto (πŸ₯‰20 Β· ⭐ 610 Β· πŸ’€) - Build fully-functioning computer vision models with PyTorch. MIT - Caer (πŸ₯‰18 Β· ⭐ 770 Β· πŸ’€) - A lightweight Computer Vision library. Scale your models, not boilerplate. MIT - solt (πŸ₯‰18 Β· ⭐ 260) - Streaming over lightweight data transformations. MIT -- Torch Points 3D (πŸ₯‰17 Β· ⭐ 210 Β· πŸ’€) - Pytorch framework for doing deep learning on point.. BSD-3 +- Torch Points 3D (πŸ₯‰17 Β· ⭐ 220 Β· πŸ’€) - Pytorch framework for doing deep learning on point.. BSD-3 - HugsVision (πŸ₯‰16 Β· ⭐ 190 Β· πŸ’€) - HugsVision is a easy to use huggingface wrapper for state-of-.. MIT huggingface

@@ -2763,70 +2737,70 @@ _Libraries for image & video processing, manipulation, and augmentation as well _Libraries for graph processing, clustering, embedding, and machine learning tasks._ -
networkx (πŸ₯‡43 Β· ⭐ 15K) - 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’» 750 Β· πŸ”€ 3.2K Β· πŸ“₯ 76 Β· πŸ“¦ 300K Β· πŸ“‹ 3.4K - 10% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/networkx/networkx) (πŸ‘¨β€πŸ’» 750 Β· πŸ”€ 3.2K Β· πŸ“₯ 76 Β· πŸ“¦ 310K Β· πŸ“‹ 3.4K - 10% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/networkx/networkx ``` -- [PyPi](https://pypi.org/project/networkx) (πŸ“₯ 81M / month Β· πŸ“¦ 9.5K Β· ⏱️ 06.10.2024): +- [PyPi](https://pypi.org/project/networkx) (πŸ“₯ 81M / month Β· πŸ“¦ 9.6K Β· ⏱️ 21.10.2024): ``` pip install networkx ``` -- [Conda](https://anaconda.org/conda-forge/networkx) (πŸ“₯ 18M Β· ⏱️ 08.04.2024): +- [Conda](https://anaconda.org/conda-forge/networkx) (πŸ“₯ 18M Β· ⏱️ 21.10.2024): ``` conda install -c conda-forge networkx ```
PyTorch Geometric (πŸ₯‡40 Β· ⭐ 21K) - Graph Neural Network Library for PyTorch. MIT -- [GitHub](https://github.com/pyg-team/pytorch_geometric) (πŸ‘¨β€πŸ’» 520 Β· πŸ”€ 3.6K Β· πŸ“¦ 6.6K Β· πŸ“‹ 3.7K - 27% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/pyg-team/pytorch_geometric) (πŸ‘¨β€πŸ’» 520 Β· πŸ”€ 3.6K Β· πŸ“¦ 6.7K Β· πŸ“‹ 3.7K - 28% open Β· ⏱️ 21.10.2024): ``` git clone https://github.com/pyg-team/pytorch_geometric ``` -- [PyPi](https://pypi.org/project/torch-geometric) (πŸ“₯ 410K / month Β· πŸ“¦ 360 Β· ⏱️ 26.09.2024): +- [PyPi](https://pypi.org/project/torch-geometric) (πŸ“₯ 390K / month Β· πŸ“¦ 360 Β· ⏱️ 26.09.2024): ``` pip install torch-geometric ``` -- [Conda](https://anaconda.org/conda-forge/pytorch_geometric) (πŸ“₯ 94K Β· ⏱️ 26.09.2024): +- [Conda](https://anaconda.org/conda-forge/pytorch_geometric) (πŸ“₯ 98K Β· ⏱️ 26.09.2024): ``` conda install -c conda-forge pytorch_geometric ```
-
dgl (πŸ₯‡39 Β· ⭐ 13K) - Python package built to ease deep learning on graph, on top of existing DL.. Apache-2 +
dgl (πŸ₯‡38 Β· ⭐ 13K Β· πŸ“‰) - Python package built to ease deep learning on graph, on top of.. Apache-2 -- [GitHub](https://github.com/dmlc/dgl) (πŸ‘¨β€πŸ’» 300 Β· πŸ”€ 3K Β· πŸ“¦ 310 Β· πŸ“‹ 2.9K - 18% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/dmlc/dgl) (πŸ‘¨β€πŸ’» 300 Β· πŸ”€ 3K Β· πŸ“¦ 310 Β· πŸ“‹ 2.9K - 18% open Β· ⏱️ 18.10.2024): ``` git clone https://github.com/dmlc/dgl ``` -- [PyPi](https://pypi.org/project/dgl) (πŸ“₯ 130K / month Β· πŸ“¦ 150 Β· ⏱️ 13.05.2024): +- [PyPi](https://pypi.org/project/dgl) (πŸ“₯ 170K / month Β· πŸ“¦ 150 Β· ⏱️ 13.05.2024): ``` pip install dgl ```
-
pygraphistry (πŸ₯ˆ32 Β· ⭐ 2.1K Β· πŸ“ˆ) - PyGraphistry is a Python library to quickly load,.. BSD-3 +
pygraphistry (πŸ₯ˆ32 Β· ⭐ 2.1K) - PyGraphistry is a Python library to quickly load, shape,.. BSD-3 -- [GitHub](https://github.com/graphistry/pygraphistry) (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 200 Β· πŸ“¦ 120 Β· πŸ“‹ 340 - 51% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/graphistry/pygraphistry) (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 200 Β· πŸ“¦ 120 Β· πŸ“‹ 340 - 51% open Β· ⏱️ 20.10.2024): ``` git clone https://github.com/graphistry/pygraphistry ``` -- [PyPi](https://pypi.org/project/graphistry) (πŸ“₯ 9.9K / month Β· πŸ“¦ 6 Β· ⏱️ 10.10.2024): +- [PyPi](https://pypi.org/project/graphistry) (πŸ“₯ 16K / month Β· πŸ“¦ 6 Β· ⏱️ 20.10.2024): ``` pip install graphistry ```
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PyKEEN (πŸ₯ˆ30 Β· ⭐ 1.6K) - A Python library for learning and evaluating knowledge graph embeddings. MIT +
PyKEEN (πŸ₯ˆ31 Β· ⭐ 1.6K) - A Python library for learning and evaluating knowledge graph embeddings. MIT -- [GitHub](https://github.com/pykeen/pykeen) (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 180 Β· πŸ“₯ 210 Β· πŸ“¦ 240 Β· πŸ“‹ 580 - 20% open Β· ⏱️ 07.10.2024): +- [GitHub](https://github.com/pykeen/pykeen) (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 180 Β· πŸ“₯ 210 Β· πŸ“¦ 250 Β· πŸ“‹ 580 - 20% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/pykeen/pykeen ``` -- [PyPi](https://pypi.org/project/pykeen) (πŸ“₯ 9.8K / month Β· πŸ“¦ 6 Β· ⏱️ 19.02.2024): +- [PyPi](https://pypi.org/project/pykeen) (πŸ“₯ 11K / month Β· πŸ“¦ 6 Β· ⏱️ 19.02.2024): ``` pip install pykeen ``` @@ -2838,18 +2812,18 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas ``` git clone https://github.com/snap-stanford/ogb ``` -- [PyPi](https://pypi.org/project/ogb) (πŸ“₯ 81K / month Β· πŸ“¦ 22 Β· ⏱️ 02.11.2022): +- [PyPi](https://pypi.org/project/ogb) (πŸ“₯ 68K / month Β· πŸ“¦ 22 Β· ⏱️ 02.11.2022): ``` pip install ogb ``` -- [Conda](https://anaconda.org/conda-forge/ogb) (πŸ“₯ 38K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/ogb) (πŸ“₯ 39K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge ogb ```
Spektral (πŸ₯ˆ28 Β· ⭐ 2.4K Β· πŸ’€) - Graph Neural Networks with Keras and Tensorflow 2. MIT -- [GitHub](https://github.com/danielegrattarola/spektral) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 340 Β· πŸ“¦ 330 Β· πŸ“‹ 280 - 24% open Β· ⏱️ 21.01.2024): +- [GitHub](https://github.com/danielegrattarola/spektral) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 340 Β· πŸ“¦ 340 Β· πŸ“‹ 280 - 24% open Β· ⏱️ 21.01.2024): ``` git clone https://github.com/danielegrattarola/spektral @@ -2866,51 +2840,63 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas ``` git clone https://github.com/Accenture/AmpliGraph ``` -- [PyPi](https://pypi.org/project/ampligraph) (πŸ“₯ 1.5K / month Β· πŸ“¦ 2 Β· ⏱️ 26.02.2024): +- [PyPi](https://pypi.org/project/ampligraph) (πŸ“₯ 2.9K / month Β· πŸ“¦ 2 Β· ⏱️ 26.02.2024): ``` pip install ampligraph ```
-
Node2Vec (πŸ₯ˆ25 Β· ⭐ 1.2K) - Implementation of the node2vec algorithm. MIT +
pytorch_geometric_temporal (πŸ₯ˆ25 Β· ⭐ 2.6K) - PyTorch Geometric Temporal: Spatiotemporal Signal.. MIT -- [GitHub](https://github.com/eliorc/node2vec) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 240 Β· πŸ“¦ 690 Β· πŸ“‹ 93 - 5% open Β· ⏱️ 02.08.2024): +- [GitHub](https://github.com/benedekrozemberczki/pytorch_geometric_temporal) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 370 Β· πŸ“‹ 200 - 20% open Β· ⏱️ 14.10.2024): ``` - git clone https://github.com/eliorc/node2vec - ``` -- [PyPi](https://pypi.org/project/node2vec) (πŸ“₯ 17K / month Β· πŸ“¦ 31 Β· ⏱️ 02.08.2024): - ``` - pip install node2vec + git clone https://github.com/benedekrozemberczki/pytorch_geometric_temporal ``` -- [Conda](https://anaconda.org/conda-forge/node2vec) (πŸ“₯ 31K Β· ⏱️ 16.06.2023): +- [PyPi](https://pypi.org/project/torch-geometric-temporal) (πŸ“₯ 3.1K / month Β· πŸ“¦ 7 Β· ⏱️ 04.09.2022): ``` - conda install -c conda-forge node2vec + pip install torch-geometric-temporal ```
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PyTorch-BigGraph (πŸ₯ˆ23 Β· ⭐ 3.4K Β· πŸ’€) - Generate embeddings from large-scale graph-structured.. BSD-3 +
PyTorch-BigGraph (πŸ₯ˆ24 Β· ⭐ 3.4K Β· πŸ’€) - 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“₯ 210 Β· πŸ“‹ 200 - 32% open Β· ⏱️ 03.03.2024): ``` git clone https://github.com/facebookresearch/PyTorch-BigGraph ``` -- [PyPi](https://pypi.org/project/torchbiggraph) (πŸ“₯ 430K / month Β· πŸ“¦ 2 Β· ⏱️ 14.10.2019): +- [PyPi](https://pypi.org/project/torchbiggraph) (πŸ“₯ 450K / month Β· πŸ“¦ 2 Β· ⏱️ 14.10.2019): ``` pip install torchbiggraph ```
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Node2Vec (πŸ₯ˆ24 Β· ⭐ 1.2K) - Implementation of the node2vec algorithm. MIT + +- [GitHub](https://github.com/eliorc/node2vec) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 240 Β· πŸ“¦ 710 Β· πŸ“‹ 93 - 5% open Β· ⏱️ 02.08.2024): + + ``` + git clone https://github.com/eliorc/node2vec + ``` +- [PyPi](https://pypi.org/project/node2vec) (πŸ“₯ 18K / month Β· πŸ“¦ 31 Β· ⏱️ 02.08.2024): + ``` + pip install node2vec + ``` +- [Conda](https://anaconda.org/conda-forge/node2vec) (πŸ“₯ 31K Β· ⏱️ 16.06.2023): + ``` + conda install -c conda-forge node2vec + ``` +
torch-cluster (πŸ₯‰22 Β· ⭐ 820) - PyTorch Extension Library of Optimized Graph Cluster.. MIT -- [GitHub](https://github.com/rusty1s/pytorch_cluster) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 140 Β· πŸ“‹ 170 - 21% open Β· ⏱️ 10.09.2024): +- [GitHub](https://github.com/rusty1s/pytorch_cluster) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 140 Β· πŸ“‹ 180 - 21% open Β· ⏱️ 10.09.2024): ``` git clone https://github.com/rusty1s/pytorch_cluster ``` -- [PyPi](https://pypi.org/project/torch-cluster) (πŸ“₯ 16K / month Β· πŸ“¦ 62 Β· ⏱️ 12.10.2023): +- [PyPi](https://pypi.org/project/torch-cluster) (πŸ“₯ 18K / month Β· πŸ“¦ 62 Β· ⏱️ 12.10.2023): ``` pip install torch-cluster ``` -- [Conda](https://anaconda.org/conda-forge/pytorch_cluster) (πŸ“₯ 200K Β· ⏱️ 28.08.2024): +- [Conda](https://anaconda.org/conda-forge/pytorch_cluster) (πŸ“₯ 210K Β· ⏱️ 28.08.2024): ``` conda install -c conda-forge pytorch_cluster ``` @@ -2922,19 +2908,19 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas ``` git clone https://github.com/snap-stanford/deepsnap ``` -- [PyPi](https://pypi.org/project/deepsnap) (πŸ“₯ 600 / month Β· πŸ“¦ 2 Β· ⏱️ 05.09.2021): +- [PyPi](https://pypi.org/project/deepsnap) (πŸ“₯ 910 / month Β· πŸ“¦ 2 Β· ⏱️ 05.09.2021): ``` pip install deepsnap ```
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“¦ 48 Β· πŸ“‹ 34 - 44% open Β· ⏱️ 07.11.2023): +- [GitHub](https://github.com/gsi-upm/sematch) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 110 Β· πŸ“¦ 48 Β· πŸ“‹ 34 - 44% open Β· ⏱️ 07.11.2023): ``` git clone https://github.com/gsi-upm/sematch ``` -- [PyPi](https://pypi.org/project/sematch) (πŸ“₯ 550 / month Β· ⏱️ 17.04.2017): +- [PyPi](https://pypi.org/project/sematch) (πŸ“₯ 510 / month Β· ⏱️ 17.04.2017): ``` pip install sematch ``` @@ -2946,7 +2932,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas ``` git clone https://github.com/vaticle/kglib ``` -- [PyPi](https://pypi.org/project/grakn-kglib) (πŸ“₯ 370 / month Β· ⏱️ 19.08.2020): +- [PyPi](https://pypi.org/project/grakn-kglib) (πŸ“₯ 560 / month Β· ⏱️ 19.08.2020): ``` pip install grakn-kglib ``` @@ -2978,23 +2964,22 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas ``` git clone https://github.com/DeepGraphLearning/graphvite ``` -- [Conda](https://anaconda.org/milagraph/graphvite) (πŸ“₯ 4.8K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/milagraph/graphvite) (πŸ“₯ 4.9K Β· ⏱️ 16.06.2023): ``` conda install -c milagraph graphvite ```
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Show 19 hidden projects... +
Show 18 hidden projects... - 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 - Paddle Graph Learning (πŸ₯ˆ26 Β· ⭐ 1.6K Β· πŸ’€) - Paddle Graph Learning (PGL) is an efficient and.. Apache-2 -- pytorch_geometric_temporal (πŸ₯ˆ24 Β· ⭐ 2.6K Β· πŸ’€) - PyTorch Geometric Temporal: Spatiotemporal Signal.. MIT -- Karate Club (πŸ₯ˆ23 Β· ⭐ 2.1K) - Karate Club: An API Oriented Open-source Python Framework for.. ❗️GPL-3.0 -- jraph (πŸ₯ˆ23 Β· ⭐ 1.4K Β· πŸ’€) - A Graph Neural Network Library in Jax. Apache-2 +- Karate Club (πŸ₯ˆ24 Β· ⭐ 2.2K) - Karate Club: An API Oriented Open-source Python Framework for.. ❗️GPL-3.0 - graph-nets (πŸ₯‰22 Β· ⭐ 5.4K Β· πŸ’€) - Build Graph Nets in Tensorflow. Apache-2 - graph4nlp (πŸ₯‰22 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 +- jraph (πŸ₯‰22 Β· ⭐ 1.4K Β· πŸ’€) - A Graph Neural Network Library in Jax. Apache-2 +- pyRDF2Vec (πŸ₯‰21 Β· ⭐ 250 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 - DIG (πŸ₯‰20 Β· ⭐ 1.9K Β· πŸ’€) - A library for graph deep learning research. ❗️GPL-3.0 - GraphGym (πŸ₯‰19 Β· ⭐ 1.7K Β· πŸ’€) - Platform for designing and evaluating Graph Neural Networks (GNN). MIT @@ -3013,72 +2998,72 @@ _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₯‡40 Β· ⭐ 8.7K) - A PyTorch-based Speech Toolkit. Apache-2 +
speechbrain (πŸ₯‡41 Β· ⭐ 8.8K) - A PyTorch-based Speech Toolkit. Apache-2 -- [GitHub](https://github.com/speechbrain/speechbrain) (πŸ‘¨β€πŸ’» 240 Β· πŸ”€ 1.4K Β· πŸ“¦ 2.3K Β· πŸ“‹ 1.1K - 12% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/speechbrain/speechbrain) (πŸ‘¨β€πŸ’» 240 Β· πŸ”€ 1.4K Β· πŸ“¦ 2.4K Β· πŸ“‹ 1.1K - 11% open Β· ⏱️ 22.10.2024): ``` git clone https://github.com/speechbrain/speechbrain ``` -- [PyPi](https://pypi.org/project/speechbrain) (πŸ“₯ 2.9M / month Β· πŸ“¦ 62 Β· ⏱️ 02.09.2024): +- [PyPi](https://pypi.org/project/speechbrain) (πŸ“₯ 3.8M / month Β· πŸ“¦ 62 Β· ⏱️ 02.09.2024): ``` pip install speechbrain ```
espnet (πŸ₯‡38 Β· ⭐ 8.4K) - End-to-End Speech Processing Toolkit. Apache-2 -- [GitHub](https://github.com/espnet/espnet) (πŸ‘¨β€πŸ’» 450 Β· πŸ”€ 2.2K Β· πŸ“₯ 82 Β· πŸ“¦ 380 Β· πŸ“‹ 2.4K - 14% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/espnet/espnet) (πŸ‘¨β€πŸ’» 450 Β· πŸ”€ 2.2K Β· πŸ“₯ 82 Β· πŸ“¦ 380 Β· πŸ“‹ 2.4K - 14% open Β· ⏱️ 20.10.2024): ``` git clone https://github.com/espnet/espnet ``` -- [PyPi](https://pypi.org/project/espnet) (πŸ“₯ 33K / month Β· πŸ“¦ 12 Β· ⏱️ 06.02.2024): +- [PyPi](https://pypi.org/project/espnet) (πŸ“₯ 39K / month Β· πŸ“¦ 12 Β· ⏱️ 06.02.2024): ``` pip install espnet ```
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Coqui TTS (πŸ₯‡35 Β· ⭐ 34K Β· πŸ’€) - - a deep learning toolkit for Text-to-Speech, battle-.. MPL-2.0 +
Coqui TTS (πŸ₯‡35 Β· ⭐ 35K Β· πŸ’€) - - a deep learning toolkit for Text-to-Speech, battle-.. MPL-2.0 -- [GitHub](https://github.com/coqui-ai/TTS) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 4.2K Β· πŸ“₯ 3.3M Β· πŸ“¦ 1.8K Β· πŸ“‹ 1.1K - 7% open Β· ⏱️ 10.02.2024): +- [GitHub](https://github.com/coqui-ai/TTS) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 4.2K Β· πŸ“₯ 3.5M Β· πŸ“¦ 1.8K Β· πŸ“‹ 1.1K - 7% open Β· ⏱️ 10.02.2024): ``` git clone https://github.com/coqui-ai/TTS ``` -- [PyPi](https://pypi.org/project/tts) (πŸ“₯ 120K / month Β· πŸ“¦ 53 Β· ⏱️ 12.12.2023): +- [PyPi](https://pypi.org/project/tts) (πŸ“₯ 130K / month Β· πŸ“¦ 53 Β· ⏱️ 12.12.2023): ``` pip install tts ``` -- [Conda](https://anaconda.org/conda-forge/tts) (πŸ“₯ 17K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/tts) (πŸ“₯ 18K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge tts ```
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torchaudio (πŸ₯‡35 Β· ⭐ 2.5K) - Data manipulation and transformation for audio signal.. BSD-2 +
SpeechRecognition (πŸ₯‡35 Β· ⭐ 8.4K Β· πŸ“ˆ) - Speech recognition module for Python, supporting.. BSD-3 -- [GitHub](https://github.com/pytorch/audio) (πŸ‘¨β€πŸ’» 230 Β· πŸ”€ 640 Β· πŸ“‹ 980 - 25% open Β· ⏱️ 29.09.2024): +- [GitHub](https://github.com/Uberi/speech_recognition) (πŸ‘¨β€πŸ’» 51 Β· πŸ”€ 2.4K Β· πŸ“¦ 21 Β· πŸ“‹ 660 - 50% open Β· ⏱️ 21.10.2024): ``` - git clone https://github.com/pytorch/audio + git clone https://github.com/Uberi/speech_recognition ``` -- [PyPi](https://pypi.org/project/torchaudio) (πŸ“₯ 5.5M / month Β· πŸ“¦ 1.3K Β· ⏱️ 04.09.2024): +- [PyPi](https://pypi.org/project/SpeechRecognition) (πŸ“₯ 1.1M / month Β· πŸ“¦ 580 Β· ⏱️ 20.10.2024): ``` - pip install torchaudio + pip install SpeechRecognition + ``` +- [Conda](https://anaconda.org/conda-forge/speechrecognition) (πŸ“₯ 210K Β· ⏱️ 06.05.2024): + ``` + conda install -c conda-forge speechrecognition ```
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SpeechRecognition (πŸ₯ˆ33 Β· ⭐ 8.4K) - Speech recognition module for Python, supporting several.. BSD-3 +
torchaudio (πŸ₯‡35 Β· ⭐ 2.5K) - Data manipulation and transformation for audio signal.. BSD-2 -- [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): +- [GitHub](https://github.com/pytorch/audio) (πŸ‘¨β€πŸ’» 230 Β· πŸ”€ 650 Β· πŸ“‹ 980 - 26% open Β· ⏱️ 23.10.2024): ``` - git clone https://github.com/Uberi/speech_recognition - ``` -- [PyPi](https://pypi.org/project/SpeechRecognition) (πŸ“₯ 1.1M / month Β· πŸ“¦ 580 Β· ⏱️ 05.05.2024): - ``` - pip install SpeechRecognition + git clone https://github.com/pytorch/audio ``` -- [Conda](https://anaconda.org/conda-forge/speechrecognition) (πŸ“₯ 200K Β· ⏱️ 06.05.2024): +- [PyPi](https://pypi.org/project/torchaudio) (πŸ“₯ 6.6M / month Β· πŸ“¦ 1.4K Β· ⏱️ 17.10.2024): ``` - conda install -c conda-forge speechrecognition + pip install torchaudio ```
librosa (πŸ₯ˆ33 Β· ⭐ 7.1K) - Python library for audio and music analysis. ISC @@ -3088,7 +3073,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as ``` git clone https://github.com/librosa/librosa ``` -- [PyPi](https://pypi.org/project/librosa) (πŸ“₯ 2.8M / month Β· πŸ“¦ 1.4K Β· ⏱️ 14.05.2024): +- [PyPi](https://pypi.org/project/librosa) (πŸ“₯ 3.1M / month Β· πŸ“¦ 1.4K Β· ⏱️ 14.05.2024): ``` pip install librosa ``` @@ -3099,48 +3084,48 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as
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“¦ 530 Β· πŸ“‹ 1K - 41% open Β· ⏱️ 01.08.2024): +- [GitHub](https://github.com/magenta/magenta) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 3.7K Β· πŸ“¦ 540 Β· πŸ“‹ 1K - 41% open Β· ⏱️ 01.08.2024): ``` git clone https://github.com/magenta/magenta ``` -- [PyPi](https://pypi.org/project/magenta) (πŸ“₯ 7K / month Β· πŸ“¦ 5 Β· ⏱️ 01.08.2022): +- [PyPi](https://pypi.org/project/magenta) (πŸ“₯ 8.1K / month Β· πŸ“¦ 5 Β· ⏱️ 01.08.2022): ``` pip install magenta ```
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audiomentations (πŸ₯ˆ31 Β· ⭐ 1.8K) - A Python library for audio data augmentation. Inspired by.. MIT +
audiomentations (πŸ₯ˆ31 Β· ⭐ 1.9K) - A Python library for audio data augmentation. Inspired by.. MIT -- [GitHub](https://github.com/iver56/audiomentations) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 190 Β· πŸ“¦ 580 Β· πŸ“‹ 180 - 25% open Β· ⏱️ 07.10.2024): +- [GitHub](https://github.com/iver56/audiomentations) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 190 Β· πŸ“¦ 590 Β· πŸ“‹ 180 - 25% open Β· ⏱️ 07.10.2024): ``` git clone https://github.com/iver56/audiomentations ``` -- [PyPi](https://pypi.org/project/audiomentations) (πŸ“₯ 49K / month Β· πŸ“¦ 18 Β· ⏱️ 03.09.2024): +- [PyPi](https://pypi.org/project/audiomentations) (πŸ“₯ 52K / month Β· πŸ“¦ 18 Β· ⏱️ 03.09.2024): ``` pip install audiomentations ```
Porcupine (πŸ₯ˆ30 Β· ⭐ 3.7K) - On-device wake word detection powered by deep learning. Apache-2 -- [GitHub](https://github.com/Picovoice/porcupine) (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 500 Β· πŸ“¦ 34 Β· πŸ“‹ 550 - 0% open Β· ⏱️ 27.09.2024): +- [GitHub](https://github.com/Picovoice/porcupine) (πŸ‘¨β€πŸ’» 39 Β· πŸ”€ 500 Β· πŸ“¦ 34 Β· πŸ“‹ 550 - 0% open Β· ⏱️ 22.10.2024): ``` git clone https://github.com/Picovoice/Porcupine ``` -- [PyPi](https://pypi.org/project/pvporcupine) (πŸ“₯ 12K / month Β· πŸ“¦ 35 Β· ⏱️ 27.08.2024): +- [PyPi](https://pypi.org/project/pvporcupine) (πŸ“₯ 13K / month Β· πŸ“¦ 35 Β· ⏱️ 27.08.2024): ``` pip install pvporcupine ```
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audioread (πŸ₯ˆ30 Β· ⭐ 480 Β· πŸ’€) - cross-library (GStreamer + Core Audio + MAD + FFmpeg) audio.. MIT +
audioread (πŸ₯ˆ30 Β· ⭐ 490 Β· πŸ’€) - cross-library (GStreamer + Core Audio + MAD + FFmpeg) audio.. MIT -- [GitHub](https://github.com/beetbox/audioread) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 110 Β· πŸ“¦ 24K Β· πŸ“‹ 94 - 39% open Β· ⏱️ 15.12.2023): +- [GitHub](https://github.com/beetbox/audioread) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 110 Β· πŸ“¦ 25K Β· πŸ“‹ 94 - 39% open Β· ⏱️ 15.12.2023): ``` git clone https://github.com/beetbox/audioread ``` -- [PyPi](https://pypi.org/project/audioread) (πŸ“₯ 2.1M / month Β· πŸ“¦ 140 Β· ⏱️ 27.09.2023): +- [PyPi](https://pypi.org/project/audioread) (πŸ“₯ 2.2M / month Β· πŸ“¦ 140 Β· ⏱️ 27.09.2023): ``` pip install audioread ``` @@ -3149,32 +3134,44 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as conda install -c conda-forge audioread ```
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pyAudioAnalysis (πŸ₯‰28 Β· ⭐ 5.8K Β· πŸ’€) - Python Audio Analysis Library: Feature Extraction,.. Apache-2 +
pyAudioAnalysis (πŸ₯‰28 Β· ⭐ 5.9K 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“¦ 520 Β· πŸ“‹ 320 - 62% open Β· ⏱️ 22.10.2023): ``` git clone https://github.com/tyiannak/pyAudioAnalysis ``` -- [PyPi](https://pypi.org/project/pyAudioAnalysis) (πŸ“₯ 15K / month Β· πŸ“¦ 12 Β· ⏱️ 07.02.2022): +- [PyPi](https://pypi.org/project/pyAudioAnalysis) (πŸ“₯ 14K / month Β· πŸ“¦ 12 Β· ⏱️ 07.02.2022): ``` pip install pyAudioAnalysis ```
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python-soundfile (πŸ₯‰28 Β· ⭐ 700) - SoundFile is an audio library based on libsndfile, CFFI, and.. BSD-3 +
python-soundfile (πŸ₯‰28 Β· ⭐ 710) - SoundFile is an audio library based on libsndfile, CFFI, and.. BSD-3 + +- [GitHub](https://github.com/bastibe/python-soundfile) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 110 Β· πŸ“₯ 20K Β· πŸ“¦ 44K Β· πŸ“‹ 260 - 46% open Β· ⏱️ 27.07.2024): + + ``` + git clone https://github.com/bastibe/python-soundfile + ``` +- [PyPi](https://pypi.org/project/soundfile) (πŸ“₯ 4.8M / month Β· πŸ“¦ 780 Β· ⏱️ 15.02.2023): + ``` + pip install soundfile + ``` +- [Conda](https://anaconda.org/anaconda/pysoundfile): + ``` + conda install -c anaconda pysoundfile + ``` +
+
tinytag (πŸ₯‰28 Β· ⭐ 700 Β· πŸ“ˆ) - Python library for reading audio file metadata. MIT -- [GitHub](https://github.com/bastibe/python-soundfile) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 110 Β· πŸ“₯ 20K Β· πŸ“¦ 43K Β· πŸ“‹ 260 - 46% open Β· ⏱️ 27.07.2024): +- [GitHub](https://github.com/tinytag/tinytag) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 100 Β· πŸ“¦ 1.1K Β· πŸ“‹ 130 - 11% open Β· ⏱️ 20.10.2024): ``` - git clone https://github.com/bastibe/python-soundfile - ``` -- [PyPi](https://pypi.org/project/soundfile) (πŸ“₯ 5.7M / month Β· πŸ“¦ 780 Β· ⏱️ 15.02.2023): - ``` - pip install soundfile + git clone https://github.com/devsnd/tinytag ``` -- [Conda](https://anaconda.org/anaconda/pysoundfile): +- [PyPi](https://pypi.org/project/tinytag) (πŸ“₯ 27K / month Β· πŸ“¦ 110 Β· ⏱️ 26.10.2023): ``` - conda install -c anaconda pysoundfile + pip install tinytag ```
Madmom (πŸ₯‰27 Β· ⭐ 1.3K) - Python audio and music signal processing library. BSD-3 @@ -3184,7 +3181,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as ``` git clone https://github.com/CPJKU/madmom ``` -- [PyPi](https://pypi.org/project/madmom) (πŸ“₯ 2.6K / month Β· πŸ“¦ 27 Β· ⏱️ 14.11.2018): +- [PyPi](https://pypi.org/project/madmom) (πŸ“₯ 2.7K / month Β· πŸ“¦ 27 Β· ⏱️ 14.11.2018): ``` pip install madmom ``` @@ -3196,43 +3193,31 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as ``` git clone https://github.com/magenta/ddsp ``` -- [PyPi](https://pypi.org/project/ddsp) (πŸ“₯ 4.5K / month Β· πŸ“¦ 1 Β· ⏱️ 25.05.2022): +- [PyPi](https://pypi.org/project/ddsp) (πŸ“₯ 5.9K / month Β· πŸ“¦ 1 Β· ⏱️ 25.05.2022): ``` pip install ddsp ``` -- [Conda](https://anaconda.org/conda-forge/ddsp) (πŸ“₯ 18K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/ddsp) (πŸ“₯ 19K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge ddsp ```
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tinytag (πŸ₯‰24 Β· ⭐ 690) - Python library for reading audio file metadata. MIT - -- [GitHub](https://github.com/tinytag/tinytag) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 100 Β· πŸ“‹ 130 - 11% open Β· ⏱️ 29.08.2024): - - ``` - git clone https://github.com/devsnd/tinytag - ``` -- [PyPi](https://pypi.org/project/tinytag) (πŸ“₯ 28K / month Β· πŸ“¦ 110 Β· ⏱️ 26.10.2023): - ``` - pip install tinytag - ``` -
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”€ 89 Β· πŸ“¦ 220 Β· πŸ“‹ 63 - 28% open Β· ⏱️ 13.02.2024): +- [GitHub](https://github.com/KinWaiCheuk/nnAudio) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 89 Β· πŸ“¦ 230 Β· πŸ“‹ 63 - 28% open Β· ⏱️ 13.02.2024): ``` git clone https://github.com/KinWaiCheuk/nnAudio ``` -- [PyPi](https://pypi.org/project/nnAudio) (πŸ“₯ 16K / month Β· πŸ“¦ 4 Β· ⏱️ 13.02.2024): +- [PyPi](https://pypi.org/project/nnAudio) (πŸ“₯ 15K / month Β· πŸ“¦ 4 Β· ⏱️ 13.02.2024): ``` pip install nnAudio ```
Show 13 hidden projects... -- DeepSpeech (πŸ₯ˆ34 Β· ⭐ 25K Β· πŸ’€) - DeepSpeech is an open source embedded (offline, on-.. MPL-2.0 -- Pydub (πŸ₯ˆ34 Β· ⭐ 8.8K Β· πŸ’€) - Manipulate audio with a simple and easy high level interface. MIT +- DeepSpeech (πŸ₯‡35 Β· ⭐ 25K Β· πŸ’€) - DeepSpeech is an open source embedded (offline, on-.. MPL-2.0 +- Pydub (πŸ₯ˆ34 Β· ⭐ 8.9K Β· πŸ’€) - Manipulate audio with a simple and easy high level interface. MIT - 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 @@ -3240,7 +3225,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as - 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 +- TimeSide (πŸ₯‰22 Β· ⭐ 370) - scalable audio processing framework and server written in Python. ❗️AGPL-3.0 - Julius (πŸ₯‰21 Β· ⭐ 420 Β· πŸ’€) - Fast PyTorch based DSP for audio and 1D signals. MIT - Muda (πŸ₯‰18 Β· ⭐ 230 Β· πŸ’€) - A library for augmenting annotated audio data. ISC - textlesslib (πŸ₯‰10 Β· ⭐ 530 Β· πŸ’€) - Library for Textless Spoken Language Processing. MIT @@ -3255,27 +3240,27 @@ _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’» 270 Β· πŸ”€ 2.1K Β· πŸ“¦ 8.1K Β· πŸ“‹ 3.1K - 11% open Β· ⏱️ 04.10.2024): +- [GitHub](https://github.com/visgl/deck.gl) (πŸ‘¨β€πŸ’» 270 Β· πŸ”€ 2.1K Β· πŸ“¦ 8.2K Β· πŸ“‹ 3.1K - 11% open Β· ⏱️ 21.10.2024): ``` git clone https://github.com/visgl/deck.gl ``` -- [PyPi](https://pypi.org/project/pydeck) (πŸ“₯ 5.5M / month Β· πŸ“¦ 120 Β· ⏱️ 10.05.2024): +- [PyPi](https://pypi.org/project/pydeck) (πŸ“₯ 5.7M / month Β· πŸ“¦ 120 Β· ⏱️ 10.05.2024): ``` pip install pydeck ``` -- [Conda](https://anaconda.org/conda-forge/pydeck) (πŸ“₯ 620K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/pydeck) (πŸ“₯ 630K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge pydeck ``` -- [npm](https://www.npmjs.com/package/deck.gl) (πŸ“₯ 580K / month Β· πŸ“¦ 300 Β· ⏱️ 08.10.2024): +- [npm](https://www.npmjs.com/package/deck.gl) (πŸ“₯ 610K / month Β· πŸ“¦ 300 Β· ⏱️ 08.10.2024): ``` npm install deck.gl ```
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Shapely (πŸ₯‡40 Β· ⭐ 3.9K Β· πŸ“‰) - Manipulation and analysis of geometric objects. BSD-3 +
Shapely (πŸ₯‡40 Β· ⭐ 3.9K) - Manipulation and analysis of geometric objects. BSD-3 -- [GitHub](https://github.com/shapely/shapely) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 560 Β· πŸ“₯ 3.7K Β· πŸ“¦ 81K Β· πŸ“‹ 1.2K - 23% open Β· ⏱️ 02.10.2024): +- [GitHub](https://github.com/shapely/shapely) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 560 Β· πŸ“₯ 3.7K Β· πŸ“¦ 83K Β· πŸ“‹ 1.2K - 23% open Β· ⏱️ 17.10.2024): ``` git clone https://github.com/shapely/shapely @@ -3284,67 +3269,67 @@ _Libraries to load, process, analyze, and write geographic data as well as libra ``` pip install shapely ``` -- [Conda](https://anaconda.org/conda-forge/shapely) (πŸ“₯ 10M Β· ⏱️ 25.09.2024): +- [Conda](https://anaconda.org/conda-forge/shapely) (πŸ“₯ 11M Β· ⏱️ 25.09.2024): ``` conda install -c conda-forge shapely ```
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GeoPandas (πŸ₯‡39 Β· ⭐ 4.5K) - Python tools for geographic data. BSD-3 +
folium (πŸ₯‡39 Β· ⭐ 6.9K) - Python Data. Leaflet.js Maps. MIT -- [GitHub](https://github.com/geopandas/geopandas) (πŸ‘¨β€πŸ’» 230 Β· πŸ”€ 920 Β· πŸ“₯ 2.7K Β· πŸ“¦ 42K Β· πŸ“‹ 1.7K - 25% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/python-visualization/folium) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 2.2K Β· πŸ“¦ 45K Β· πŸ“‹ 1.1K - 7% open Β· ⏱️ 23.10.2024): ``` - git clone https://github.com/geopandas/geopandas + git clone https://github.com/python-visualization/folium ``` -- [PyPi](https://pypi.org/project/geopandas) (πŸ“₯ 7.8M / month Β· πŸ“¦ 2.8K Β· ⏱️ 02.07.2024): +- [PyPi](https://pypi.org/project/folium) (πŸ“₯ 1.5M / month Β· πŸ“¦ 770 Β· ⏱️ 22.10.2024): ``` - pip install geopandas + pip install folium ``` -- [Conda](https://anaconda.org/conda-forge/geopandas) (πŸ“₯ 4M Β· ⏱️ 21.09.2024): +- [Conda](https://anaconda.org/conda-forge/folium) (πŸ“₯ 3.2M Β· ⏱️ 23.10.2024): ``` - conda install -c conda-forge geopandas + conda install -c conda-forge folium ```
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folium (πŸ₯ˆ38 Β· ⭐ 6.9K) - Python Data. Leaflet.js Maps. MIT +
GeoPandas (πŸ₯‡39 Β· ⭐ 4.5K) - Python tools for geographic data. BSD-3 -- [GitHub](https://github.com/python-visualization/folium) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 2.2K Β· πŸ“¦ 44K Β· πŸ“‹ 1.1K - 7% open Β· ⏱️ 08.10.2024): +- [GitHub](https://github.com/geopandas/geopandas) (πŸ‘¨β€πŸ’» 230 Β· πŸ”€ 930 Β· πŸ“₯ 2.7K Β· πŸ“¦ 42K Β· πŸ“‹ 1.7K - 26% open Β· ⏱️ 16.10.2024): ``` - git clone https://github.com/python-visualization/folium + git clone https://github.com/geopandas/geopandas ``` -- [PyPi](https://pypi.org/project/folium) (πŸ“₯ 1.5M / month Β· πŸ“¦ 750 Β· ⏱️ 16.06.2024): +- [PyPi](https://pypi.org/project/geopandas) (πŸ“₯ 7.9M / month Β· πŸ“¦ 2.8K Β· ⏱️ 02.07.2024): ``` - pip install folium + pip install geopandas ``` -- [Conda](https://anaconda.org/conda-forge/folium) (πŸ“₯ 3.1M Β· ⏱️ 17.06.2024): +- [Conda](https://anaconda.org/conda-forge/geopandas) (πŸ“₯ 4.1M Β· ⏱️ 21.09.2024): ``` - conda install -c conda-forge folium + conda install -c conda-forge geopandas ```
Rasterio (πŸ₯ˆ38 Β· ⭐ 2.2K) - Rasterio reads and writes geospatial raster datasets. BSD-3 -- [GitHub](https://github.com/rasterio/rasterio) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 530 Β· πŸ“₯ 970 Β· πŸ“¦ 13K Β· πŸ“‹ 1.8K - 7% open Β· ⏱️ 07.10.2024): +- [GitHub](https://github.com/rasterio/rasterio) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 530 Β· πŸ“₯ 970 Β· πŸ“¦ 13K Β· πŸ“‹ 1.8K - 7% open Β· ⏱️ 22.10.2024): ``` git clone https://github.com/rasterio/rasterio ``` -- [PyPi](https://pypi.org/project/rasterio) (πŸ“₯ 3.5M / month Β· πŸ“¦ 1.4K Β· ⏱️ 01.10.2024): +- [PyPi](https://pypi.org/project/rasterio) (πŸ“₯ 3.7M / month Β· πŸ“¦ 1.4K Β· ⏱️ 01.10.2024): ``` pip install rasterio ``` -- [Conda](https://anaconda.org/conda-forge/rasterio) (πŸ“₯ 3.6M Β· ⏱️ 01.10.2024): +- [Conda](https://anaconda.org/conda-forge/rasterio) (πŸ“₯ 3.7M Β· ⏱️ 01.10.2024): ``` conda install -c conda-forge rasterio ```
ArcGIS API (πŸ₯ˆ37 Β· ⭐ 1.9K) - Documentation and samples for ArcGIS API for Python. Apache-2 -- [GitHub](https://github.com/Esri/arcgis-python-api) (πŸ‘¨β€πŸ’» 92 Β· πŸ”€ 1.1K Β· πŸ“₯ 12K Β· πŸ“¦ 840 Β· πŸ“‹ 760 - 8% open Β· ⏱️ 02.10.2024): +- [GitHub](https://github.com/Esri/arcgis-python-api) (πŸ‘¨β€πŸ’» 94 Β· πŸ”€ 1.1K Β· πŸ“₯ 13K Β· πŸ“¦ 840 Β· πŸ“‹ 770 - 8% open Β· ⏱️ 17.10.2024): ``` git clone https://github.com/Esri/arcgis-python-api ``` -- [PyPi](https://pypi.org/project/arcgis) (πŸ“₯ 78K / month Β· πŸ“¦ 40 Β· ⏱️ 01.10.2024): +- [PyPi](https://pypi.org/project/arcgis) (πŸ“₯ 81K / month Β· πŸ“¦ 40 Β· ⏱️ 01.10.2024): ``` pip install arcgis ``` @@ -3355,44 +3340,44 @@ _Libraries to load, process, analyze, and write geographic data as well as libra
Fiona (πŸ₯ˆ37 Β· ⭐ 1.2K) - Fiona reads and writes geographic data files. BSD-3 -- [GitHub](https://github.com/Toblerity/Fiona) (πŸ‘¨β€πŸ’» 76 Β· πŸ”€ 200 Β· πŸ“¦ 23K Β· πŸ“‹ 800 - 3% open Β· ⏱️ 30.09.2024): +- [GitHub](https://github.com/Toblerity/Fiona) (πŸ‘¨β€πŸ’» 76 Β· πŸ”€ 200 Β· πŸ“¦ 23K Β· πŸ“‹ 810 - 3% open Β· ⏱️ 21.10.2024): ``` git clone https://github.com/Toblerity/Fiona ``` -- [PyPi](https://pypi.org/project/fiona) (πŸ“₯ 5.3M / month Β· πŸ“¦ 270 Β· ⏱️ 16.09.2024): +- [PyPi](https://pypi.org/project/fiona) (πŸ“₯ 5.4M / month Β· πŸ“¦ 300 Β· ⏱️ 16.09.2024): ``` pip install fiona ``` -- [Conda](https://anaconda.org/conda-forge/fiona) (πŸ“₯ 6M Β· ⏱️ 18.09.2024): +- [Conda](https://anaconda.org/conda-forge/fiona) (πŸ“₯ 6.1M Β· ⏱️ 18.09.2024): ``` conda install -c conda-forge fiona ```
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pyproj (πŸ₯ˆ36 Β· ⭐ 1K) - Python interface to PROJ (cartographic projections and coordinate.. MIT +
pyproj (πŸ₯ˆ36 Β· ⭐ 1.1K) - Python interface to PROJ (cartographic projections and coordinate.. MIT -- [GitHub](https://github.com/pyproj4/pyproj) (πŸ‘¨β€πŸ’» 66 Β· πŸ”€ 210 Β· πŸ“¦ 34K Β· πŸ“‹ 620 - 5% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/pyproj4/pyproj) (πŸ‘¨β€πŸ’» 67 Β· πŸ”€ 210 Β· πŸ“¦ 35K Β· πŸ“‹ 620 - 5% open Β· ⏱️ 22.10.2024): ``` git clone https://github.com/pyproj4/pyproj ``` -- [PyPi](https://pypi.org/project/pyproj) (πŸ“₯ 9.6M / month Β· πŸ“¦ 1.7K Β· ⏱️ 01.10.2024): +- [PyPi](https://pypi.org/project/pyproj) (πŸ“₯ 9.9M / month Β· πŸ“¦ 1.7K Β· ⏱️ 01.10.2024): ``` pip install pyproj ``` -- [Conda](https://anaconda.org/conda-forge/pyproj) (πŸ“₯ 8.7M Β· ⏱️ 01.10.2024): +- [Conda](https://anaconda.org/conda-forge/pyproj) (πŸ“₯ 8.8M Β· ⏱️ 01.10.2024): ``` conda install -c conda-forge pyproj ```
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geopy (πŸ₯ˆ33 Β· ⭐ 4.4K Β· πŸ’€) - Geocoding library for Python. MIT +
geopy (πŸ₯ˆ33 Β· ⭐ 4.5K Β· πŸ’€) - Geocoding library for Python. MIT -- [GitHub](https://github.com/geopy/geopy) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 640 Β· πŸ“₯ 84 Β· πŸ“‹ 290 - 13% open Β· ⏱️ 23.11.2023): +- [GitHub](https://github.com/geopy/geopy) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 640 Β· πŸ“₯ 87 Β· πŸ“‹ 290 - 13% open Β· ⏱️ 23.11.2023): ``` git clone https://github.com/geopy/geopy ``` -- [PyPi](https://pypi.org/project/geopy) (πŸ“₯ 6.3M / month Β· πŸ“¦ 900 Β· ⏱️ 23.11.2023): +- [PyPi](https://pypi.org/project/geopy) (πŸ“₯ 6M / month Β· πŸ“¦ 900 Β· ⏱️ 23.11.2023): ``` pip install geopy ``` @@ -3401,14 +3386,14 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge geopy ```
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ipyleaflet (πŸ₯ˆ33 Β· ⭐ 1.5K) - A Jupyter - Leaflet.js bridge. MIT +
ipyleaflet (πŸ₯‰32 Β· ⭐ 1.5K) - A Jupyter - Leaflet.js bridge. MIT -- [GitHub](https://github.com/jupyter-widgets/ipyleaflet) (πŸ‘¨β€πŸ’» 90 Β· πŸ”€ 360 Β· πŸ“¦ 12K Β· πŸ“‹ 650 - 44% open Β· ⏱️ 22.07.2024): +- [GitHub](https://github.com/jupyter-widgets/ipyleaflet) (πŸ‘¨β€πŸ’» 90 Β· πŸ”€ 360 Β· πŸ“¦ 12K Β· πŸ“‹ 650 - 44% open Β· ⏱️ 21.10.2024): ``` git clone https://github.com/jupyter-widgets/ipyleaflet ``` -- [PyPi](https://pypi.org/project/ipyleaflet) (πŸ“₯ 280K / month Β· πŸ“¦ 280 Β· ⏱️ 22.07.2024): +- [PyPi](https://pypi.org/project/ipyleaflet) (πŸ“₯ 230K / month Β· πŸ“¦ 280 Β· ⏱️ 22.07.2024): ``` pip install ipyleaflet ``` @@ -3416,12 +3401,12 @@ _Libraries to load, process, analyze, and write geographic data as well as libra ``` conda install -c conda-forge ipyleaflet ``` -- [npm](https://www.npmjs.com/package/jupyter-leaflet) (πŸ“₯ 7.4K / month Β· πŸ“¦ 9 Β· ⏱️ 22.07.2024): +- [npm](https://www.npmjs.com/package/jupyter-leaflet) (πŸ“₯ 7.5K / month Β· πŸ“¦ 9 Β· ⏱️ 22.07.2024): ``` npm install jupyter-leaflet ```
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PySAL (πŸ₯‰32 Β· ⭐ 1.3K) - PySAL: Python Spatial Analysis Library Meta-Package. BSD-3 +
PySAL (πŸ₯‰31 Β· ⭐ 1.3K) - PySAL: Python Spatial Analysis Library Meta-Package. BSD-3 - [GitHub](https://github.com/pysal/pysal) (πŸ‘¨β€πŸ’» 79 Β· πŸ”€ 300 Β· πŸ“¦ 1.7K Β· πŸ“‹ 650 - 2% open Β· ⏱️ 07.10.2024): @@ -3437,14 +3422,14 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge pysal ```
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geojson (πŸ₯‰30 Β· ⭐ 910) - Python bindings and utilities for GeoJSON. BSD-3 +
geojson (πŸ₯‰30 Β· ⭐ 920) - Python bindings and utilities for GeoJSON. BSD-3 -- [GitHub](https://github.com/jazzband/geojson) (πŸ‘¨β€πŸ’» 58 Β· πŸ”€ 120 Β· πŸ“¦ 18K Β· πŸ“‹ 100 - 25% open Β· ⏱️ 04.10.2024): +- [GitHub](https://github.com/jazzband/geojson) (πŸ‘¨β€πŸ’» 58 Β· πŸ”€ 120 Β· πŸ“¦ 19K Β· πŸ“‹ 100 - 25% open Β· ⏱️ 04.10.2024): ``` git clone https://github.com/jazzband/geojson ``` -- [PyPi](https://pypi.org/project/geojson) (πŸ“₯ 3.1M / month Β· πŸ“¦ 700 Β· ⏱️ 05.11.2023): +- [PyPi](https://pypi.org/project/geojson) (πŸ“₯ 3M / month Β· πŸ“¦ 700 Β· ⏱️ 05.11.2023): ``` pip install geojson ``` @@ -3453,14 +3438,14 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge geojson ```
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GeoViews (πŸ₯‰29 Β· ⭐ 590) - Simple, concise geographical visualization in Python. BSD-3 +
GeoViews (πŸ₯‰29 Β· ⭐ 600) - Simple, concise geographical visualization in Python. BSD-3 -- [GitHub](https://github.com/holoviz/geoviews) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 75 Β· πŸ“¦ 1.1K Β· πŸ“‹ 340 - 29% open Β· ⏱️ 08.10.2024): +- [GitHub](https://github.com/holoviz/geoviews) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 76 Β· πŸ“¦ 1.1K Β· πŸ“‹ 350 - 30% open Β· ⏱️ 08.10.2024): ``` git clone https://github.com/holoviz/geoviews ``` -- [PyPi](https://pypi.org/project/geoviews) (πŸ“₯ 17K / month Β· πŸ“¦ 59 Β· ⏱️ 16.09.2024): +- [PyPi](https://pypi.org/project/geoviews) (πŸ“₯ 20K / month Β· πŸ“¦ 59 Β· ⏱️ 16.09.2024): ``` pip install geoviews ``` @@ -3471,7 +3456,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra
pymap3d (πŸ₯‰23 Β· ⭐ 390 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”€ 87 Β· πŸ“¦ 440 Β· πŸ“‹ 58 - 15% open Β· ⏱️ 11.02.2024): +- [GitHub](https://github.com/geospace-code/pymap3d) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 87 Β· πŸ“¦ 450 Β· πŸ“‹ 58 - 15% open Β· ⏱️ 11.02.2024): ``` git clone https://github.com/geospace-code/pymap3d @@ -3480,7 +3465,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra ``` pip install pymap3d ``` -- [Conda](https://anaconda.org/conda-forge/pymap3d) (πŸ“₯ 82K Β· ⏱️ 11.02.2024): +- [Conda](https://anaconda.org/conda-forge/pymap3d) (πŸ“₯ 83K Β· ⏱️ 11.02.2024): ``` conda install -c conda-forge pymap3d ``` @@ -3490,7 +3475,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra - Geocoder (πŸ₯‰32 Β· ⭐ 1.6K Β· πŸ’€) - Python Geocoder. MIT - Satpy (πŸ₯‰32 Β· ⭐ 1.1K) - Python package for earth-observing satellite data processing. ❗️GPL-3.0 - Sentinelsat (πŸ₯‰27 Β· ⭐ 980 Β· πŸ’€) - Search and download Copernicus Sentinel satellite images. ❗️GPL-3.0 -- EarthPy (πŸ₯‰26 Β· ⭐ 500 Β· πŸ’€) - A package built to support working with spatial data using open.. BSD-3 +- EarthPy (πŸ₯‰26 Β· ⭐ 510 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 - gmaps (πŸ₯‰22 Β· ⭐ 760 Β· πŸ’€) - Google maps for Jupyter notebooks. BSD-3 @@ -3504,14 +3489,14 @@ _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₯‡41 Β· ⭐ 13K) - Download market data from Yahoo! Finances API. Apache-2 +
yfinance (πŸ₯‡41 Β· ⭐ 14K) - Download market data from Yahoo! Finances API. Apache-2 -- [GitHub](https://github.com/ranaroussi/yfinance) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 2.3K Β· πŸ“¦ 48K Β· πŸ“‹ 1.4K - 13% open Β· ⏱️ 07.10.2024): +- [GitHub](https://github.com/ranaroussi/yfinance) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 2.4K Β· πŸ“¦ 49K Β· πŸ“‹ 1.4K - 12% open Β· ⏱️ 22.10.2024): ``` git clone https://github.com/ranaroussi/yfinance ``` -- [PyPi](https://pypi.org/project/yfinance) (πŸ“₯ 2.3M / month Β· πŸ“¦ 660 Β· ⏱️ 30.09.2024): +- [PyPi](https://pypi.org/project/yfinance) (πŸ“₯ 2.4M / month Β· πŸ“¦ 670 Β· ⏱️ 21.10.2024): ``` pip install yfinance ``` @@ -3520,42 +3505,42 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te conda install -c ranaroussi yfinance ```
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bt (πŸ₯‡31 Β· ⭐ 2.2K) - bt - flexible backtesting for Python. MIT +
bt (πŸ₯‡31 Β· ⭐ 2.3K) - bt - flexible backtesting for Python. MIT -- [GitHub](https://github.com/pmorissette/bt) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 410 Β· πŸ“¦ 1.6K Β· πŸ“‹ 340 - 22% open Β· ⏱️ 01.10.2024): +- [GitHub](https://github.com/pmorissette/bt) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 430 Β· πŸ“¦ 1.6K Β· πŸ“‹ 340 - 22% open Β· ⏱️ 01.10.2024): ``` git clone https://github.com/pmorissette/bt ``` -- [PyPi](https://pypi.org/project/bt) (πŸ“₯ 9.3K / month Β· πŸ“¦ 10 Β· ⏱️ 06.08.2024): +- [PyPi](https://pypi.org/project/bt) (πŸ“₯ 13K / month Β· πŸ“¦ 10 Β· ⏱️ 06.08.2024): ``` pip install bt ``` -- [Conda](https://anaconda.org/conda-forge/bt) (πŸ“₯ 46K Β· ⏱️ 21.09.2024): +- [Conda](https://anaconda.org/conda-forge/bt) (πŸ“₯ 48K Β· ⏱️ 21.09.2024): ``` conda install -c conda-forge bt ```
Qlib (πŸ₯ˆ30 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”€ 2.6K Β· πŸ“₯ 720 Β· πŸ“¦ 21 Β· πŸ“‹ 930 - 25% open Β· ⏱️ 12.09.2024): +- [GitHub](https://github.com/microsoft/qlib) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 2.6K Β· πŸ“₯ 730 Β· πŸ“¦ 21 Β· πŸ“‹ 930 - 25% open Β· ⏱️ 12.09.2024): ``` git clone https://github.com/microsoft/qlib ``` -- [PyPi](https://pypi.org/project/pyqlib) (πŸ“₯ 4.8K / month Β· πŸ“¦ 1 Β· ⏱️ 24.05.2024): +- [PyPi](https://pypi.org/project/pyqlib) (πŸ“₯ 7.7K / month Β· πŸ“¦ 1 Β· ⏱️ 24.05.2024): ``` pip install pyqlib ```
ta (πŸ₯ˆ29 Β· ⭐ 4.3K Β· πŸ’€) - Technical Analysis Library using Pandas and Numpy. MIT -- [GitHub](https://github.com/bukosabino/ta) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 890 Β· πŸ“¦ 4.2K Β· πŸ“‹ 240 - 57% open Β· ⏱️ 02.11.2023): +- [GitHub](https://github.com/bukosabino/ta) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 900 Β· πŸ“¦ 4.3K Β· πŸ“‹ 240 - 57% open Β· ⏱️ 02.11.2023): ``` git clone https://github.com/bukosabino/ta ``` -- [PyPi](https://pypi.org/project/ta) (πŸ“₯ 190K / month Β· πŸ“¦ 110 Β· ⏱️ 02.11.2023): +- [PyPi](https://pypi.org/project/ta) (πŸ“₯ 160K / month Β· πŸ“¦ 110 Β· ⏱️ 02.11.2023): ``` pip install ta ``` @@ -3564,66 +3549,66 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te conda install -c conda-forge ta ```
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Alpha Vantage (πŸ₯ˆ29 Β· ⭐ 4.2K) - A python wrapper for Alpha Vantage API for financial data. MIT +
ffn (πŸ₯ˆ29 Β· ⭐ 2K) - ffn - a financial function library for Python. MIT -- [GitHub](https://github.com/RomelTorres/alpha_vantage) (πŸ‘¨β€πŸ’» 44 Β· πŸ”€ 740 Β· πŸ“‹ 290 - 0% open Β· ⏱️ 18.07.2024): +- [GitHub](https://github.com/pmorissette/ffn) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 290 Β· πŸ“¦ 500 Β· πŸ“‹ 130 - 17% open Β· ⏱️ 01.10.2024): ``` - git clone https://github.com/RomelTorres/alpha_vantage + git clone https://github.com/pmorissette/ffn ``` -- [PyPi](https://pypi.org/project/alpha_vantage) (πŸ“₯ 39K / month Β· πŸ“¦ 35 Β· ⏱️ 18.07.2024): +- [PyPi](https://pypi.org/project/ffn) (πŸ“₯ 19K / month Β· πŸ“¦ 18 Β· ⏱️ 05.08.2024): ``` - pip install alpha_vantage + pip install ffn ``` -- [Conda](https://anaconda.org/conda-forge/alpha_vantage) (πŸ“₯ 7.5K Β· ⏱️ 09.08.2024): +- [Conda](https://anaconda.org/conda-forge/ffn) (πŸ“₯ 13K Β· ⏱️ 06.08.2024): ``` - conda install -c conda-forge alpha_vantage + conda install -c conda-forge ffn ```
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ffn (πŸ₯ˆ29 Β· ⭐ 2K) - ffn - a financial function library for Python. MIT +
Alpha Vantage (πŸ₯ˆ28 Β· ⭐ 4.3K) - A python wrapper for Alpha Vantage API for financial data. MIT -- [GitHub](https://github.com/pmorissette/ffn) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 290 Β· πŸ“¦ 490 Β· πŸ“‹ 130 - 17% open Β· ⏱️ 01.10.2024): +- [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/pmorissette/ffn + git clone https://github.com/RomelTorres/alpha_vantage ``` -- [PyPi](https://pypi.org/project/ffn) (πŸ“₯ 17K / month Β· πŸ“¦ 18 Β· ⏱️ 05.08.2024): +- [PyPi](https://pypi.org/project/alpha_vantage) (πŸ“₯ 44K / month Β· πŸ“¦ 35 Β· ⏱️ 18.07.2024): ``` - pip install ffn + pip install alpha_vantage ``` -- [Conda](https://anaconda.org/conda-forge/ffn) (πŸ“₯ 12K Β· ⏱️ 06.08.2024): +- [Conda](https://anaconda.org/conda-forge/alpha_vantage) (πŸ“₯ 7.6K Β· ⏱️ 09.08.2024): ``` - conda install -c conda-forge ffn + conda install -c conda-forge alpha_vantage ```
IB-insync (πŸ₯‰27 Β· ⭐ 2.8K Β· πŸ’€) - Python sync/async framework for Interactive Brokers API. BSD-2 -- [GitHub](https://github.com/erdewit/ib_insync) (πŸ‘¨β€πŸ’» 36 Β· πŸ”€ 750 Β· πŸ“‹ 590 - 3% open Β· ⏱️ 14.03.2024): +- [GitHub](https://github.com/erdewit/ib_insync) (πŸ‘¨β€πŸ’» 36 Β· πŸ”€ 760 Β· πŸ“‹ 590 - 3% open Β· ⏱️ 14.03.2024): ``` git clone https://github.com/erdewit/ib_insync ``` -- [PyPi](https://pypi.org/project/ib_insync) (πŸ“₯ 53K / month Β· πŸ“¦ 44 Β· ⏱️ 21.11.2022): +- [PyPi](https://pypi.org/project/ib_insync) (πŸ“₯ 49K / month Β· πŸ“¦ 44 Β· ⏱️ 21.11.2022): ``` pip install ib_insync ``` -- [Conda](https://anaconda.org/conda-forge/ib-insync) (πŸ“₯ 47K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/ib-insync) (πŸ“₯ 48K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge ib-insync ```
TensorTrade (πŸ₯‰26 Β· ⭐ 4.5K) - An open source reinforcement learning framework for training,.. Apache-2 -- [GitHub](https://github.com/tensortrade-org/tensortrade) (πŸ‘¨β€πŸ’» 61 Β· πŸ”€ 980 Β· πŸ“¦ 62 Β· πŸ“‹ 250 - 20% open Β· ⏱️ 09.06.2024): +- [GitHub](https://github.com/tensortrade-org/tensortrade) (πŸ‘¨β€πŸ’» 61 Β· πŸ”€ 1K Β· πŸ“¦ 64 Β· πŸ“‹ 260 - 20% open Β· ⏱️ 09.06.2024): ``` git clone https://github.com/tensortrade-org/tensortrade ``` -- [PyPi](https://pypi.org/project/tensortrade) (πŸ“₯ 1.3K / month Β· πŸ“¦ 1 Β· ⏱️ 10.05.2021): +- [PyPi](https://pypi.org/project/tensortrade) (πŸ“₯ 2K / month Β· πŸ“¦ 1 Β· ⏱️ 10.05.2021): ``` pip install tensortrade ``` -- [Conda](https://anaconda.org/conda-forge/tensortrade) (πŸ“₯ 4K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/tensortrade) (πŸ“₯ 4.1K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge tensortrade ``` @@ -3635,19 +3620,19 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te ``` git clone https://github.com/jealous/stockstats ``` -- [PyPi](https://pypi.org/project/stockstats) (πŸ“₯ 8.9K / month Β· πŸ“¦ 11 Β· ⏱️ 30.07.2023): +- [PyPi](https://pypi.org/project/stockstats) (πŸ“₯ 9.5K / month Β· πŸ“¦ 11 Β· ⏱️ 30.07.2023): ``` pip install stockstats ```
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finmarketpy (πŸ₯‰22 Β· ⭐ 3.4K) - Python library for backtesting trading strategies & analyzing.. Apache-2 +
finmarketpy (πŸ₯‰23 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“₯ 56 Β· πŸ“¦ 15 Β· πŸ“‹ 28 - 85% open Β· ⏱️ 19.05.2024): +- [GitHub](https://github.com/cuemacro/finmarketpy) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 490 Β· πŸ“₯ 56 Β· πŸ“¦ 16 Β· πŸ“‹ 28 - 85% open Β· ⏱️ 19.05.2024): ``` git clone https://github.com/cuemacro/finmarketpy ``` -- [PyPi](https://pypi.org/project/finmarketpy) (πŸ“₯ 930 / month Β· ⏱️ 19.05.2024): +- [PyPi](https://pypi.org/project/finmarketpy) (πŸ“₯ 1.5K / month Β· ⏱️ 19.05.2024): ``` pip install finmarketpy ``` @@ -3655,18 +3640,18 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te
Show 15 hidden projects... - zipline (πŸ₯‡32 Β· ⭐ 18K Β· πŸ’€) - Zipline, a Pythonic Algorithmic Trading Library. Apache-2 -- pyfolio (πŸ₯ˆ30 Β· ⭐ 5.7K Β· πŸ’€) - Portfolio and risk analytics in Python. Apache-2 -- arch (πŸ₯ˆ30 Β· ⭐ 1.3K) - ARCH models in Python. ❗Unlicensed +- pyfolio (πŸ₯‡31 Β· ⭐ 5.7K 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· ⭐ 14K Β· πŸ’€) - Python Backtesting library for trading strategies. ❗️GPL-3.0 - Alphalens (πŸ₯‰27 Β· ⭐ 3.3K Β· πŸ’€) - Performance analysis of predictive (alpha) stock factors. Apache-2 - Enigma Catalyst (πŸ₯‰27 Β· ⭐ 2.5K Β· πŸ’€) - An Algorithmic Trading Library for Crypto-Assets in.. Apache-2 - empyrical (πŸ₯‰27 Β· ⭐ 1.3K Β· πŸ’€) - Common financial risk and performance metrics. Used by.. Apache-2 - PyAlgoTrade (πŸ₯‰24 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 -- Backtesting.py (πŸ₯‰23 Β· ⭐ 5.4K Β· πŸ’€) - Backtest trading strategies in Python. ❗️AGPL-3.0 +- Backtesting.py (πŸ₯‰23 Β· ⭐ 5.5K Β· πŸ’€) - Backtest trading strategies in Python. ❗️AGPL-3.0 - FinQuant (πŸ₯‰23 Β· ⭐ 1.4K Β· πŸ’€) - A program for financial portfolio management, analysis and.. MIT - Crypto Signals (πŸ₯‰22 Β· ⭐ 4.9K Β· πŸ’€) - Github.com/CryptoSignal - Trading & Technical Analysis Bot -.. MIT -- tf-quant-finance (πŸ₯‰21 Β· ⭐ 4.5K Β· πŸ’€) - High-performance TensorFlow library for quantitative.. Apache-2 +- tf-quant-finance (πŸ₯‰22 Β· ⭐ 4.5K 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₯‰9 Β· ⭐ 150 Β· πŸ’€) - Python package to generate stock portfolios. ❗️GPL-3.0
@@ -3678,30 +3663,30 @@ _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· ⭐ 7.8K) - A unified framework for machine learning with time series. BSD-3 +
sktime (πŸ₯‡39 Β· ⭐ 7.9K) - A unified framework for machine learning with time series. BSD-3 -- [GitHub](https://github.com/sktime/sktime) (πŸ‘¨β€πŸ’» 400 Β· πŸ”€ 1.3K Β· πŸ“₯ 100 Β· πŸ“¦ 3.3K Β· πŸ“‹ 2.5K - 37% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/sktime/sktime) (πŸ‘¨β€πŸ’» 400 Β· πŸ”€ 1.4K Β· πŸ“₯ 100 Β· πŸ“¦ 3.4K Β· πŸ“‹ 2.6K - 37% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/alan-turing-institute/sktime ``` -- [PyPi](https://pypi.org/project/sktime) (πŸ“₯ 760K / month Β· πŸ“¦ 130 Β· ⏱️ 26.09.2024): +- [PyPi](https://pypi.org/project/sktime) (πŸ“₯ 790K / month Β· πŸ“¦ 130 Β· ⏱️ 19.10.2024): ``` pip install sktime ``` -- [Conda](https://anaconda.org/conda-forge/sktime-all-extras) (πŸ“₯ 1M Β· ⏱️ 25.09.2024): +- [Conda](https://anaconda.org/conda-forge/sktime-all-extras) (πŸ“₯ 1M Β· ⏱️ 19.10.2024): ``` conda install -c conda-forge sktime-all-extras ```
Prophet (πŸ₯‡35 Β· ⭐ 18K) - Tool for producing high quality forecasts for time series data that has.. MIT -- [GitHub](https://github.com/facebook/prophet) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 4.5K Β· πŸ“₯ 2.8K Β· πŸ“¦ 21 Β· πŸ“‹ 2.2K - 19% open Β· ⏱️ 02.10.2024): +- [GitHub](https://github.com/facebook/prophet) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 4.5K Β· πŸ“₯ 2.8K Β· πŸ“¦ 21 Β· πŸ“‹ 2.2K - 19% open Β· ⏱️ 20.10.2024): ``` git clone https://github.com/facebook/prophet ``` -- [PyPi](https://pypi.org/project/fbprophet) (πŸ“₯ 250K / month Β· πŸ“¦ 91 Β· ⏱️ 05.09.2020): +- [PyPi](https://pypi.org/project/fbprophet) (πŸ“₯ 230K / month Β· πŸ“¦ 91 Β· ⏱️ 05.09.2020): ``` pip install fbprophet ``` @@ -3712,28 +3697,44 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l
StatsForecast (πŸ₯‡34 Β· ⭐ 3.9K) - Lightning fast forecasting with statistical and econometric.. Apache-2 -- [GitHub](https://github.com/Nixtla/statsforecast) (πŸ‘¨β€πŸ’» 46 Β· πŸ”€ 270 Β· πŸ“¦ 1.1K Β· πŸ“‹ 340 - 29% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/Nixtla/statsforecast) (πŸ‘¨β€πŸ’» 46 Β· πŸ”€ 280 Β· πŸ“¦ 1.2K Β· πŸ“‹ 340 - 29% open Β· ⏱️ 21.10.2024): ``` git clone https://github.com/Nixtla/statsforecast ``` -- [PyPi](https://pypi.org/project/statsforecast) (πŸ“₯ 670K / month Β· πŸ“¦ 57 Β· ⏱️ 19.09.2024): +- [PyPi](https://pypi.org/project/statsforecast) (πŸ“₯ 710K / month Β· πŸ“¦ 57 Β· ⏱️ 19.09.2024): ``` pip install statsforecast ``` -- [Conda](https://anaconda.org/conda-forge/statsforecast) (πŸ“₯ 98K Β· ⏱️ 23.09.2024): +- [Conda](https://anaconda.org/conda-forge/statsforecast) (πŸ“₯ 100K Β· ⏱️ 23.09.2024): ``` conda install -c conda-forge statsforecast ```
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STUMPY (πŸ₯ˆ33 Β· ⭐ 3.6K) - STUMPY is a powerful and scalable Python library for modern time series.. BSD-3 +
pytorch-forecasting (πŸ₯ˆ32 Β· ⭐ 4K) - Time series forecasting with PyTorch. MIT + +- [GitHub](https://github.com/sktime/pytorch-forecasting) (πŸ‘¨β€πŸ’» 54 Β· πŸ”€ 620 Β· πŸ“¦ 440 Β· πŸ“‹ 780 - 60% open Β· ⏱️ 22.10.2024): + + ``` + git clone https://github.com/jdb78/pytorch-forecasting + ``` +- [PyPi](https://pypi.org/project/pytorch-forecasting) (πŸ“₯ 56K / month Β· πŸ“¦ 22 Β· ⏱️ 09.09.2024): + ``` + pip install pytorch-forecasting + ``` +- [Conda](https://anaconda.org/conda-forge/pytorch-forecasting) (πŸ“₯ 66K Β· ⏱️ 16.06.2023): + ``` + conda install -c conda-forge pytorch-forecasting + ``` +
+
STUMPY (πŸ₯ˆ32 Β· ⭐ 3.7K) - STUMPY is a powerful and scalable Python library for modern time series.. BSD-3 -- [GitHub](https://github.com/TDAmeritrade/stumpy) (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 320 Β· πŸ“¦ 900 Β· πŸ“‹ 510 - 12% open Β· ⏱️ 16.09.2024): +- [GitHub](https://github.com/TDAmeritrade/stumpy) (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 320 Β· πŸ“¦ 910 Β· πŸ“‹ 520 - 12% open Β· ⏱️ 14.10.2024): ``` git clone https://github.com/TDAmeritrade/stumpy ``` -- [PyPi](https://pypi.org/project/stumpy) (πŸ“₯ 270K / month Β· πŸ“¦ 30 Β· ⏱️ 09.07.2024): +- [PyPi](https://pypi.org/project/stumpy) (πŸ“₯ 260K / month Β· πŸ“¦ 30 Β· ⏱️ 09.07.2024): ``` pip install stumpy ``` @@ -3742,82 +3743,66 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l conda install -c conda-forge stumpy ```
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tsfresh (πŸ₯ˆ32 Β· ⭐ 8.4K) - Automatic extraction of relevant features from time series:. MIT +
NeuralForecast (πŸ₯ˆ32 Β· ⭐ 3K) - Scalable and user friendly neural forecasting algorithms. Apache-2 -- [GitHub](https://github.com/blue-yonder/tsfresh) (πŸ‘¨β€πŸ’» 97 Β· πŸ”€ 1.2K Β· πŸ“¦ 21 Β· πŸ“‹ 540 - 12% open Β· ⏱️ 03.08.2024): +- [GitHub](https://github.com/Nixtla/neuralforecast) (πŸ‘¨β€πŸ’» 48 Β· πŸ”€ 350 Β· πŸ“¦ 240 Β· πŸ“‹ 560 - 20% open Β· ⏱️ 22.10.2024): ``` - git clone https://github.com/blue-yonder/tsfresh + git clone https://github.com/Nixtla/neuralforecast ``` -- [PyPi](https://pypi.org/project/tsfresh) (πŸ“₯ 240K / month Β· πŸ“¦ 93 Β· ⏱️ 03.08.2024): +- [PyPi](https://pypi.org/project/neuralforecast) (πŸ“₯ 66K / month Β· πŸ“¦ 17 Β· ⏱️ 20.09.2024): ``` - pip install tsfresh + pip install neuralforecast ``` -- [Conda](https://anaconda.org/conda-forge/tsfresh) (πŸ“₯ 1.4M Β· ⏱️ 04.08.2024): +- [Conda](https://anaconda.org/conda-forge/neuralforecast) (πŸ“₯ 24K Β· ⏱️ 20.09.2024): ``` - conda install -c conda-forge tsfresh + conda install -c conda-forge neuralforecast ```
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pytorch-forecasting (πŸ₯ˆ32 Β· ⭐ 3.9K) - Time series forecasting with PyTorch. MIT +
tsfresh (πŸ₯ˆ31 Β· ⭐ 8.4K) - Automatic extraction of relevant features from time series:. MIT -- [GitHub](https://github.com/sktime/pytorch-forecasting) (πŸ‘¨β€πŸ’» 53 Β· πŸ”€ 620 Β· πŸ“¦ 440 Β· πŸ“‹ 780 - 60% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/blue-yonder/tsfresh) (πŸ‘¨β€πŸ’» 97 Β· πŸ”€ 1.2K Β· πŸ“¦ 21 Β· πŸ“‹ 540 - 12% open Β· ⏱️ 03.08.2024): ``` - git clone https://github.com/jdb78/pytorch-forecasting + git clone https://github.com/blue-yonder/tsfresh ``` -- [PyPi](https://pypi.org/project/pytorch-forecasting) (πŸ“₯ 55K / month Β· πŸ“¦ 22 Β· ⏱️ 09.09.2024): +- [PyPi](https://pypi.org/project/tsfresh) (πŸ“₯ 240K / month Β· πŸ“¦ 93 Β· ⏱️ 03.08.2024): ``` - pip install pytorch-forecasting + pip install tsfresh ``` -- [Conda](https://anaconda.org/conda-forge/pytorch-forecasting) (πŸ“₯ 65K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/tsfresh) (πŸ“₯ 1.4M Β· ⏱️ 04.08.2024): ``` - conda install -c conda-forge pytorch-forecasting + conda install -c conda-forge tsfresh ```
Darts (πŸ₯ˆ31 Β· ⭐ 8K) - A python library for user-friendly forecasting and anomaly detection on.. Apache-2 -- [GitHub](https://github.com/unit8co/darts) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 870 Β· πŸ“‹ 1.6K - 15% open Β· ⏱️ 28.09.2024): +- [GitHub](https://github.com/unit8co/darts) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 870 Β· πŸ“‹ 1.6K - 15% open Β· ⏱️ 13.10.2024): ``` git clone https://github.com/unit8co/darts ``` -- [PyPi](https://pypi.org/project/u8darts) (πŸ“₯ 74K / month Β· πŸ“¦ 10 Β· ⏱️ 19.06.2024): +- [PyPi](https://pypi.org/project/u8darts) (πŸ“₯ 67K / month Β· πŸ“¦ 10 Β· ⏱️ 13.10.2024): ``` pip install u8darts ``` -- [Conda](https://anaconda.org/conda-forge/u8darts-all) (πŸ“₯ 59K Β· ⏱️ 21.06.2024): +- [Conda](https://anaconda.org/conda-forge/u8darts-all) (πŸ“₯ 60K Β· ⏱️ 13.10.2024): ``` conda install -c conda-forge u8darts-all ``` -- [Docker Hub](https://hub.docker.com/r/unit8/darts) (πŸ“₯ 700 Β· ⏱️ 17.04.2024): +- [Docker Hub](https://hub.docker.com/r/unit8/darts) (πŸ“₯ 790 Β· ⏱️ 17.04.2024): ``` docker pull unit8/darts ```
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NeuralForecast (πŸ₯ˆ31 Β· ⭐ 3K) - Scalable and user friendly neural forecasting algorithms. Apache-2 - -- [GitHub](https://github.com/Nixtla/neuralforecast) (πŸ‘¨β€πŸ’» 48 Β· πŸ”€ 340 Β· πŸ“¦ 220 Β· πŸ“‹ 540 - 20% open Β· ⏱️ 10.10.2024): - - ``` - git clone https://github.com/Nixtla/neuralforecast - ``` -- [PyPi](https://pypi.org/project/neuralforecast) (πŸ“₯ 49K / month Β· πŸ“¦ 17 Β· ⏱️ 20.09.2024): - ``` - pip install neuralforecast - ``` -- [Conda](https://anaconda.org/conda-forge/neuralforecast) (πŸ“₯ 23K Β· ⏱️ 20.09.2024): - ``` - conda install -c conda-forge neuralforecast - ``` -
tslearn (πŸ₯ˆ31 Β· ⭐ 2.9K) - The machine learning toolkit for time series analysis in Python. BSD-2 -- [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): +- [GitHub](https://github.com/tslearn-team/tslearn) (πŸ‘¨β€πŸ’» 43 Β· πŸ”€ 340 Β· πŸ“¦ 1.5K Β· πŸ“‹ 330 - 40% open Β· ⏱️ 01.07.2024): ``` git clone https://github.com/tslearn-team/tslearn ``` -- [PyPi](https://pypi.org/project/tslearn) (πŸ“₯ 460K / month Β· πŸ“¦ 79 Β· ⏱️ 12.12.2023): +- [PyPi](https://pypi.org/project/tslearn) (πŸ“₯ 430K / month Β· πŸ“¦ 79 Β· ⏱️ 12.12.2023): ``` pip install tslearn ``` @@ -3828,7 +3813,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l
pmdarima (πŸ₯ˆ31 Β· ⭐ 1.6K) - A statistical library designed to fill the void in Pythons time series.. MIT -- [GitHub](https://github.com/alkaline-ml/pmdarima) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 230 Β· πŸ“¦ 9.4K Β· πŸ“‹ 340 - 18% open Β· ⏱️ 24.09.2024): +- [GitHub](https://github.com/alkaline-ml/pmdarima) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 230 Β· πŸ“¦ 9.6K Β· πŸ“‹ 340 - 18% open Β· ⏱️ 24.09.2024): ``` git clone https://github.com/alkaline-ml/pmdarima @@ -3842,26 +3827,26 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l conda install -c conda-forge pmdarima ```
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skforecast (πŸ₯ˆ30 Β· ⭐ 1.1K) - Time series forecasting with machine learning 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’» 14 Β· πŸ”€ 130 Β· πŸ“¦ 330 Β· πŸ“‹ 170 - 13% open Β· ⏱️ 13.08.2024): +- [GitHub](https://github.com/skforecast/skforecast) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 130 Β· πŸ“¦ 340 Β· πŸ“‹ 170 - 13% open Β· ⏱️ 13.08.2024): ``` git clone https://github.com/JoaquinAmatRodrigo/skforecast ``` -- [PyPi](https://pypi.org/project/skforecast) (πŸ“₯ 80K / month Β· πŸ“¦ 15 Β· ⏱️ 01.08.2024): +- [PyPi](https://pypi.org/project/skforecast) (πŸ“₯ 90K / month Β· πŸ“¦ 15 Β· ⏱️ 01.08.2024): ``` pip install skforecast ```
GluonTS (πŸ₯ˆ29 Β· ⭐ 4.6K) - Probabilistic time series modeling in Python. Apache-2 -- [GitHub](https://github.com/awslabs/gluonts) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 740 Β· πŸ“‹ 960 - 33% open Β· ⏱️ 25.07.2024): +- [GitHub](https://github.com/awslabs/gluonts) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 750 Β· πŸ“‹ 960 - 34% open Β· ⏱️ 17.10.2024): ``` git clone https://github.com/awslabs/gluon-ts ``` -- [PyPi](https://pypi.org/project/gluonts) (πŸ“₯ 650K / month Β· πŸ“¦ 31 Β· ⏱️ 03.06.2024): +- [PyPi](https://pypi.org/project/gluonts) (πŸ“₯ 690K / month Β· πŸ“¦ 33 Β· ⏱️ 21.10.2024): ``` pip install gluonts ``` @@ -3870,38 +3855,38 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l conda install -c anaconda gluonts ```
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NeuralProphet (πŸ₯ˆ29 Β· ⭐ 3.8K) - NeuralProphet: A simple forecasting package. MIT +
NeuralProphet (πŸ₯ˆ29 Β· ⭐ 3.9K) - NeuralProphet: A simple forecasting package. MIT - [GitHub](https://github.com/ourownstory/neural_prophet) (πŸ‘¨β€πŸ’» 56 Β· πŸ”€ 470 Β· πŸ“‹ 560 - 10% open Β· ⏱️ 13.09.2024): ``` git clone https://github.com/ourownstory/neural_prophet ``` -- [PyPi](https://pypi.org/project/neuralprophet) (πŸ“₯ 140K / month Β· πŸ“¦ 8 Β· ⏱️ 26.06.2024): +- [PyPi](https://pypi.org/project/neuralprophet) (πŸ“₯ 120K / month Β· πŸ“¦ 8 Β· ⏱️ 26.06.2024): ``` pip install neuralprophet ```
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TSFEL (πŸ₯‰24 Β· ⭐ 920) - An intuitive library to extract features from time series. BSD-3 +
TSFEL (πŸ₯‰24 Β· ⭐ 930) - An intuitive library to extract features from time series. BSD-3 -- [GitHub](https://github.com/fraunhoferportugal/tsfel) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 140 Β· πŸ“¦ 150 Β· πŸ“‹ 76 - 6% open Β· ⏱️ 12.09.2024): +- [GitHub](https://github.com/fraunhoferportugal/tsfel) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 140 Β· πŸ“¦ 160 Β· πŸ“‹ 78 - 8% open Β· ⏱️ 17.10.2024): ``` git clone https://github.com/fraunhoferportugal/tsfel ``` -- [PyPi](https://pypi.org/project/tsfel) (πŸ“₯ 21K / month Β· πŸ“¦ 7 Β· ⏱️ 12.09.2024): +- [PyPi](https://pypi.org/project/tsfel) (πŸ“₯ 16K / month Β· πŸ“¦ 7 Β· ⏱️ 12.09.2024): ``` pip install tsfel ```
uber/orbit (πŸ₯‰23 Β· ⭐ 1.9K) - A Python package for Bayesian forecasting with object-oriented.. Apache-2 -- [GitHub](https://github.com/uber/orbit) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 140 Β· πŸ“¦ 63 Β· πŸ“‹ 400 - 12% open Β· ⏱️ 10.07.2024): +- [GitHub](https://github.com/uber/orbit) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 140 Β· πŸ“¦ 64 Β· πŸ“‹ 400 - 12% open Β· ⏱️ 10.07.2024): ``` git clone https://github.com/uber/orbit ``` -- [PyPi](https://pypi.org/project/orbit-ml) (πŸ“₯ 14K / month Β· πŸ“¦ 1 Β· ⏱️ 01.04.2024): +- [PyPi](https://pypi.org/project/orbit-ml) (πŸ“₯ 19K / month Β· πŸ“¦ 1 Β· ⏱️ 01.04.2024): ``` pip install orbit-ml ``` @@ -3917,7 +3902,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l ``` git clone https://github.com/wwrechard/pydlm ``` -- [PyPi](https://pypi.org/project/pydlm) (πŸ“₯ 27K / month Β· πŸ“¦ 2 Β· ⏱️ 13.08.2024): +- [PyPi](https://pypi.org/project/pydlm) (πŸ“₯ 28K / month Β· πŸ“¦ 2 Β· ⏱️ 13.08.2024): ``` pip install pydlm ``` @@ -3929,7 +3914,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l ``` git clone https://github.com/predict-idlab/tsflex ``` -- [PyPi](https://pypi.org/project/tsflex) (πŸ“₯ 1.5K / month Β· πŸ“¦ 2 Β· ⏱️ 06.09.2024): +- [PyPi](https://pypi.org/project/tsflex) (πŸ“₯ 2.1K / month Β· πŸ“¦ 2 Β· ⏱️ 06.09.2024): ``` pip install tsflex ``` @@ -3945,7 +3930,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l ``` git clone https://github.com/linkedin/greykite ``` -- [PyPi](https://pypi.org/project/greykite) (πŸ“₯ 6.8K / month Β· ⏱️ 12.01.2024): +- [PyPi](https://pypi.org/project/greykite) (πŸ“₯ 7.9K / month Β· ⏱️ 12.01.2024): ``` pip install greykite ``` @@ -3957,7 +3942,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l ``` git clone https://github.com/AutoViML/Auto_TS ``` -- [PyPi](https://pypi.org/project/auto-ts) (πŸ“₯ 12K / month Β· ⏱️ 05.05.2024): +- [PyPi](https://pypi.org/project/auto-ts) (πŸ“₯ 18K / month Β· ⏱️ 05.05.2024): ``` pip install auto-ts ``` @@ -3967,14 +3952,14 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l - Streamz (πŸ₯‰27 Β· ⭐ 1.2K Β· πŸ’€) - Real-time stream processing for python. BSD-3 - pyts (πŸ₯‰26 Β· ⭐ 1.8K Β· πŸ’€) - A Python package for time series classification. 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· ⭐ 490 Β· πŸ’€) - Module for statistical learning, with a particular emphasis on time-.. BSD-3 -- luminol (πŸ₯‰21 Β· ⭐ 1.2K Β· πŸ’€) - Anomaly Detection and Correlation library. Apache-2 - ADTK (πŸ₯‰21 Β· ⭐ 1.1K Β· πŸ’€) - A Python toolkit for rule-based/unsupervised anomaly detection in.. MPL-2.0 - seglearn (πŸ₯‰21 Β· ⭐ 570 Β· πŸ’€) - Python module for machine learning time series:. BSD-3 - matrixprofile-ts (πŸ₯‰19 Β· ⭐ 730 Β· πŸ’€) - A Python library for detecting patterns and anomalies.. Apache-2 - atspy (πŸ₯‰16 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 -- tslumen (πŸ₯‰8 Β· ⭐ 66 Β· πŸ’€) - A library for Time Series EDA (exploratory data analysis). Apache-2 +- 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

@@ -3986,7 +3971,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic
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’» 380 Β· πŸ”€ 1.3K Β· πŸ“¦ 4.5K Β· πŸ“‹ 4.9K - 10% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/mne-tools/mne-python) (πŸ‘¨β€πŸ’» 380 Β· πŸ”€ 1.3K Β· πŸ“¦ 4.5K Β· πŸ“‹ 4.9K - 10% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/mne-tools/mne-python @@ -4000,25 +3985,25 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic conda install -c conda-forge mne ```
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MONAI (πŸ₯‡36 Β· ⭐ 5.7K) - AI Toolkit for Healthcare Imaging. Apache-2 +
MONAI (πŸ₯‡36 Β· ⭐ 5.8K) - AI Toolkit for Healthcare Imaging. Apache-2 -- [GitHub](https://github.com/Project-MONAI/MONAI) (πŸ‘¨β€πŸ’» 200 Β· πŸ”€ 1.1K Β· πŸ“¦ 2.9K Β· πŸ“‹ 3.1K - 11% open Β· ⏱️ 30.09.2024): +- [GitHub](https://github.com/Project-MONAI/MONAI) (πŸ‘¨β€πŸ’» 210 Β· πŸ”€ 1.1K Β· πŸ“¦ 3K Β· πŸ“‹ 3.1K - 11% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/Project-MONAI/MONAI ``` -- [PyPi](https://pypi.org/project/monai) (πŸ“₯ 150K / month Β· πŸ“¦ 120 Β· ⏱️ 30.09.2024): +- [PyPi](https://pypi.org/project/monai) (πŸ“₯ 160K / month Β· πŸ“¦ 120 Β· ⏱️ 16.10.2024): ``` pip install monai ``` -- [Conda](https://anaconda.org/conda-forge/monai) (πŸ“₯ 30K Β· ⏱️ 26.06.2024): +- [Conda](https://anaconda.org/conda-forge/monai) (πŸ“₯ 31K Β· ⏱️ 17.10.2024): ``` conda install -c conda-forge monai ```
Nilearn (πŸ₯‡36 Β· ⭐ 1.2K) - Machine learning for NeuroImaging in Python. BSD-3 -- [GitHub](https://github.com/nilearn/nilearn) (πŸ‘¨β€πŸ’» 240 Β· πŸ”€ 600 Β· πŸ“₯ 240 Β· πŸ“¦ 3.5K Β· πŸ“‹ 2.1K - 14% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/nilearn/nilearn) (πŸ‘¨β€πŸ’» 250 Β· πŸ”€ 600 Β· πŸ“₯ 240 Β· πŸ“¦ 3.5K Β· πŸ“‹ 2.1K - 13% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/nilearn/nilearn @@ -4034,32 +4019,32 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic
NiBabel (πŸ₯‡36 Β· ⭐ 650) - 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“¦ 22K Β· πŸ“‹ 540 - 23% open Β· ⏱️ 08.10.2024): +- [GitHub](https://github.com/nipy/nibabel) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 260 Β· πŸ“¦ 22K Β· πŸ“‹ 540 - 24% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/nipy/nibabel ``` -- [PyPi](https://pypi.org/project/nibabel) (πŸ“₯ 1.5M / month Β· πŸ“¦ 1.2K Β· ⏱️ 08.10.2024): +- [PyPi](https://pypi.org/project/nibabel) (πŸ“₯ 1.4M / month Β· πŸ“¦ 1.2K Β· ⏱️ 23.10.2024): ``` pip install nibabel ``` -- [Conda](https://anaconda.org/conda-forge/nibabel) (πŸ“₯ 780K Β· ⏱️ 08.10.2024): +- [Conda](https://anaconda.org/conda-forge/nibabel) (πŸ“₯ 780K Β· ⏱️ 23.10.2024): ``` conda install -c conda-forge nibabel ```
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NIPYPE (πŸ₯ˆ35 Β· ⭐ 750 Β· πŸ“ˆ) - Workflows and interfaces for neuroimaging packages. Apache-2 +
NIPYPE (πŸ₯ˆ35 Β· ⭐ 750) - Workflows and interfaces for neuroimaging packages. Apache-2 -- [GitHub](https://github.com/nipy/nipype) (πŸ‘¨β€πŸ’» 260 Β· πŸ”€ 510 Β· πŸ“¦ 5K Β· πŸ“‹ 1.4K - 29% open Β· ⏱️ 07.10.2024): +- [GitHub](https://github.com/nipy/nipype) (πŸ‘¨β€πŸ’» 260 Β· πŸ”€ 510 Β· πŸ“¦ 5.1K Β· πŸ“‹ 1.4K - 29% open Β· ⏱️ 16.10.2024): ``` git clone https://github.com/nipy/nipype ``` -- [PyPi](https://pypi.org/project/nipype) (πŸ“₯ 200K / month Β· πŸ“¦ 150 Β· ⏱️ 06.04.2023): +- [PyPi](https://pypi.org/project/nipype) (πŸ“₯ 190K / month Β· πŸ“¦ 150 Β· ⏱️ 06.04.2023): ``` pip install nipype ``` -- [Conda](https://anaconda.org/conda-forge/nipype) (πŸ“₯ 690K Β· ⏱️ 22.09.2023): +- [Conda](https://anaconda.org/conda-forge/nipype) (πŸ“₯ 700K Β· ⏱️ 22.09.2023): ``` conda install -c conda-forge nipype ``` @@ -4071,7 +4056,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic ``` git clone https://github.com/CamDavidsonPilon/lifelines ``` -- [PyPi](https://pypi.org/project/lifelines) (πŸ“₯ 1.2M / month Β· πŸ“¦ 150 Β· ⏱️ 26.06.2024): +- [PyPi](https://pypi.org/project/lifelines) (πŸ“₯ 1.9M / month Β· πŸ“¦ 150 Β· ⏱️ 26.06.2024): ``` pip install lifelines ``` @@ -4082,19 +4067,19 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic
Hail (πŸ₯ˆ32 Β· ⭐ 980) - Cloud-native genomic dataframes and batch computing. MIT -- [GitHub](https://github.com/hail-is/hail) (πŸ‘¨β€πŸ’» 95 Β· πŸ”€ 240 Β· πŸ“¦ 140 Β· πŸ“‹ 2.5K - 10% open Β· ⏱️ 08.10.2024): +- [GitHub](https://github.com/hail-is/hail) (πŸ‘¨β€πŸ’» 97 Β· πŸ”€ 240 Β· πŸ“¦ 150 Β· πŸ“‹ 2.5K - 10% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/hail-is/hail ``` -- [PyPi](https://pypi.org/project/hail) (πŸ“₯ 37K / month Β· πŸ“¦ 34 Β· ⏱️ 04.10.2024): +- [PyPi](https://pypi.org/project/hail) (πŸ“₯ 49K / month Β· πŸ“¦ 34 Β· ⏱️ 04.10.2024): ``` pip install hail ```
DeepVariant (πŸ₯‰24 Β· ⭐ 3.2K Β· πŸ’€) - DeepVariant is an analysis pipeline that uses a deep.. BSD-3 -- [GitHub](https://github.com/google/deepvariant) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 710 Β· πŸ“₯ 4.8K Β· πŸ“‹ 830 - 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“‹ 840 - 0% open Β· ⏱️ 18.03.2024): ``` git clone https://github.com/google/deepvariant @@ -4104,14 +4089,14 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic conda install -c bioconda deepvariant ```
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Brainiak (πŸ₯‰19 Β· ⭐ 330) - Brain Imaging Analysis Kit. Apache-2 +
Brainiak (πŸ₯‰20 Β· ⭐ 340) - Brain Imaging Analysis Kit. Apache-2 - [GitHub](https://github.com/brainiak/brainiak) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 130 Β· πŸ“‹ 220 - 38% open Β· ⏱️ 08.07.2024): ``` git clone https://github.com/brainiak/brainiak ``` -- [PyPi](https://pypi.org/project/brainiak) (πŸ“₯ 580 / month Β· ⏱️ 15.10.2020): +- [PyPi](https://pypi.org/project/brainiak) (πŸ“₯ 1.1K / month Β· ⏱️ 15.10.2020): ``` pip install brainiak ``` @@ -4123,12 +4108,12 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic
Show 10 hidden projects... - DIPY (πŸ₯ˆ32 Β· ⭐ 710) - DIPY is the paragon 3D/4D+ imaging library in Python. Contains.. ❗Unlicensed -- NIPY (πŸ₯‰27 Β· ⭐ 380 Β· πŸ“ˆ) - Neuroimaging in Python FMRI analysis package. ❗Unlicensed +- NIPY (πŸ₯‰27 Β· ⭐ 380) - Neuroimaging in Python FMRI analysis package. ❗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 +- MedPy (πŸ₯‰25 Β· ⭐ 580) - Medical image processing in Python. ❗️GPL-3.0 - DLTK (πŸ₯‰21 Β· ⭐ 1.4K Β· πŸ’€) - Deep Learning Toolkit for Medical Image Analysis. Apache-2 -- Glow (πŸ₯‰20 Β· ⭐ 270) - An open-source toolkit for large-scale genomic analysis. Apache-2 -- MedicalTorch (πŸ₯‰16 Β· ⭐ 840 Β· πŸ’€) - A medical imaging framework for Pytorch. Apache-2 +- Glow (πŸ₯‰21 Β· ⭐ 270) - An open-source toolkit for large-scale genomic analysis. Apache-2 +- MedicalTorch (πŸ₯‰16 Β· ⭐ 850 Β· πŸ’€) - A medical imaging framework for Pytorch. Apache-2 - DeepNeuro (πŸ₯‰15 Β· ⭐ 120 Β· πŸ’€) - A deep learning python package for neuroimaging data. Made by:. MIT - Medical Detection Toolkit (πŸ₯‰14 Β· ⭐ 1.3K Β· πŸ’€) - The Medical Detection Toolkit contains 2D + 3D.. Apache-2 - MedicalNet (πŸ₯‰12 Β· ⭐ 1.9K Β· πŸ’€) - Many studies have shown that the performance on deep learning is.. MIT @@ -4141,42 +4126,42 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic _Libraries for processing tabular and structured data._ -
miceforest (πŸ₯‡26 Β· ⭐ 340) - Multiple Imputation with LightGBM in Python. MIT +
miceforest (πŸ₯‡25 Β· ⭐ 350) - Multiple Imputation with LightGBM in Python. MIT -- [GitHub](https://github.com/AnotherSamWilson/miceforest) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 30 Β· πŸ“¦ 160 Β· πŸ“‹ 85 - 8% open Β· ⏱️ 02.08.2024): +- [GitHub](https://github.com/AnotherSamWilson/miceforest) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 30 Β· πŸ“¦ 170 Β· πŸ“‹ 85 - 8% open Β· ⏱️ 02.08.2024): ``` git clone https://github.com/AnotherSamWilson/miceforest ``` -- [PyPi](https://pypi.org/project/miceforest) (πŸ“₯ 65K / month Β· πŸ“¦ 9 Β· ⏱️ 02.08.2024): +- [PyPi](https://pypi.org/project/miceforest) (πŸ“₯ 66K / month Β· πŸ“¦ 9 Β· ⏱️ 02.08.2024): ``` pip install miceforest ``` -- [Conda](https://anaconda.org/conda-forge/miceforest) (πŸ“₯ 15K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/miceforest) (πŸ“₯ 16K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge miceforest ```
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pytorch_tabular (πŸ₯ˆ23 Β· ⭐ 1.3K) - A standard framework for modelling Deep Learning Models.. MIT +
pytorch_tabular (πŸ₯ˆ23 Β· ⭐ 1.4K) - A standard framework for modelling Deep Learning Models.. MIT -- [GitHub](https://github.com/manujosephv/pytorch_tabular) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 130 Β· πŸ“₯ 43 Β· πŸ“‹ 160 - 13% open Β· ⏱️ 17.09.2024): +- [GitHub](https://github.com/manujosephv/pytorch_tabular) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 140 Β· πŸ“₯ 43 Β· πŸ“‹ 160 - 12% open Β· ⏱️ 17.09.2024): ``` git clone https://github.com/manujosephv/pytorch_tabular ``` -- [PyPi](https://pypi.org/project/pytorch_tabular) (πŸ“₯ 3.9K / month Β· πŸ“¦ 3 Β· ⏱️ 15.01.2024): +- [PyPi](https://pypi.org/project/pytorch_tabular) (πŸ“₯ 4.1K / month Β· πŸ“¦ 3 Β· ⏱️ 15.01.2024): ``` pip install pytorch_tabular ```
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upgini (πŸ₯‰22 Β· ⭐ 310) - Data search & enrichment library for Machine Learning Easily find and add.. BSD-3 +
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“¦ 9 Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/upgini/upgini) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 25 Β· πŸ“¦ 9 Β· ⏱️ 21.10.2024): ``` git clone https://github.com/upgini/upgini ``` -- [PyPi](https://pypi.org/project/upgini) (πŸ“₯ 25K / month Β· ⏱️ 10.10.2024): +- [PyPi](https://pypi.org/project/upgini) (πŸ“₯ 40K / month Β· ⏱️ 21.10.2024): ``` pip install upgini ``` @@ -4188,7 +4173,7 @@ _Libraries for processing tabular and structured data._ ``` git clone https://github.com/carefree0910/carefree-learn ``` -- [PyPi](https://pypi.org/project/carefree-learn) (πŸ“₯ 3.2K / month Β· ⏱️ 09.01.2024): +- [PyPi](https://pypi.org/project/carefree-learn) (πŸ“₯ 5.8K / month Β· ⏱️ 09.01.2024): ``` pip install carefree-learn ``` @@ -4205,33 +4190,33 @@ _Libraries for processing tabular and structured data._ _Libraries for optical character recognition (OCR) and text extraction from images or videos._ -
PaddleOCR (πŸ₯‡41 Β· ⭐ 43K) - Awesome multilingual OCR toolkits based on PaddlePaddle.. Apache-2 +
PaddleOCR (πŸ₯‡40 Β· ⭐ 44K Β· πŸ“‰) - Awesome multilingual OCR toolkits based on PaddlePaddle.. Apache-2 -- [GitHub](https://github.com/PaddlePaddle/PaddleOCR) (πŸ‘¨β€πŸ’» 260 Β· πŸ”€ 7.7K Β· πŸ“₯ 420K Β· πŸ“¦ 3.4K Β· πŸ“‹ 9.3K - 1% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/PaddlePaddle/PaddleOCR) (πŸ‘¨β€πŸ’» 270 Β· πŸ”€ 7.8K Β· πŸ“₯ 520K Β· πŸ“¦ 3.5K Β· πŸ“‹ 9.4K - 1% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/PaddlePaddle/PaddleOCR ``` -- [PyPi](https://pypi.org/project/paddleocr) (πŸ“₯ 440K / month Β· πŸ“¦ 100 Β· ⏱️ 17.07.2024): +- [PyPi](https://pypi.org/project/paddleocr) (πŸ“₯ 390K / month Β· πŸ“¦ 110 Β· ⏱️ 22.10.2024): ``` pip install paddleocr ```
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EasyOCR (πŸ₯‡36 Β· ⭐ 24K) - Ready-to-use OCR with 80+ supported languages and all popular writing.. Apache-2 +
EasyOCR (πŸ₯‡35 Β· ⭐ 24K Β· πŸ“‰) - Ready-to-use OCR with 80+ supported languages and all popular.. Apache-2 -- [GitHub](https://github.com/JaidedAI/EasyOCR) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 3.1K Β· πŸ“₯ 15M Β· πŸ“¦ 8.7K Β· πŸ“‹ 1K - 41% open Β· ⏱️ 24.09.2024): +- [GitHub](https://github.com/JaidedAI/EasyOCR) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 3.1K Β· πŸ“₯ 15M Β· πŸ“¦ 8.9K Β· πŸ“‹ 1K - 41% open Β· ⏱️ 24.09.2024): ``` git clone https://github.com/JaidedAI/EasyOCR ``` -- [PyPi](https://pypi.org/project/easyocr) (πŸ“₯ 470K / month Β· πŸ“¦ 210 Β· ⏱️ 24.09.2024): +- [PyPi](https://pypi.org/project/easyocr) (πŸ“₯ 490K / month Β· πŸ“¦ 210 Β· ⏱️ 24.09.2024): ``` pip install easyocr ```
OCRmyPDF (πŸ₯ˆ34 Β· ⭐ 14K) - OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them.. MPL-2.0 -- [GitHub](https://github.com/ocrmypdf/OCRmyPDF) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 990 Β· πŸ“₯ 5.3K Β· πŸ“¦ 1K Β· πŸ“‹ 1.2K - 9% open Β· ⏱️ 15.09.2024): +- [GitHub](https://github.com/ocrmypdf/OCRmyPDF) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 1K Β· πŸ“₯ 5.4K Β· πŸ“¦ 1K Β· πŸ“‹ 1.2K - 9% open Β· ⏱️ 15.09.2024): ``` git clone https://github.com/ocrmypdf/OCRmyPDF @@ -4240,14 +4225,14 @@ _Libraries for optical character recognition (OCR) and text extraction from imag ``` pip install ocrmypdf ``` -- [Conda](https://anaconda.org/conda-forge/ocrmypdf) (πŸ“₯ 79K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/ocrmypdf) (πŸ“₯ 80K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge ocrmypdf ```
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Tesseract (πŸ₯ˆ31 Β· ⭐ 5.8K) - Python-tesseract is an optical character recognition (OCR) tool.. Apache-2 +
Tesseract (πŸ₯ˆ32 Β· ⭐ 5.8K) - Python-tesseract is an optical character recognition (OCR) tool.. Apache-2 -- [GitHub](https://github.com/madmaze/pytesseract) (πŸ‘¨β€πŸ’» 49 Β· πŸ”€ 710 Β· πŸ“‹ 370 - 4% open Β· ⏱️ 22.09.2024): +- [GitHub](https://github.com/madmaze/pytesseract) (πŸ‘¨β€πŸ’» 49 Β· πŸ”€ 710 Β· πŸ“‹ 370 - 4% open Β· ⏱️ 15.10.2024): ``` git clone https://github.com/madmaze/pytesseract @@ -4263,32 +4248,20 @@ _Libraries for optical character recognition (OCR) and text extraction from imag
tesserocr (πŸ₯ˆ30 Β· ⭐ 2K) - A Python wrapper for the tesseract-ocr API. MIT -- [GitHub](https://github.com/sirfz/tesserocr) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 250 Β· πŸ“₯ 580 Β· πŸ“¦ 1.1K Β· πŸ“‹ 280 - 18% open Β· ⏱️ 26.08.2024): +- [GitHub](https://github.com/sirfz/tesserocr) (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 250 Β· πŸ“₯ 600 Β· πŸ“¦ 1.1K Β· πŸ“‹ 280 - 18% open Β· ⏱️ 26.08.2024): ``` git clone https://github.com/sirfz/tesserocr ``` -- [PyPi](https://pypi.org/project/tesserocr) (πŸ“₯ 100K / month Β· πŸ“¦ 36 Β· ⏱️ 26.08.2024): +- [PyPi](https://pypi.org/project/tesserocr) (πŸ“₯ 110K / month Β· πŸ“¦ 36 Β· ⏱️ 26.08.2024): ``` pip install tesserocr ``` -- [Conda](https://anaconda.org/conda-forge/tesserocr) (πŸ“₯ 180K Β· ⏱️ 13.09.2024): +- [Conda](https://anaconda.org/conda-forge/tesserocr) (πŸ“₯ 190K Β· ⏱️ 13.09.2024): ``` conda install -c conda-forge tesserocr ```
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MMOCR (πŸ₯‰27 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”€ 740 Β· πŸ“¦ 170 Β· πŸ“‹ 930 - 20% open Β· ⏱️ 23.04.2024): - - ``` - git clone https://github.com/open-mmlab/mmocr - ``` -- [PyPi](https://pypi.org/project/mmocr) (πŸ“₯ 8.8K / month Β· πŸ“¦ 4 Β· ⏱️ 05.05.2022): - ``` - pip install mmocr - ``` -
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“₯ 1.7M Β· πŸ“¦ 570 Β· πŸ“‹ 210 - 46% open Β· ⏱️ 06.11.2023): @@ -4296,15 +4269,27 @@ _Libraries for optical character recognition (OCR) and text extraction from imag ``` git clone https://github.com/faustomorales/keras-ocr ``` -- [PyPi](https://pypi.org/project/keras-ocr) (πŸ“₯ 38K / month Β· πŸ“¦ 8 Β· ⏱️ 06.11.2023): +- [PyPi](https://pypi.org/project/keras-ocr) (πŸ“₯ 31K / month Β· πŸ“¦ 8 Β· ⏱️ 06.11.2023): ``` pip install keras-ocr ``` -- [Conda](https://anaconda.org/anaconda/keras-ocr) (πŸ“₯ 330 Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/anaconda/keras-ocr) (πŸ“₯ 340 Β· ⏱️ 16.06.2023): ``` conda install -c anaconda keras-ocr ```
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MMOCR (πŸ₯‰26 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”€ 740 Β· πŸ“¦ 170 Β· πŸ“‹ 930 - 20% open Β· ⏱️ 23.04.2024): + + ``` + git clone https://github.com/open-mmlab/mmocr + ``` +- [PyPi](https://pypi.org/project/mmocr) (πŸ“₯ 4.8K / month Β· πŸ“¦ 4 Β· ⏱️ 05.05.2022): + ``` + pip install mmocr + ``` +
attention-ocr (πŸ₯‰22 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“¦ 30 Β· πŸ“‹ 150 - 16% open Β· ⏱️ 20.10.2023): @@ -4312,7 +4297,7 @@ _Libraries for optical character recognition (OCR) and text extraction from imag ``` git clone https://github.com/emedvedev/attention-ocr ``` -- [PyPi](https://pypi.org/project/aocr) (πŸ“₯ 1.5K / month Β· ⏱️ 19.04.2019): +- [PyPi](https://pypi.org/project/aocr) (πŸ“₯ 3.5K / month Β· ⏱️ 19.04.2019): ``` pip install aocr ``` @@ -4332,7 +4317,7 @@ _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 ( ⭐ 3.6K) - Collection of data-container, dataframe, and pandas-.. +πŸ”— best-of-python - Data Containers ( ⭐ 3.7K) - Collection of data-container, dataframe, and pandas-..
@@ -4342,7 +4327,7 @@ _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 ( ⭐ 3.6K) - Collection of data-loading and -extraction libraries. +πŸ”— best-of-python - Data Extraction ( ⭐ 3.7K) - Collection of data-loading and -extraction libraries.
@@ -4362,7 +4347,7 @@ _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 ( ⭐ 3.6K) - Libraries for data batch- and stream-processing,.. +πŸ”— best-of-python - Data Pipelines ( ⭐ 3.7K) - Libraries for data batch- and stream-processing,..
@@ -4372,46 +4357,46 @@ _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₯‡45 Β· ⭐ 33K) - Ray is a unified framework for scaling AI and Python applications. Ray.. Apache-2 +
Ray (πŸ₯‡45 Β· ⭐ 34K) - Ray is an AI compute engine. Ray consists of a core distributed runtime.. Apache-2 -- [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· ⏱️ 10.10.2024): +- [GitHub](https://github.com/ray-project/ray) (πŸ‘¨β€πŸ’» 1.1K Β· πŸ”€ 5.7K Β· πŸ“₯ 240 Β· πŸ“¦ 19K Β· πŸ“‹ 19K - 21% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/ray-project/ray ``` -- [PyPi](https://pypi.org/project/ray) (πŸ“₯ 6.1M / month Β· πŸ“¦ 770 Β· ⏱️ 24.09.2024): +- [PyPi](https://pypi.org/project/ray) (πŸ“₯ 6.2M / month Β· πŸ“¦ 790 Β· ⏱️ 23.10.2024): ``` pip install ray ``` -- [Conda](https://anaconda.org/conda-forge/ray-tune) (πŸ“₯ 420K Β· ⏱️ 01.10.2024): +- [Conda](https://anaconda.org/conda-forge/ray-tune) (πŸ“₯ 440K Β· ⏱️ 23.10.2024): ``` conda install -c conda-forge ray-tune ```
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dask (πŸ₯‡44 Β· ⭐ 12K) - Parallel computing with task scheduling. BSD-3 +
dask (πŸ₯‡44 Β· ⭐ 13K) - Parallel computing with task scheduling. BSD-3 -- [GitHub](https://github.com/dask/dask) (πŸ‘¨β€πŸ’» 610 Β· πŸ”€ 1.7K Β· πŸ“¦ 65K Β· πŸ“‹ 5.4K - 20% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/dask/dask) (πŸ‘¨β€πŸ’» 610 Β· πŸ”€ 1.7K Β· πŸ“¦ 66K Β· πŸ“‹ 5.4K - 20% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/dask/dask ``` -- [PyPi](https://pypi.org/project/dask) (πŸ“₯ 13M / month Β· πŸ“¦ 2.4K Β· ⏱️ 28.09.2024): +- [PyPi](https://pypi.org/project/dask) (πŸ“₯ 13M / month Β· πŸ“¦ 2.4K Β· ⏱️ 17.10.2024): ``` pip install dask ``` -- [Conda](https://anaconda.org/conda-forge/dask) (πŸ“₯ 12M Β· ⏱️ 28.09.2024): +- [Conda](https://anaconda.org/conda-forge/dask) (πŸ“₯ 12M Β· ⏱️ 18.10.2024): ``` conda install -c conda-forge dask ```
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’» 340 Β· πŸ”€ 4.1K Β· πŸ“¦ 9K Β· πŸ“‹ 2.9K - 38% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/microsoft/DeepSpeed) (πŸ‘¨β€πŸ’» 350 Β· πŸ”€ 4.1K Β· πŸ“¦ 9.3K Β· πŸ“‹ 2.9K - 37% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/microsoft/DeepSpeed ``` -- [PyPi](https://pypi.org/project/deepspeed) (πŸ“₯ 510K / month Β· πŸ“¦ 210 Β· ⏱️ 09.10.2024): +- [PyPi](https://pypi.org/project/deepspeed) (πŸ“₯ 510K / month Β· πŸ“¦ 210 Β· ⏱️ 22.10.2024): ``` pip install deepspeed ``` @@ -4422,51 +4407,51 @@ _Libraries that provide capabilities to distribute and parallelize machine learn
dask.distributed (πŸ₯‡40 Β· ⭐ 1.6K) - A distributed task scheduler for Dask. BSD-3 -- [GitHub](https://github.com/dask/distributed) (πŸ‘¨β€πŸ’» 330 Β· πŸ”€ 720 Β· πŸ“¦ 37K Β· πŸ“‹ 3.9K - 39% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/dask/distributed) (πŸ‘¨β€πŸ’» 330 Β· πŸ”€ 720 Β· πŸ“¦ 37K Β· πŸ“‹ 3.9K - 39% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/dask/distributed ``` -- [PyPi](https://pypi.org/project/distributed) (πŸ“₯ 5.1M / month Β· πŸ“¦ 840 Β· ⏱️ 28.09.2024): +- [PyPi](https://pypi.org/project/distributed) (πŸ“₯ 4.9M / month Β· πŸ“¦ 850 Β· ⏱️ 17.10.2024): ``` pip install distributed ``` -- [Conda](https://anaconda.org/conda-forge/distributed) (πŸ“₯ 15M Β· ⏱️ 28.09.2024): +- [Conda](https://anaconda.org/conda-forge/distributed) (πŸ“₯ 15M Β· ⏱️ 17.10.2024): ``` conda install -c conda-forge distributed ```
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metrics (πŸ₯ˆ36 Β· ⭐ 2.1K) - Torchmetrics - Machine learning metrics for distributed,.. Apache-2 +
metrics (πŸ₯ˆ36 Β· ⭐ 2.1K) - Machine learning metrics for distributed, scalable PyTorch.. Apache-2 -- [GitHub](https://github.com/Lightning-AI/torchmetrics) (πŸ‘¨β€πŸ’» 250 Β· πŸ”€ 390 Β· πŸ“₯ 5.7K Β· πŸ“¦ 31K Β· πŸ“‹ 870 - 9% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/Lightning-AI/torchmetrics) (πŸ‘¨β€πŸ’» 250 Β· πŸ”€ 400 Β· πŸ“₯ 5.7K Β· πŸ“¦ 32K Β· πŸ“‹ 880 - 8% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/Lightning-AI/metrics ``` -- [PyPi](https://pypi.org/project/metrics) (πŸ“₯ 6K / month Β· πŸ“¦ 2 Β· ⏱️ 28.04.2018): +- [PyPi](https://pypi.org/project/metrics) (πŸ“₯ 6.1K / month Β· πŸ“¦ 2 Β· ⏱️ 28.04.2018): ``` pip install metrics ``` -- [Conda](https://anaconda.org/conda-forge/torchmetrics) (πŸ“₯ 1.6M Β· ⏱️ 14.09.2024): +- [Conda](https://anaconda.org/conda-forge/torchmetrics) (πŸ“₯ 1.6M Β· ⏱️ 24.10.2024): ``` conda install -c conda-forge torchmetrics ```
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horovod (πŸ₯ˆ35 Β· ⭐ 14K Β· πŸ“‰) - Distributed training framework for TensorFlow, Keras, PyTorch,.. Apache-2 +
horovod (πŸ₯ˆ35 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“‹ 2.3K - 17% open Β· ⏱️ 31.08.2024): ``` git clone https://github.com/horovod/horovod ``` -- [PyPi](https://pypi.org/project/horovod) (πŸ“₯ 130K / month Β· πŸ“¦ 33 Β· ⏱️ 12.06.2023): +- [PyPi](https://pypi.org/project/horovod) (πŸ“₯ 110K / month Β· πŸ“¦ 33 Β· ⏱️ 12.06.2023): ``` pip install horovod ```
H2O-3 (πŸ₯ˆ35 Β· ⭐ 6.9K) - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning.. Apache-2 -- [GitHub](https://github.com/h2oai/h2o-3) (πŸ‘¨β€πŸ’» 270 Β· πŸ”€ 2K Β· πŸ“¦ 21 Β· πŸ“‹ 9.5K - 29% open Β· ⏱️ 04.10.2024): +- [GitHub](https://github.com/h2oai/h2o-3) (πŸ‘¨β€πŸ’» 270 Β· πŸ”€ 2K Β· πŸ“¦ 21 Β· πŸ“‹ 9.5K - 29% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/h2oai/h2o-3 @@ -4478,20 +4463,20 @@ _Libraries that provide capabilities to distribute and parallelize machine learn
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”€ 4.3K Β· πŸ“¦ 420 Β· πŸ“‹ 1.7K - 24% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/hpcaitech/ColossalAI) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 4.3K Β· πŸ“¦ 430 Β· πŸ“‹ 1.7K - 25% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/hpcaitech/colossalai ```
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BigDL (πŸ₯ˆ33 Β· ⭐ 6.6K) - Accelerate local LLM inference and finetuning (LLaMA, Mistral,.. Apache-2 +
BigDL (πŸ₯ˆ34 Β· ⭐ 6.6K) - Accelerate local LLM inference and finetuning (LLaMA, Mistral,.. Apache-2 -- [GitHub](https://github.com/intel-analytics/ipex-llm) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 1.3K Β· πŸ“₯ 640 Β· πŸ“‹ 2.6K - 38% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/intel-analytics/ipex-llm) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 1.3K Β· πŸ“₯ 640 Β· πŸ“‹ 2.6K - 38% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/intel-analytics/BigDL ``` -- [PyPi](https://pypi.org/project/bigdl) (πŸ“₯ 54K / month Β· πŸ“¦ 2 Β· ⏱️ 24.03.2024): +- [PyPi](https://pypi.org/project/bigdl) (πŸ“₯ 120K / month Β· πŸ“¦ 2 Β· ⏱️ 24.03.2024): ``` pip install bigdl ``` @@ -4506,65 +4491,65 @@ _Libraries that provide capabilities to distribute and parallelize machine learn
FairScale (πŸ₯ˆ32 Β· ⭐ 3.2K) - PyTorch extensions for high performance and large scale training. BSD-3 -- [GitHub](https://github.com/facebookresearch/fairscale) (πŸ‘¨β€πŸ’» 75 Β· πŸ”€ 280 Β· πŸ“¦ 6.4K Β· πŸ“‹ 390 - 26% open Β· ⏱️ 03.05.2024): +- [GitHub](https://github.com/facebookresearch/fairscale) (πŸ‘¨β€πŸ’» 75 Β· πŸ”€ 280 Β· πŸ“¦ 6.5K Β· πŸ“‹ 390 - 26% open Β· ⏱️ 03.05.2024): ``` git clone https://github.com/facebookresearch/fairscale ``` -- [PyPi](https://pypi.org/project/fairscale) (πŸ“₯ 540K / month Β· πŸ“¦ 150 Β· ⏱️ 11.12.2022): +- [PyPi](https://pypi.org/project/fairscale) (πŸ“₯ 470K / month Β· πŸ“¦ 150 Β· ⏱️ 11.12.2022): ``` pip install fairscale ``` -- [Conda](https://anaconda.org/conda-forge/fairscale) (πŸ“₯ 310K Β· ⏱️ 28.11.2023): +- [Conda](https://anaconda.org/conda-forge/fairscale) (πŸ“₯ 320K Β· ⏱️ 28.11.2023): ``` conda install -c conda-forge fairscale ```
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mpi4py (πŸ₯ˆ31 Β· ⭐ 800) - Python bindings for MPI. BSD-3 +
mpi4py (πŸ₯ˆ30 Β· ⭐ 800) - Python bindings for MPI. BSD-3 -- [GitHub](https://github.com/mpi4py/mpi4py) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 120 Β· πŸ“₯ 27K Β· πŸ“‹ 180 - 3% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/mpi4py/mpi4py) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 120 Β· πŸ“₯ 28K Β· πŸ“‹ 180 - 4% open Β· ⏱️ 14.10.2024): ``` git clone https://github.com/mpi4py/mpi4py ``` -- [PyPi](https://pypi.org/project/mpi4py) (πŸ“₯ 710K / month Β· πŸ“¦ 740 Β· ⏱️ 28.07.2024): +- [PyPi](https://pypi.org/project/mpi4py) (πŸ“₯ 560K / month Β· πŸ“¦ 750 Β· ⏱️ 11.10.2024): ``` pip install mpi4py ``` -- [Conda](https://anaconda.org/conda-forge/mpi4py) (πŸ“₯ 3M Β· ⏱️ 04.09.2024): +- [Conda](https://anaconda.org/conda-forge/mpi4py) (πŸ“₯ 3M Β· ⏱️ 12.10.2024): ``` conda install -c conda-forge mpi4py ```
SynapseML (πŸ₯ˆ29 Β· ⭐ 5.1K) - Simple and Distributed Machine Learning. MIT -- [GitHub](https://github.com/microsoft/SynapseML) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 830 Β· πŸ“‹ 770 - 47% open Β· ⏱️ 10.09.2024): +- [GitHub](https://github.com/microsoft/SynapseML) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 830 Β· πŸ“‹ 780 - 48% open Β· ⏱️ 16.10.2024): ``` git clone https://github.com/microsoft/SynapseML ``` -- [PyPi](https://pypi.org/project/synapseml) (πŸ“₯ 250K / month Β· πŸ“¦ 5 Β· ⏱️ 30.08.2024): +- [PyPi](https://pypi.org/project/synapseml) (πŸ“₯ 230K / month Β· πŸ“¦ 5 Β· ⏱️ 16.10.2024): ``` pip install synapseml ```
Submit it (πŸ₯ˆ29 Β· ⭐ 1.3K) - Python 3.8+ toolbox for submitting jobs to Slurm. MIT -- [GitHub](https://github.com/facebookincubator/submitit) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 120 Β· πŸ“¦ 3.3K Β· πŸ“‹ 120 - 37% open Β· ⏱️ 18.09.2024): +- [GitHub](https://github.com/facebookincubator/submitit) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 120 Β· πŸ“¦ 3.4K Β· πŸ“‹ 120 - 37% open Β· ⏱️ 18.09.2024): ``` git clone https://github.com/facebookincubator/submitit ``` -- [PyPi](https://pypi.org/project/submitit) (πŸ“₯ 460K / month Β· πŸ“¦ 49 Β· ⏱️ 18.09.2024): +- [PyPi](https://pypi.org/project/submitit) (πŸ“₯ 540K / month Β· πŸ“¦ 49 Β· ⏱️ 18.09.2024): ``` pip install submitit ``` -- [Conda](https://anaconda.org/conda-forge/submitit) (πŸ“₯ 41K Β· ⏱️ 24.11.2023): +- [Conda](https://anaconda.org/conda-forge/submitit) (πŸ“₯ 42K Β· ⏱️ 24.11.2023): ``` conda install -c conda-forge submitit ```
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petastorm (πŸ₯‰27 Β· ⭐ 1.8K Β· πŸ’€) - Petastorm library enables single machine or distributed.. Apache-2 +
petastorm (πŸ₯ˆ28 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“₯ 520 Β· πŸ“¦ 180 Β· πŸ“‹ 320 - 53% open Β· ⏱️ 02.12.2023): @@ -4576,7 +4561,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn pip install petastorm ```
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dask-ml (πŸ₯‰27 Β· ⭐ 900) - Scalable Machine Learning with Dask. BSD-3 +
dask-ml (πŸ₯ˆ28 Β· ⭐ 900) - Scalable Machine Learning with Dask. BSD-3 - [GitHub](https://github.com/dask/dask-ml) (πŸ‘¨β€πŸ’» 80 Β· πŸ”€ 260 Β· πŸ“¦ 1.1K Β· πŸ“‹ 540 - 52% open Β· ⏱️ 20.07.2024): @@ -4592,37 +4577,37 @@ _Libraries that provide capabilities to distribute and parallelize machine learn conda install -c conda-forge dask-ml ```
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Apache Singa (πŸ₯‰25 Β· ⭐ 3.4K) - a distributed deep learning platform. Apache-2 +
Apache Singa (πŸ₯‰24 Β· ⭐ 3.4K) - a distributed deep learning platform. Apache-2 - [GitHub](https://github.com/apache/singa) (πŸ‘¨β€πŸ’» 91 Β· πŸ”€ 1.2K Β· πŸ“¦ 5 Β· πŸ“‹ 130 - 37% open Β· ⏱️ 17.08.2024): ``` git clone https://github.com/apache/singa ``` -- [Conda](https://anaconda.org/nusdbsystem/singa): +- [Conda](https://anaconda.org/nusdbsystem/singa) (πŸ“₯ 800 Β· ⏱️ 16.06.2023): ``` conda install -c nusdbsystem singa ``` -- [Docker Hub](https://hub.docker.com/r/apache/singa) (πŸ“₯ 8.1K Β· ⭐ 4 Β· ⏱️ 31.05.2022): +- [Docker Hub](https://hub.docker.com/r/apache/singa) (πŸ“₯ 8.2K Β· ⭐ 4 Β· ⏱️ 31.05.2022): ``` docker pull apache/singa ```
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’» 32 Β· πŸ”€ 150 Β· πŸ“¦ 110 Β· πŸ“‹ 180 - 41% open Β· ⏱️ 15.07.2024): +- [GitHub](https://github.com/learning-at-home/hivemind) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 160 Β· πŸ“¦ 110 Β· πŸ“‹ 180 - 41% open Β· ⏱️ 21.10.2024): ``` git clone https://github.com/learning-at-home/hivemind ``` -- [PyPi](https://pypi.org/project/hivemind) (πŸ“₯ 2.3K / month Β· πŸ“¦ 10 Β· ⏱️ 31.08.2023): +- [PyPi](https://pypi.org/project/hivemind) (πŸ“₯ 3.6K / month Β· πŸ“¦ 10 Β· ⏱️ 31.08.2023): ``` pip install hivemind ```
MMLSpark (πŸ₯‰23 Β· ⭐ 5.1K) - Simple and Distributed Machine Learning. MIT -- [GitHub](https://github.com/microsoft/SynapseML) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 830 Β· πŸ“‹ 770 - 47% open Β· ⏱️ 10.09.2024): +- [GitHub](https://github.com/microsoft/SynapseML) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 830 Β· πŸ“‹ 780 - 48% open Β· ⏱️ 16.10.2024): ``` git clone https://github.com/microsoft/SynapseML @@ -4639,19 +4624,19 @@ _Libraries that provide capabilities to distribute and parallelize machine learn ``` git clone https://github.com/intel-analytics/analytics-zoo ``` -- [PyPi](https://pypi.org/project/analytics-zoo) (πŸ“₯ 4K / month Β· πŸ“¦ 1 Β· ⏱️ 22.08.2022): +- [PyPi](https://pypi.org/project/analytics-zoo) (πŸ“₯ 11K / month Β· πŸ“¦ 1 Β· ⏱️ 22.08.2022): ``` pip install analytics-zoo ```
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Mesh (πŸ₯‰23 Β· ⭐ 1.6K Β· πŸ’€) - Mesh TensorFlow: Model Parallelism Made Easier. Apache-2 +
Mesh (πŸ₯‰22 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”€ 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“₯ 64K / month Β· πŸ“¦ 3 Β· ⏱️ 15.05.2022): +- [PyPi](https://pypi.org/project/mesh-tensorflow) (πŸ“₯ 51K / month Β· πŸ“¦ 3 Β· ⏱️ 15.05.2022): ``` pip install mesh-tensorflow ``` @@ -4685,28 +4670,28 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc
Optuna (πŸ₯‡43 Β· ⭐ 11K) - A hyperparameter optimization framework. MIT -- [GitHub](https://github.com/optuna/optuna) (πŸ‘¨β€πŸ’» 270 Β· πŸ”€ 1K Β· πŸ“¦ 18K Β· πŸ“‹ 1.7K - 4% open Β· ⏱️ 08.10.2024): +- [GitHub](https://github.com/optuna/optuna) (πŸ‘¨β€πŸ’» 270 Β· πŸ”€ 1K Β· πŸ“¦ 18K Β· πŸ“‹ 1.7K - 4% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/optuna/optuna ``` -- [PyPi](https://pypi.org/project/optuna) (πŸ“₯ 3.6M / month Β· πŸ“¦ 1K Β· ⏱️ 02.09.2024): +- [PyPi](https://pypi.org/project/optuna) (πŸ“₯ 3.7M / month Β· πŸ“¦ 1K Β· ⏱️ 02.09.2024): ``` pip install optuna ``` -- [Conda](https://anaconda.org/conda-forge/optuna) (πŸ“₯ 1.7M Β· ⏱️ 03.09.2024): +- [Conda](https://anaconda.org/conda-forge/optuna) (πŸ“₯ 1.8M Β· ⏱️ 03.09.2024): ``` conda install -c conda-forge optuna ```
Ax (πŸ₯‡36 Β· ⭐ 2.4K) - Adaptive Experimentation Platform. MIT -- [GitHub](https://github.com/facebook/Ax) (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 300 Β· πŸ“¦ 820 Β· πŸ“‹ 780 - 7% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/facebook/Ax) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 310 Β· πŸ“¦ 820 Β· πŸ“‹ 780 - 7% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/facebook/Ax ``` -- [PyPi](https://pypi.org/project/ax-platform) (πŸ“₯ 110K / month Β· πŸ“¦ 54 Β· ⏱️ 23.09.2024): +- [PyPi](https://pypi.org/project/ax-platform) (πŸ“₯ 120K / month Β· πŸ“¦ 54 Β· ⏱️ 23.09.2024): ``` pip install ax-platform ``` @@ -4715,46 +4700,34 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc conda install -c conda-forge ax-platform ```
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Bayesian Optimization (πŸ₯‡34 Β· ⭐ 7.8K) - A Python implementation of global optimization with.. MIT - -- [GitHub](https://github.com/bayesian-optimization/BayesianOptimization) (πŸ‘¨β€πŸ’» 47 Β· πŸ”€ 1.5K Β· πŸ“₯ 160 Β· πŸ“¦ 3K Β· πŸ“‹ 360 - 2% open Β· ⏱️ 01.10.2024): - - ``` - git clone https://github.com/fmfn/BayesianOptimization - ``` -- [PyPi](https://pypi.org/project/bayesian-optimization) (πŸ“₯ 470K / month Β· πŸ“¦ 140 Β· ⏱️ 10.07.2024): - ``` - pip install bayesian-optimization - ``` -
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AutoGluon (πŸ₯‡34 Β· ⭐ 7.8K) - Fast and Accurate ML in 3 Lines of Code. Apache-2 +
AutoGluon (πŸ₯‡35 Β· ⭐ 7.9K) - Fast and Accurate ML in 3 Lines of Code. Apache-2 -- [GitHub](https://github.com/autogluon/autogluon) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 910 Β· πŸ“¦ 840 Β· πŸ“‹ 1.5K - 25% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/autogluon/autogluon) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 920 Β· πŸ“¦ 840 Β· πŸ“‹ 1.5K - 25% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/autogluon/autogluon ``` -- [PyPi](https://pypi.org/project/autogluon) (πŸ“₯ 240K / month Β· πŸ“¦ 27 Β· ⏱️ 10.10.2024): +- [PyPi](https://pypi.org/project/autogluon) (πŸ“₯ 490K / month Β· πŸ“¦ 27 Β· ⏱️ 24.10.2024): ``` pip install autogluon ``` -- [Conda](https://anaconda.org/conda-forge/autogluon) (πŸ“₯ 20K Β· ⏱️ 18.06.2024): +- [Conda](https://anaconda.org/conda-forge/autogluon) (πŸ“₯ 21K Β· ⏱️ 18.10.2024): ``` conda install -c conda-forge autogluon ``` -- [Docker Hub](https://hub.docker.com/r/autogluon/autogluon) (πŸ“₯ 10K Β· ⭐ 17 Β· ⏱️ 07.03.2024): +- [Docker Hub](https://hub.docker.com/r/autogluon/autogluon) (πŸ“₯ 11K Β· ⭐ 17 Β· ⏱️ 07.03.2024): ``` docker pull autogluon/autogluon ```
BoTorch (πŸ₯‡34 Β· ⭐ 3.1K) - Bayesian optimization in PyTorch. MIT -- [GitHub](https://github.com/pytorch/botorch) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 390 Β· πŸ“¦ 1.2K Β· πŸ“‹ 530 - 12% open Β· ⏱️ 07.10.2024): +- [GitHub](https://github.com/pytorch/botorch) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 390 Β· πŸ“¦ 1.2K Β· πŸ“‹ 540 - 12% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/pytorch/botorch ``` -- [PyPi](https://pypi.org/project/botorch) (πŸ“₯ 200K / month Β· πŸ“¦ 84 Β· ⏱️ 17.09.2024): +- [PyPi](https://pypi.org/project/botorch) (πŸ“₯ 220K / month Β· πŸ“¦ 84 Β· ⏱️ 17.09.2024): ``` pip install botorch ``` @@ -4763,6 +4736,18 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc conda install -c conda-forge botorch ```
+
Bayesian Optimization (πŸ₯‡33 Β· ⭐ 7.9K) - A Python implementation of global optimization with.. MIT + +- [GitHub](https://github.com/bayesian-optimization/BayesianOptimization) (πŸ‘¨β€πŸ’» 47 Β· πŸ”€ 1.5K Β· πŸ“₯ 160 Β· πŸ“¦ 3K Β· πŸ“‹ 360 - 2% open Β· ⏱️ 21.10.2024): + + ``` + git clone https://github.com/fmfn/BayesianOptimization + ``` +- [PyPi](https://pypi.org/project/bayesian-optimization) (πŸ“₯ 440K / month Β· πŸ“¦ 150 Β· ⏱️ 21.10.2024): + ``` + pip install bayesian-optimization + ``` +
featuretools (πŸ₯‡33 Β· ⭐ 7.2K) - An open source python library for automated feature engineering. BSD-3 - [GitHub](https://github.com/alteryx/featuretools) (πŸ‘¨β€πŸ’» 73 Β· πŸ”€ 870 Β· πŸ“¦ 1.8K Β· πŸ“‹ 1K - 14% open Β· ⏱️ 21.06.2024): @@ -4770,7 +4755,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc ``` git clone https://github.com/alteryx/featuretools ``` -- [PyPi](https://pypi.org/project/featuretools) (πŸ“₯ 70K / month Β· πŸ“¦ 74 Β· ⏱️ 14.05.2024): +- [PyPi](https://pypi.org/project/featuretools) (πŸ“₯ 110K / month Β· πŸ“¦ 74 Β· ⏱️ 14.05.2024): ``` pip install featuretools ``` @@ -4795,9 +4780,9 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc conda install -c conda-forge hyperopt ```
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nevergrad (πŸ₯ˆ32 Β· ⭐ 3.9K) - A Python toolbox for performing gradient-free optimization. MIT +
nevergrad (πŸ₯ˆ32 Β· ⭐ 4K) - A Python toolbox for performing gradient-free optimization. MIT -- [GitHub](https://github.com/facebookresearch/nevergrad) (πŸ‘¨β€πŸ’» 57 Β· πŸ”€ 350 Β· πŸ“¦ 750 Β· πŸ“‹ 300 - 39% open Β· ⏱️ 04.10.2024): +- [GitHub](https://github.com/facebookresearch/nevergrad) (πŸ‘¨β€πŸ’» 57 Β· πŸ”€ 350 Β· πŸ“¦ 760 Β· πŸ“‹ 300 - 39% open Β· ⏱️ 12.10.2024): ``` git clone https://github.com/facebookresearch/nevergrad @@ -4806,7 +4791,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc ``` pip install nevergrad ``` -- [Conda](https://anaconda.org/conda-forge/nevergrad) (πŸ“₯ 54K Β· ⏱️ 09.01.2024): +- [Conda](https://anaconda.org/conda-forge/nevergrad) (πŸ“₯ 55K Β· ⏱️ 09.01.2024): ``` conda install -c conda-forge nevergrad ``` @@ -4823,53 +4808,53 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install nni ```
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AutoKeras (πŸ₯ˆ31 Β· ⭐ 9.1K Β· πŸ’€) - AutoML library for deep learning. Apache-2 +
AutoKeras (πŸ₯ˆ31 Β· ⭐ 9.1K) - AutoML library for deep learning. Apache-2 -- [GitHub](https://github.com/keras-team/autokeras) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 1.4K Β· πŸ“₯ 19K Β· πŸ“¦ 740 Β· πŸ“‹ 900 - 15% open Β· ⏱️ 20.03.2024): +- [GitHub](https://github.com/keras-team/autokeras) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 1.4K Β· πŸ“₯ 19K Β· πŸ“¦ 750 Β· πŸ“‹ 900 - 15% open Β· ⏱️ 17.10.2024): ``` git clone https://github.com/keras-team/autokeras ``` -- [PyPi](https://pypi.org/project/autokeras) (πŸ“₯ 24K / month Β· πŸ“¦ 13 Β· ⏱️ 20.03.2024): +- [PyPi](https://pypi.org/project/autokeras) (πŸ“₯ 30K / month Β· πŸ“¦ 13 Β· ⏱️ 20.03.2024): ``` pip install autokeras ```
Keras Tuner (πŸ₯ˆ31 Β· ⭐ 2.9K) - A Hyperparameter Tuning Library for Keras. Apache-2 -- [GitHub](https://github.com/keras-team/keras-tuner) (πŸ‘¨β€πŸ’» 61 Β· πŸ”€ 390 Β· πŸ“¦ 4.4K Β· πŸ“‹ 490 - 44% open Β· ⏱️ 24.06.2024): +- [GitHub](https://github.com/keras-team/keras-tuner) (πŸ‘¨β€πŸ’» 61 Β· πŸ”€ 390 Β· πŸ“¦ 4.5K Β· πŸ“‹ 490 - 44% open Β· ⏱️ 24.06.2024): ``` git clone https://github.com/keras-team/keras-tuner ``` -- [PyPi](https://pypi.org/project/keras-tuner) (πŸ“₯ 250K / month Β· πŸ“¦ 120 Β· ⏱️ 04.03.2024): +- [PyPi](https://pypi.org/project/keras-tuner) (πŸ“₯ 240K / month Β· πŸ“¦ 120 Β· ⏱️ 04.03.2024): ``` pip install keras-tuner ``` -- [Conda](https://anaconda.org/conda-forge/keras-tuner) (πŸ“₯ 40K Β· ⏱️ 05.03.2024): +- [Conda](https://anaconda.org/conda-forge/keras-tuner) (πŸ“₯ 41K Β· ⏱️ 05.03.2024): ``` conda install -c conda-forge keras-tuner ```
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mljar-supervised (πŸ₯ˆ29 Β· ⭐ 3K) - Python package for AutoML on Tabular Data with Feature.. MIT +
mljar-supervised (πŸ₯ˆ30 Β· ⭐ 3K) - Python package for AutoML on Tabular Data with Feature.. MIT -- [GitHub](https://github.com/mljar/mljar-supervised) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 400 Β· πŸ“¦ 130 Β· πŸ“‹ 660 - 21% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/mljar/mljar-supervised) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 400 Β· πŸ“¦ 130 Β· πŸ“‹ 660 - 21% open Β· ⏱️ 14.10.2024): ``` git clone https://github.com/mljar/mljar-supervised ``` -- [PyPi](https://pypi.org/project/mljar-supervised) (πŸ“₯ 6.8K / month Β· πŸ“¦ 4 Β· ⏱️ 09.10.2024): +- [PyPi](https://pypi.org/project/mljar-supervised) (πŸ“₯ 9K / month Β· πŸ“¦ 4 Β· ⏱️ 09.10.2024): ``` pip install mljar-supervised ``` -- [Conda](https://anaconda.org/conda-forge/mljar-supervised) (πŸ“₯ 22K Β· ⏱️ 10.09.2024): +- [Conda](https://anaconda.org/conda-forge/mljar-supervised) (πŸ“₯ 23K Β· ⏱️ 10.09.2024): ``` conda install -c conda-forge mljar-supervised ```
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lazypredict (πŸ₯ˆ26 Β· ⭐ 2.9K) - Lazy Predict help build a lot of basic models without much code.. MIT +
lazypredict (πŸ₯ˆ26 Β· ⭐ 3K) - 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”€ 330 Β· πŸ“¦ 1.1K Β· πŸ“‹ 120 - 67% open Β· ⏱️ 02.06.2024): +- [GitHub](https://github.com/shankarpandala/lazypredict) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 340 Β· πŸ“¦ 1.1K Β· πŸ“‹ 120 - 67% open Β· ⏱️ 02.06.2024): ``` git clone https://github.com/shankarpandala/lazypredict @@ -4890,31 +4875,31 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc ``` git clone https://github.com/autonomio/talos ``` -- [PyPi](https://pypi.org/project/talos) (πŸ“₯ 2.1K / month Β· πŸ“¦ 8 Β· ⏱️ 21.04.2024): +- [PyPi](https://pypi.org/project/talos) (πŸ“₯ 3.1K / month Β· πŸ“¦ 8 Β· ⏱️ 21.04.2024): ``` pip install talos ```
FEDOT (πŸ₯ˆ25 Β· ⭐ 640) - Automated modeling and machine learning framework FEDOT. BSD-3 -- [GitHub](https://github.com/aimclub/FEDOT) (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 86 Β· πŸ“¦ 53 Β· πŸ“‹ 550 - 17% open Β· ⏱️ 30.09.2024): +- [GitHub](https://github.com/aimclub/FEDOT) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 86 Β· πŸ“¦ 55 Β· πŸ“‹ 550 - 11% open Β· ⏱️ 17.10.2024): ``` git clone https://github.com/nccr-itmo/FEDOT ``` -- [PyPi](https://pypi.org/project/fedot) (πŸ“₯ 2.2K / month Β· πŸ“¦ 5 Β· ⏱️ 28.08.2024): +- [PyPi](https://pypi.org/project/fedot) (πŸ“₯ 3.2K / month Β· πŸ“¦ 5 Β· ⏱️ 28.08.2024): ``` pip install fedot ```
Hyperactive (πŸ₯ˆ25 Β· ⭐ 510) - An optimization and data collection toolbox for convenient and fast.. MIT -- [GitHub](https://github.com/SimonBlanke/Hyperactive) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 42 Β· πŸ“₯ 250 Β· πŸ“¦ 35 Β· πŸ“‹ 76 - 19% open Β· ⏱️ 01.10.2024): +- [GitHub](https://github.com/SimonBlanke/Hyperactive) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 42 Β· πŸ“₯ 250 Β· πŸ“¦ 36 Β· πŸ“‹ 76 - 19% open Β· ⏱️ 12.10.2024): ``` git clone https://github.com/SimonBlanke/Hyperactive ``` -- [PyPi](https://pypi.org/project/hyperactive) (πŸ“₯ 4K / month Β· πŸ“¦ 13 Β· ⏱️ 15.08.2024): +- [PyPi](https://pypi.org/project/hyperactive) (πŸ“₯ 5.5K / month Β· πŸ“¦ 13 Β· ⏱️ 15.08.2024): ``` pip install hyperactive ``` @@ -4926,7 +4911,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc ``` git clone https://github.com/AutoViML/Auto_ViML ``` -- [PyPi](https://pypi.org/project/autoviml) (πŸ“₯ 12K / month Β· πŸ“¦ 3 Β· ⏱️ 11.05.2024): +- [PyPi](https://pypi.org/project/autoviml) (πŸ“₯ 34K / month Β· πŸ“¦ 3 Β· ⏱️ 11.05.2024): ``` pip install autoviml ``` @@ -4938,31 +4923,31 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc ``` git clone https://github.com/ScottfreeLLC/AlphaPy ``` -- [PyPi](https://pypi.org/project/alphapy) (πŸ“₯ 2.4K / month Β· ⏱️ 29.08.2020): +- [PyPi](https://pypi.org/project/alphapy) (πŸ“₯ 6.7K / month Β· ⏱️ 29.08.2020): ``` pip install alphapy ```
featurewiz (πŸ₯‰21 Β· ⭐ 590) - Use advanced feature engineering strategies and select best.. Apache-2 -- [GitHub](https://github.com/AutoViML/featurewiz) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 86 Β· πŸ“¦ 74 Β· πŸ“‹ 96 - 4% open Β· ⏱️ 02.05.2024): +- [GitHub](https://github.com/AutoViML/featurewiz) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 87 Β· πŸ“¦ 74 Β· πŸ“‹ 96 - 4% open Β· ⏱️ 02.05.2024): ``` git clone https://github.com/AutoViML/featurewiz ``` -- [PyPi](https://pypi.org/project/featurewiz) (πŸ“₯ 40K / month Β· πŸ“¦ 2 Β· ⏱️ 10.02.2024): +- [PyPi](https://pypi.org/project/featurewiz) (πŸ“₯ 54K / month Β· πŸ“¦ 2 Β· ⏱️ 10.02.2024): ``` pip install featurewiz ```
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opytimizer (πŸ₯‰19 Β· ⭐ 600) - Opytimizer is a Python library consisting of meta-heuristic.. Apache-2 +
opytimizer (πŸ₯‰20 Β· ⭐ 600) - Opytimizer is a Python library consisting of meta-heuristic.. Apache-2 - [GitHub](https://github.com/gugarosa/opytimizer) (πŸ‘¨β€πŸ’» 4 Β· πŸ”€ 40 Β· πŸ“¦ 19 Β· ⏱️ 18.08.2024): ``` git clone https://github.com/gugarosa/opytimizer ``` -- [PyPi](https://pypi.org/project/opytimizer) (πŸ“₯ 800 / month Β· ⏱️ 18.08.2024): +- [PyPi](https://pypi.org/project/opytimizer) (πŸ“₯ 1.4K / month Β· ⏱️ 18.08.2024): ``` pip install opytimizer ``` @@ -4974,7 +4959,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc ``` git clone https://github.com/cerlymarco/shap-hypetune ``` -- [PyPi](https://pypi.org/project/shap-hypetune) (πŸ“₯ 2.6K / month Β· πŸ“¦ 2 Β· ⏱️ 21.02.2024): +- [PyPi](https://pypi.org/project/shap-hypetune) (πŸ“₯ 2.4K / month Β· πŸ“¦ 2 Β· ⏱️ 21.02.2024): ``` pip install shap-hypetune ``` @@ -4985,33 +4970,33 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc - TPOT (πŸ₯ˆ31 Β· ⭐ 9.7K Β· πŸ’€) - A Python Automated Machine Learning tool that optimizes.. ❗️LGPL-3.0 - auto-sklearn (πŸ₯ˆ31 Β· ⭐ 7.6K 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 +- SMAC3 (πŸ₯ˆ26 Β· ⭐ 1.1K) - SMAC3: A Versatile Bayesian Optimization Package for.. ❗️BSD-1-Clause - GPyOpt (πŸ₯ˆ26 Β· ⭐ 930 Β· πŸ’€) - Gaussian Process Optimization using GPy. BSD-3 - AdaNet (πŸ₯ˆ25 Β· ⭐ 3.5K Β· πŸ’€) - Fast and flexible AutoML with learning guarantees. Apache-2 -- SMAC3 (πŸ₯ˆ25 Β· ⭐ 1.1K) - SMAC3: A Versatile Bayesian Optimization Package for.. ❗️BSD-1-Clause +- auto_ml (πŸ₯‰24 Β· ⭐ 1.6K Β· πŸ’€) - [UNMAINTAINED] Automated machine learning for analytics & production. MIT - lightwood (πŸ₯‰24 Β· ⭐ 440) - Lightwood is Legos for Machine Learning. ❗️GPL-3.0 -- auto_ml (πŸ₯‰23 Β· ⭐ 1.6K Β· πŸ’€) - [UNMAINTAINED] Automated machine learning for analytics & production. MIT -- Orion (πŸ₯‰22 Β· ⭐ 280 Β· πŸ’€) - Asynchronous Distributed Hyperparameter Optimization. BSD-3 +- Orion (πŸ₯‰23 Β· ⭐ 280 Β· πŸ’€) - Asynchronous Distributed Hyperparameter Optimization. BSD-3 +- MLBox (πŸ₯‰22 Β· ⭐ 1.5K Β· πŸ’€) - MLBox is a powerful Automated Machine Learning python library. ❗️BSD-1-Clause +- Neuraxle (πŸ₯‰22 Β· ⭐ 610 Β· πŸ’€) - The worlds cleanest AutoML library - Do hyperparameter tuning.. Apache-2 - igel (πŸ₯‰21 Β· ⭐ 3.1K Β· πŸ’€) - a delightful machine learning tool that allows you to train, test, and.. MIT -- MLBox (πŸ₯‰21 Β· ⭐ 1.5K Β· πŸ’€) - MLBox is a powerful Automated Machine Learning python library. ❗️BSD-1-Clause -- sklearn-deap (πŸ₯‰21 Β· ⭐ 770 Β· πŸ’€) - Use evolutionary algorithms instead of gridsearch in.. MIT - Test Tube (πŸ₯‰21 Β· ⭐ 740 Β· πŸ’€) - Python library to easily log experiments and parallelize.. MIT - HpBandSter (πŸ₯‰21 Β· ⭐ 610 Β· πŸ’€) - a distributed Hyperband implementation on Steroids. BSD-3 -- Neuraxle (πŸ₯‰21 Β· ⭐ 610 Β· πŸ’€) - The worlds cleanest AutoML library - Do hyperparameter tuning.. Apache-2 - optunity (πŸ₯‰21 Β· ⭐ 420 Β· πŸ’€) - optimization routines for hyperparameter tuning. BSD-3 +- sklearn-deap (πŸ₯‰20 Β· ⭐ 770 Β· πŸ’€) - Use evolutionary algorithms instead of gridsearch in.. MIT +- Auto Tune Models (πŸ₯‰20 Β· ⭐ 530 Β· πŸ’€) - Auto Tune Models - A multi-tenant, multi-data system for.. MIT +- Advisor (πŸ₯‰19 Β· ⭐ 1.5K Β· πŸ’€) - Open-source implementation of Google Vizier for hyper parameters.. Apache-2 - Dragonfly (πŸ₯‰19 Β· ⭐ 850 Β· πŸ’€) - An open source python library for scalable Bayesian optimisation. MIT -- Auto Tune Models (πŸ₯‰19 Β· ⭐ 520 Β· πŸ’€) - Auto Tune Models - A multi-tenant, multi-data system for.. MIT -- Advisor (πŸ₯‰18 Β· ⭐ 1.5K Β· πŸ’€) - Open-source implementation of Google Vizier for hyper parameters.. Apache-2 +- Sherpa (πŸ₯‰19 Β· ⭐ 330 Β· πŸ’€) - Hyperparameter optimization that enables researchers to.. ❗️GPL-3.0 - Xcessiv (πŸ₯‰18 Β· ⭐ 1.3K Β· πŸ’€) - A web-based application for quick, scalable, and automated.. Apache-2 -- Sherpa (πŸ₯‰18 Β· ⭐ 330 Β· πŸ’€) - Hyperparameter optimization that enables researchers to.. ❗️GPL-3.0 -- HyperparameterHunter (πŸ₯‰17 Β· ⭐ 710 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 +- HyperparameterHunter (πŸ₯‰18 Β· ⭐ 710 Β· πŸ’€) - Easy hyperparameter optimization and automatic result.. MIT +- automl-gs (πŸ₯‰17 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 +- Auptimizer (πŸ₯‰14 Β· ⭐ 200 Β· πŸ’€) - An automatic ML model optimization tool. ❗️GPL-3.0 - ENAS (πŸ₯‰13 Β· ⭐ 2.7K Β· πŸ’€) - PyTorch implementation of Efficient Neural Architecture Search via.. Apache-2 -- Auptimizer (πŸ₯‰13 Β· ⭐ 200 Β· πŸ’€) - An automatic ML model optimization tool. ❗️GPL-3.0 - Hypermax (πŸ₯‰13 Β· ⭐ 110 Β· πŸ’€) - Better, faster hyper-parameter optimization. BSD-3 - model_search (πŸ₯‰11 Β· ⭐ 3.3K Β· πŸ’€) - AutoML algorithms for model architecture search at scale. Apache-2 - Devol (πŸ₯‰11 Β· ⭐ 950 Β· πŸ’€) - Genetic neural architecture search with Keras. MIT -- Hypertunity (πŸ₯‰10 Β· ⭐ 140 Β· πŸ’€) - A toolset for black-box hyperparameter optimisation. Apache-2 +- Hypertunity (πŸ₯‰11 Β· ⭐ 140 Β· πŸ’€) - A toolset for black-box hyperparameter optimisation. Apache-2

@@ -5021,26 +5006,26 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc _Libraries for building and evaluating reinforcement learning & agent-based systems._ -
FinRL (πŸ₯‡31 Β· ⭐ 9.8K) - FinRL: Financial Reinforcement Learning. MIT +
FinRL (πŸ₯‡31 Β· ⭐ 10K) - FinRL: Financial Reinforcement Learning. MIT -- [GitHub](https://github.com/AI4Finance-Foundation/FinRL) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 2.4K Β· πŸ“¦ 51 Β· πŸ“‹ 720 - 34% open Β· ⏱️ 08.10.2024): +- [GitHub](https://github.com/AI4Finance-Foundation/FinRL) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 2.4K Β· πŸ“¦ 51 Β· πŸ“‹ 720 - 34% open Β· ⏱️ 15.10.2024): ``` git clone https://github.com/AI4Finance-Foundation/FinRL ``` -- [PyPi](https://pypi.org/project/finrl) (πŸ“₯ 1.6K / month Β· ⏱️ 08.01.2022): +- [PyPi](https://pypi.org/project/finrl) (πŸ“₯ 2.1K / month Β· ⏱️ 08.01.2022): ``` pip install finrl ```
ViZDoom (πŸ₯‡30 Β· ⭐ 1.7K) - Reinforcement Learning environments based on the 1993 game Doom. MIT -- [GitHub](https://github.com/Farama-Foundation/ViZDoom) (πŸ‘¨β€πŸ’» 55 Β· πŸ”€ 380 Β· πŸ“₯ 12K Β· πŸ“¦ 270 Β· πŸ“‹ 460 - 6% open Β· ⏱️ 08.09.2024): +- [GitHub](https://github.com/Farama-Foundation/ViZDoom) (πŸ‘¨β€πŸ’» 55 Β· πŸ”€ 380 Β· πŸ“₯ 12K Β· πŸ“¦ 280 Β· πŸ“‹ 460 - 6% open Β· ⏱️ 08.09.2024): ``` git clone https://github.com/mwydmuch/ViZDoom ``` -- [PyPi](https://pypi.org/project/vizdoom) (πŸ“₯ 3.9K / month Β· πŸ“¦ 15 Β· ⏱️ 20.08.2024): +- [PyPi](https://pypi.org/project/vizdoom) (πŸ“₯ 6.3K / month Β· πŸ“¦ 15 Β· ⏱️ 20.08.2024): ``` pip install vizdoom ``` @@ -5052,7 +5037,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst ``` git clone https://github.com/tensorflow/agents ``` -- [PyPi](https://pypi.org/project/tf-agents) (πŸ“₯ 110K / month Β· πŸ“¦ 14 Β· ⏱️ 14.12.2023): +- [PyPi](https://pypi.org/project/tf-agents) (πŸ“₯ 93K / month Β· πŸ“¦ 14 Β· ⏱️ 14.12.2023): ``` pip install tf-agents ``` @@ -5064,23 +5049,23 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst ``` git clone https://github.com/deepmind/acme ``` -- [PyPi](https://pypi.org/project/dm-acme) (πŸ“₯ 1.6K / month Β· πŸ“¦ 3 Β· ⏱️ 10.02.2022): +- [PyPi](https://pypi.org/project/dm-acme) (πŸ“₯ 2.2K / month Β· πŸ“¦ 3 Β· ⏱️ 10.02.2022): ``` pip install dm-acme ``` -- [Conda](https://anaconda.org/conda-forge/dm-acme) (πŸ“₯ 9.9K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/dm-acme) (πŸ“₯ 10K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge dm-acme ```
Dopamine (πŸ₯ˆ27 Β· ⭐ 11K) - Dopamine is a research framework for fast prototyping of.. Apache-2 -- [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/google/dopamine) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 1.4K Β· πŸ“¦ 21 Β· πŸ“‹ 190 - 54% open Β· ⏱️ 06.05.2024): ``` git clone https://github.com/google/dopamine ``` -- [PyPi](https://pypi.org/project/dopamine-rl) (πŸ“₯ 40K / month Β· πŸ“¦ 10 Β· ⏱️ 06.05.2024): +- [PyPi](https://pypi.org/project/dopamine-rl) (πŸ“₯ 43K / month Β· πŸ“¦ 10 Β· ⏱️ 06.05.2024): ``` pip install dopamine-rl ``` @@ -5092,31 +5077,31 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst ``` git clone https://github.com/tensorforce/tensorforce ``` -- [PyPi](https://pypi.org/project/tensorforce) (πŸ“₯ 1.2K / month Β· πŸ“¦ 4 Β· ⏱️ 30.08.2021): +- [PyPi](https://pypi.org/project/tensorforce) (πŸ“₯ 1.6K / month Β· πŸ“¦ 4 Β· ⏱️ 30.08.2021): ``` pip install tensorforce ```
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PARL (πŸ₯‰25 Β· ⭐ 3.3K Β· πŸ“ˆ) - A high-performance distributed training framework for.. Apache-2 +
PARL (πŸ₯‰25 Β· ⭐ 3.3K) - A high-performance distributed training framework for Reinforcement.. Apache-2 - [GitHub](https://github.com/PaddlePaddle/PARL) (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 820 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“₯ 1.3K / month Β· πŸ“¦ 1 Β· ⏱️ 13.05.2022): +- [PyPi](https://pypi.org/project/parl) (πŸ“₯ 1.9K / month Β· πŸ“¦ 1 Β· ⏱️ 13.05.2022): ``` pip install parl ```
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RLax (πŸ₯‰25 Β· ⭐ 1.2K) - A library of reinforcement learning building blocks in JAX. Apache-2 +
RLax (πŸ₯‰25 Β· ⭐ 1.3K) - A library of reinforcement learning building blocks in JAX. Apache-2 - [GitHub](https://github.com/google-deepmind/rlax) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 85 Β· πŸ“¦ 270 Β· πŸ“‹ 26 - 30% open Β· ⏱️ 24.05.2024): ``` git clone https://github.com/deepmind/rlax ``` -- [PyPi](https://pypi.org/project/rlax) (πŸ“₯ 23K / month Β· πŸ“¦ 11 Β· ⏱️ 09.01.2023): +- [PyPi](https://pypi.org/project/rlax) (πŸ“₯ 21K / month Β· πŸ“¦ 11 Β· ⏱️ 09.01.2023): ``` pip install rlax ``` @@ -5128,7 +5113,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst ``` git clone https://github.com/facebookresearch/ReAgent ``` -- [PyPi](https://pypi.org/project/reagent) (πŸ“₯ 77 / month Β· ⏱️ 27.05.2020): +- [PyPi](https://pypi.org/project/reagent) (πŸ“₯ 85 / month Β· ⏱️ 27.05.2020): ``` pip install reagent ``` @@ -5140,14 +5125,14 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst ``` git clone https://github.com/pfnet/pfrl ``` -- [PyPi](https://pypi.org/project/pfrl) (πŸ“₯ 970 / month Β· πŸ“¦ 1 Β· ⏱️ 16.07.2023): +- [PyPi](https://pypi.org/project/pfrl) (πŸ“₯ 810 / month Β· πŸ“¦ 1 Β· ⏱️ 16.07.2023): ``` pip install pfrl ```
rliable (πŸ₯‰14 Β· ⭐ 760) - [NeurIPS21 Outstanding Paper] Library for reliable evaluation on RL.. Apache-2 -- [GitHub](https://github.com/google-research/rliable) (πŸ‘¨β€πŸ’» 9 Β· πŸ”€ 46 Β· πŸ“¦ 150 Β· πŸ“‹ 17 - 5% open Β· ⏱️ 12.08.2024): +- [GitHub](https://github.com/google-research/rliable) (πŸ‘¨β€πŸ’» 9 Β· πŸ”€ 47 Β· πŸ“¦ 160 Β· πŸ“‹ 17 - 5% open Β· ⏱️ 12.08.2024): ``` git clone https://github.com/google-research/rliable @@ -5159,12 +5144,12 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst
Show 12 hidden projects... -- OpenAI Gym (πŸ₯‡40 Β· ⭐ 35K Β· πŸ’€) - A toolkit for developing and comparing reinforcement learning.. MIT +- OpenAI Gym (πŸ₯‡41 Β· ⭐ 35K Β· πŸ’€) - A toolkit for developing and comparing reinforcement learning.. MIT - baselines (πŸ₯‡30 Β· ⭐ 16K 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 - TensorLayer (πŸ₯ˆ27 Β· ⭐ 7.3K Β· πŸ’€) - Deep Learning and Reinforcement Learning Library for.. Apache-2 - garage (πŸ₯‰26 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 +- Stable Baselines (πŸ₯‰24 Β· ⭐ 4.2K 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₯‰21 Β· ⭐ 2.3K Β· πŸ’€) - Reinforcement Learning Coach by Intel AI Lab enables easy.. Apache-2 @@ -5182,40 +5167,40 @@ _Libraries for building and evaluating recommendation systems._
Recommenders (πŸ₯‡35 Β· ⭐ 19K) - Best Practices on Recommendation Systems. MIT -- [GitHub](https://github.com/recommenders-team/recommenders) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 3.1K Β· πŸ“₯ 590 Β· πŸ“¦ 120 Β· πŸ“‹ 860 - 18% open Β· ⏱️ 11.09.2024): +- [GitHub](https://github.com/recommenders-team/recommenders) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 3.1K Β· πŸ“₯ 590 Β· πŸ“¦ 120 Β· πŸ“‹ 870 - 18% open Β· ⏱️ 11.09.2024): ``` git clone https://github.com/microsoft/recommenders ``` -- [PyPi](https://pypi.org/project/recommenders) (πŸ“₯ 30K / month Β· πŸ“¦ 4 Β· ⏱️ 01.05.2024): +- [PyPi](https://pypi.org/project/recommenders) (πŸ“₯ 33K / month Β· πŸ“¦ 4 Β· ⏱️ 01.05.2024): ``` pip install recommenders ```
torchrec (πŸ₯‡32 Β· ⭐ 1.9K) - Pytorch domain library for recommendation systems. BSD-3 -- [GitHub](https://github.com/pytorch/torchrec) (πŸ‘¨β€πŸ’» 280 Β· πŸ”€ 420 Β· πŸ“¦ 140 Β· πŸ“‹ 420 - 71% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/pytorch/torchrec) (πŸ‘¨β€πŸ’» 280 Β· πŸ”€ 420 Β· πŸ“¦ 150 Β· πŸ“‹ 420 - 71% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/pytorch/torchrec ``` -- [PyPi](https://pypi.org/project/torchrec-nightly-cpu) (πŸ“₯ 9.2K / month Β· ⏱️ 12.05.2022): +- [PyPi](https://pypi.org/project/torchrec-nightly-cpu) (πŸ“₯ 12K / month Β· ⏱️ 12.05.2022): ``` pip install torchrec-nightly-cpu ```
implicit (πŸ₯ˆ30 Β· ⭐ 3.5K Β· πŸ’€) - Fast Python Collaborative Filtering for Implicit Feedback Datasets. MIT -- [GitHub](https://github.com/benfred/implicit) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 600 Β· πŸ“₯ 1.4K Β· πŸ“¦ 1.5K Β· πŸ“‹ 500 - 17% open Β· ⏱️ 21.11.2023): +- [GitHub](https://github.com/benfred/implicit) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 600 Β· πŸ“₯ 1.5K Β· πŸ“¦ 1.5K Β· πŸ“‹ 500 - 17% open Β· ⏱️ 21.11.2023): ``` git clone https://github.com/benfred/implicit ``` -- [PyPi](https://pypi.org/project/implicit) (πŸ“₯ 280K / month Β· πŸ“¦ 29 Β· ⏱️ 29.09.2023): +- [PyPi](https://pypi.org/project/implicit) (πŸ“₯ 260K / month Β· πŸ“¦ 29 Β· ⏱️ 29.09.2023): ``` pip install implicit ``` -- [Conda](https://anaconda.org/conda-forge/implicit) (πŸ“₯ 870K Β· ⏱️ 23.08.2024): +- [Conda](https://anaconda.org/conda-forge/implicit) (πŸ“₯ 900K Β· ⏱️ 23.08.2024): ``` conda install -c conda-forge implicit ``` @@ -5227,27 +5212,27 @@ _Libraries for building and evaluating recommendation systems._ ``` git clone https://github.com/NicolasHug/Surprise ``` -- [PyPi](https://pypi.org/project/scikit-surprise) (πŸ“₯ 78K / month Β· πŸ“¦ 37 Β· ⏱️ 19.05.2024): +- [PyPi](https://pypi.org/project/scikit-surprise) (πŸ“₯ 90K / month Β· πŸ“¦ 37 Β· ⏱️ 19.05.2024): ``` pip install scikit-surprise ``` -- [Conda](https://anaconda.org/conda-forge/scikit-surprise) (πŸ“₯ 410K Β· ⏱️ 20.05.2024): +- [Conda](https://anaconda.org/conda-forge/scikit-surprise) (πŸ“₯ 420K Β· ⏱️ 20.05.2024): ``` conda install -c conda-forge scikit-surprise ```
-
Cornac (πŸ₯ˆ27 Β· ⭐ 870) - A Comparative Framework for Multimodal Recommender Systems. Apache-2 +
Cornac (πŸ₯ˆ28 Β· ⭐ 880) - A Comparative Framework for Multimodal Recommender Systems. Apache-2 -- [GitHub](https://github.com/PreferredAI/cornac) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 140 Β· πŸ“¦ 240 Β· πŸ“‹ 160 - 10% open Β· ⏱️ 14.09.2024): +- [GitHub](https://github.com/PreferredAI/cornac) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 140 Β· πŸ“¦ 240 Β· πŸ“‹ 160 - 11% open Β· ⏱️ 14.09.2024): ``` git clone https://github.com/PreferredAI/cornac ``` -- [PyPi](https://pypi.org/project/cornac) (πŸ“₯ 48K / month Β· πŸ“¦ 18 Β· ⏱️ 15.08.2024): +- [PyPi](https://pypi.org/project/cornac) (πŸ“₯ 64K / month Β· πŸ“¦ 18 Β· ⏱️ 15.08.2024): ``` pip install cornac ``` -- [Conda](https://anaconda.org/conda-forge/cornac) (πŸ“₯ 580K Β· ⏱️ 13.09.2024): +- [Conda](https://anaconda.org/conda-forge/cornac) (πŸ“₯ 590K Β· ⏱️ 13.09.2024): ``` conda install -c conda-forge cornac ``` @@ -5266,16 +5251,16 @@ _Libraries for building and evaluating recommendation systems._
RecBole (πŸ₯‰25 Β· ⭐ 3.4K) - A unified, comprehensive and efficient recommendation library. MIT -- [GitHub](https://github.com/RUCAIBox/RecBole) (πŸ‘¨β€πŸ’» 74 Β· πŸ”€ 600 Β· πŸ“‹ 990 - 28% open Β· ⏱️ 05.09.2024): +- [GitHub](https://github.com/RUCAIBox/RecBole) (πŸ‘¨β€πŸ’» 74 Β· πŸ”€ 610 Β· πŸ“‹ 990 - 28% open Β· ⏱️ 05.09.2024): ``` git clone https://github.com/RUCAIBox/RecBole ``` -- [PyPi](https://pypi.org/project/recbole) (πŸ“₯ 45K / month Β· πŸ“¦ 2 Β· ⏱️ 31.10.2023): +- [PyPi](https://pypi.org/project/recbole) (πŸ“₯ 28K / month Β· πŸ“¦ 2 Β· ⏱️ 31.10.2023): ``` pip install recbole ``` -- [Conda](https://anaconda.org/aibox/recbole) (πŸ“₯ 6.2K Β· ⏱️ 01.11.2023): +- [Conda](https://anaconda.org/aibox/recbole) (πŸ“₯ 6.3K Β· ⏱️ 01.11.2023): ``` conda install -c aibox recbole ``` @@ -5287,7 +5272,7 @@ _Libraries for building and evaluating recommendation systems._ ``` git clone https://github.com/tensorflow/recommenders ``` -- [PyPi](https://pypi.org/project/tensorflow-recommenders) (πŸ“₯ 440K / month Β· πŸ“¦ 2 Β· ⏱️ 03.02.2023): +- [PyPi](https://pypi.org/project/tensorflow-recommenders) (πŸ“₯ 400K / month Β· πŸ“¦ 2 Β· ⏱️ 03.02.2023): ``` pip install tensorflow-recommenders ``` @@ -5299,15 +5284,15 @@ _Libraries for building and evaluating recommendation systems._ ``` git clone https://github.com/statisticianinstilettos/recmetrics ``` -- [PyPi](https://pypi.org/project/recmetrics) (πŸ“₯ 4.5K / month Β· ⏱️ 26.04.2022): +- [PyPi](https://pypi.org/project/recmetrics) (πŸ“₯ 4.7K / month Β· ⏱️ 26.04.2022): ``` pip install recmetrics ```
Show 8 hidden projects... -- lightfm (πŸ₯ˆ28 Β· ⭐ 4.7K Β· πŸ’€) - A Python implementation of LightFM, a hybrid recommendation.. Apache-2 -- lkpy (πŸ₯‰25 Β· ⭐ 260) - Python recommendation toolkit. MIT +- lightfm (πŸ₯ˆ28 Β· ⭐ 4.8K Β· πŸ’€) - A Python implementation of LightFM, a hybrid recommendation.. Apache-2 +- lkpy (πŸ₯‰25 Β· ⭐ 270) - Python recommendation toolkit. MIT - fastFM (πŸ₯‰22 Β· ⭐ 1.1K Β· πŸ’€) - fastFM: A Library for Factorization Machines. BSD-3 - tensorrec (πŸ₯‰21 Β· ⭐ 1.3K Β· πŸ’€) - A TensorFlow recommendation algorithm and framework in.. Apache-2 - Case Recommender (πŸ₯‰19 Β· ⭐ 480 Β· πŸ’€) - Case Recommender: A Flexible and Extensible Python.. MIT @@ -5325,24 +5310,24 @@ _Libraries for encrypted and privacy-preserving machine learning using methods l
PySyft (πŸ₯‡37 Β· ⭐ 9.5K) - Perform data science on data that remains in someone elses server. Apache-2 -- [GitHub](https://github.com/OpenMined/PySyft) (πŸ‘¨β€πŸ’» 520 Β· πŸ”€ 2K Β· πŸ“₯ 2.3K Β· πŸ“¦ 1 Β· πŸ“‹ 3.4K - 1% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/OpenMined/PySyft) (πŸ‘¨β€πŸ’» 520 Β· πŸ”€ 2K Β· πŸ“₯ 2.3K Β· πŸ“¦ 1 Β· πŸ“‹ 3.4K - 1% open Β· ⏱️ 15.10.2024): ``` git clone https://github.com/OpenMined/PySyft ``` -- [PyPi](https://pypi.org/project/syft) (πŸ“₯ 18K / month Β· πŸ“¦ 4 Β· ⏱️ 06.10.2024): +- [PyPi](https://pypi.org/project/syft) (πŸ“₯ 26K / month Β· πŸ“¦ 4 Β· ⏱️ 15.10.2024): ``` pip install syft ```
Opacus (πŸ₯ˆ32 Β· ⭐ 1.7K) - Training PyTorch models with differential privacy. Apache-2 -- [GitHub](https://github.com/pytorch/opacus) (πŸ‘¨β€πŸ’» 81 Β· πŸ”€ 330 Β· πŸ“₯ 120 Β· πŸ“¦ 880 Β· πŸ“‹ 310 - 23% open Β· ⏱️ 25.09.2024): +- [GitHub](https://github.com/pytorch/opacus) (πŸ‘¨β€πŸ’» 82 Β· πŸ”€ 330 Β· πŸ“₯ 130 Β· πŸ“¦ 890 Β· πŸ“‹ 310 - 23% open Β· ⏱️ 19.10.2024): ``` git clone https://github.com/pytorch/opacus ``` -- [PyPi](https://pypi.org/project/opacus) (πŸ“₯ 220K / month Β· πŸ“¦ 36 Β· ⏱️ 03.08.2024): +- [PyPi](https://pypi.org/project/opacus) (πŸ“₯ 260K / month Β· πŸ“¦ 36 Β· ⏱️ 03.08.2024): ``` pip install opacus ``` @@ -5353,7 +5338,7 @@ _Libraries for encrypted and privacy-preserving machine learning using methods l
FATE (πŸ₯ˆ26 Β· ⭐ 5.7K) - An Industrial Grade Federated Learning Framework. Apache-2 -- [GitHub](https://github.com/FederatedAI/FATE) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 1.5K Β· πŸ“‹ 2K - 2% open Β· ⏱️ 21.08.2024): +- [GitHub](https://github.com/FederatedAI/FATE) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 1.5K Β· πŸ“‹ 2K - 3% open Β· ⏱️ 21.08.2024): ``` git clone https://github.com/FederatedAI/FATE @@ -5370,7 +5355,7 @@ _Libraries for encrypted and privacy-preserving machine learning using methods l ``` git clone https://github.com/tensorflow/privacy ``` -- [PyPi](https://pypi.org/project/tensorflow-privacy) (πŸ“₯ 25K / month Β· πŸ“¦ 21 Β· ⏱️ 14.02.2024): +- [PyPi](https://pypi.org/project/tensorflow-privacy) (πŸ“₯ 24K / month Β· πŸ“¦ 21 Β· ⏱️ 14.02.2024): ``` pip install tensorflow-privacy ``` @@ -5382,26 +5367,26 @@ _Libraries for encrypted and privacy-preserving machine learning using methods l ``` git clone https://github.com/tf-encrypted/tf-encrypted ``` -- [PyPi](https://pypi.org/project/tf-encrypted) (πŸ“₯ 1.9K / month Β· πŸ“¦ 9 Β· ⏱️ 16.11.2022): +- [PyPi](https://pypi.org/project/tf-encrypted) (πŸ“₯ 3.3K / month Β· πŸ“¦ 9 Β· ⏱️ 16.11.2022): ``` pip install tf-encrypted ```
CrypTen (πŸ₯‰24 Β· ⭐ 1.5K) - A framework for Privacy Preserving Machine Learning. MIT -- [GitHub](https://github.com/facebookresearch/CrypTen) (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 270 Β· πŸ“¦ 45 Β· πŸ“‹ 270 - 28% open Β· ⏱️ 18.07.2024): +- [GitHub](https://github.com/facebookresearch/CrypTen) (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 270 Β· πŸ“¦ 45 Β· πŸ“‹ 280 - 28% open Β· ⏱️ 19.10.2024): ``` git clone https://github.com/facebookresearch/CrypTen ``` -- [PyPi](https://pypi.org/project/crypten) (πŸ“₯ 500 / month Β· πŸ“¦ 1 Β· ⏱️ 08.12.2022): +- [PyPi](https://pypi.org/project/crypten) (πŸ“₯ 850 / month Β· πŸ“¦ 1 Β· ⏱️ 08.12.2022): ``` pip install crypten ```
Show 1 hidden projects... -- PipelineDP (πŸ₯‰20 Β· ⭐ 270) - PipelineDP is a Python framework for applying differentially.. Apache-2 +- PipelineDP (πŸ₯‰20 Β· ⭐ 280) - PipelineDP is a Python framework for applying differentially.. Apache-2

@@ -5411,57 +5396,57 @@ _Libraries for encrypted and privacy-preserving machine learning using methods l _Libraries to organize, track, and visualize machine learning experiments._ -
mlflow (πŸ₯‡43 Β· ⭐ 18K) - Open source platform for the machine learning lifecycle. Apache-2 +
mlflow (πŸ₯‡44 Β· ⭐ 19K) - Open source platform for the machine learning lifecycle. Apache-2 -- [GitHub](https://github.com/mlflow/mlflow) (πŸ‘¨β€πŸ’» 780 Β· πŸ”€ 4.2K Β· πŸ“¦ 44K Β· πŸ“‹ 4.2K - 38% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/mlflow/mlflow) (πŸ‘¨β€πŸ’» 780 Β· πŸ”€ 4.2K Β· πŸ“¦ 45K Β· πŸ“‹ 4.2K - 38% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/mlflow/mlflow ``` -- [PyPi](https://pypi.org/project/mlflow) (πŸ“₯ 15M / month Β· πŸ“¦ 880 Β· ⏱️ 27.09.2024): +- [PyPi](https://pypi.org/project/mlflow) (πŸ“₯ 16M / month Β· πŸ“¦ 880 Β· ⏱️ 12.10.2024): ``` pip install mlflow ``` -- [Conda](https://anaconda.org/conda-forge/mlflow) (πŸ“₯ 2.4M Β· ⏱️ 17.09.2024): +- [Conda](https://anaconda.org/conda-forge/mlflow) (πŸ“₯ 2.4M Β· ⏱️ 16.10.2024): ``` conda install -c conda-forge mlflow ```
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DVC (πŸ₯‡42 Β· ⭐ 14K) - ML Experiments and Data Management with Git. Apache-2 +
DVC (πŸ₯‡42 Β· ⭐ 14K) - Data Versioning and ML Experiments. Apache-2 -- [GitHub](https://github.com/iterative/dvc) (πŸ‘¨β€πŸ’» 300 Β· πŸ”€ 1.2K Β· πŸ“¦ 18K Β· πŸ“‹ 4.7K - 4% open Β· ⏱️ 08.10.2024): +- [GitHub](https://github.com/iterative/dvc) (πŸ‘¨β€πŸ’» 310 Β· πŸ”€ 1.2K Β· πŸ“¦ 19K Β· πŸ“‹ 4.7K - 4% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/iterative/dvc ``` -- [PyPi](https://pypi.org/project/dvc) (πŸ“₯ 620K / month Β· πŸ“¦ 130 Β· ⏱️ 02.09.2024): +- [PyPi](https://pypi.org/project/dvc) (πŸ“₯ 690K / month Β· πŸ“¦ 130 Β· ⏱️ 23.10.2024): ``` pip install dvc ``` -- [Conda](https://anaconda.org/conda-forge/dvc) (πŸ“₯ 2.3M Β· ⏱️ 02.09.2024): +- [Conda](https://anaconda.org/conda-forge/dvc) (πŸ“₯ 2.3M Β· ⏱️ 23.10.2024): ``` conda install -c conda-forge dvc ```
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wandb client (πŸ₯‡42 Β· ⭐ 9K) - The AI developer platform. Use Weights & Biases to train and fine-.. MIT +
wandb client (πŸ₯‡42 Β· ⭐ 9.1K) - The AI developer platform. Use Weights & Biases to train and fine-.. MIT -- [GitHub](https://github.com/wandb/wandb) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 660 Β· πŸ“₯ 330 Β· πŸ“¦ 55K Β· πŸ“‹ 3.3K - 26% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/wandb/wandb) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 670 Β· πŸ“₯ 350 Β· πŸ“¦ 56K Β· πŸ“‹ 3.4K - 26% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/wandb/client ``` -- [PyPi](https://pypi.org/project/wandb) (πŸ“₯ 19M / month Β· πŸ“¦ 1.4K Β· ⏱️ 01.10.2024): +- [PyPi](https://pypi.org/project/wandb) (πŸ“₯ 21M / month Β· πŸ“¦ 1.4K Β· ⏱️ 17.10.2024): ``` pip install wandb ``` -- [Conda](https://anaconda.org/conda-forge/wandb) (πŸ“₯ 660K Β· ⏱️ 08.10.2024): +- [Conda](https://anaconda.org/conda-forge/wandb) (πŸ“₯ 690K Β· ⏱️ 23.10.2024): ``` conda install -c conda-forge wandb ```
Tensorboard (πŸ₯‡42 Β· ⭐ 6.7K) - TensorFlows Visualization Toolkit. Apache-2 -- [GitHub](https://github.com/tensorflow/tensorboard) (πŸ‘¨β€πŸ’» 320 Β· πŸ”€ 1.7K Β· πŸ“¦ 260K Β· πŸ“‹ 1.9K - 35% open Β· ⏱️ 08.10.2024): +- [GitHub](https://github.com/tensorflow/tensorboard) (πŸ‘¨β€πŸ’» 320 Β· πŸ”€ 1.7K Β· πŸ“¦ 270K Β· πŸ“‹ 1.9K - 35% open Β· ⏱️ 18.10.2024): ``` git clone https://github.com/tensorflow/tensorboard @@ -5477,12 +5462,12 @@ _Libraries to organize, track, and visualize machine learning experiments._
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’» 460 Β· πŸ”€ 1.1K Β· πŸ“¦ 4.5K Β· πŸ“‹ 1.5K - 20% open Β· ⏱️ 08.10.2024): +- [GitHub](https://github.com/aws/sagemaker-python-sdk) (πŸ‘¨β€πŸ’» 460 Β· πŸ”€ 1.1K Β· πŸ“¦ 4.6K Β· πŸ“‹ 1.5K - 21% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/aws/sagemaker-python-sdk ``` -- [PyPi](https://pypi.org/project/sagemaker) (πŸ“₯ 31M / month Β· πŸ“¦ 150 Β· ⏱️ 03.10.2024): +- [PyPi](https://pypi.org/project/sagemaker) (πŸ“₯ 29M / month Β· πŸ“¦ 150 Β· ⏱️ 03.10.2024): ``` pip install sagemaker ``` @@ -5491,30 +5476,30 @@ _Libraries to organize, track, and visualize machine learning experiments._ conda install -c conda-forge sagemaker-python-sdk ```
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PyCaret (πŸ₯ˆ36 Β· ⭐ 8.9K Β· πŸ“‰) - An open-source, low-code machine learning library in Python. MIT +
PyCaret (πŸ₯ˆ36 Β· ⭐ 8.9K) - 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“₯ 710 Β· πŸ“¦ 6.4K Β· πŸ“‹ 2.3K - 15% open Β· ⏱️ 30.08.2024): +- [GitHub](https://github.com/pycaret/pycaret) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 1.7K Β· πŸ“₯ 720 Β· πŸ“¦ 6.5K Β· πŸ“‹ 2.3K - 15% open Β· ⏱️ 30.08.2024): ``` git clone https://github.com/pycaret/pycaret ``` -- [PyPi](https://pypi.org/project/pycaret) (πŸ“₯ 280K / month Β· πŸ“¦ 31 Β· ⏱️ 28.04.2024): +- [PyPi](https://pypi.org/project/pycaret) (πŸ“₯ 290K / month Β· πŸ“¦ 31 Β· ⏱️ 28.04.2024): ``` pip install pycaret ``` -- [Conda](https://anaconda.org/conda-forge/pycaret) (πŸ“₯ 56K Β· ⏱️ 25.04.2024): +- [Conda](https://anaconda.org/conda-forge/pycaret) (πŸ“₯ 57K Β· ⏱️ 25.04.2024): ``` conda install -c conda-forge pycaret ```
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Metaflow (πŸ₯ˆ34 Β· ⭐ 8.1K) - Open Source Platform for developing, scaling and deploying serious.. Apache-2 +
Metaflow (πŸ₯ˆ35 Β· ⭐ 8.1K) - Open Source Platform for developing, scaling and deploying serious.. Apache-2 -- [GitHub](https://github.com/Netflix/metaflow) (πŸ‘¨β€πŸ’» 95 Β· πŸ”€ 760 Β· πŸ“¦ 730 Β· πŸ“‹ 740 - 44% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/Netflix/metaflow) (πŸ‘¨β€πŸ’» 96 Β· πŸ”€ 760 Β· πŸ“¦ 740 Β· πŸ“‹ 760 - 44% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/Netflix/metaflow ``` -- [PyPi](https://pypi.org/project/metaflow) (πŸ“₯ 920K / month Β· πŸ“¦ 45 Β· ⏱️ 07.10.2024): +- [PyPi](https://pypi.org/project/metaflow) (πŸ“₯ 880K / month Β· πŸ“¦ 47 Β· ⏱️ 23.10.2024): ``` pip install metaflow ``` @@ -5523,162 +5508,174 @@ _Libraries to organize, track, and visualize machine learning experiments._ conda install -c conda-forge metaflow ```
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ClearML (πŸ₯ˆ34 Β· ⭐ 5.6K) - ClearML - Auto-Magical CI/CD to streamline your AI workload... Apache-2 +
tensorboardX (πŸ₯ˆ34 Β· ⭐ 7.9K Β· πŸ’€) - tensorboard for pytorch (and chainer, mxnet, numpy, ...). MIT -- [GitHub](https://github.com/allegroai/clearml) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 650 Β· πŸ“₯ 2.9K Β· πŸ“¦ 1.3K Β· πŸ“‹ 1.1K - 46% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/lanpa/tensorboardX) (πŸ‘¨β€πŸ’» 82 Β· πŸ”€ 860 Β· πŸ“₯ 450 Β· πŸ“¦ 49K Β· πŸ“‹ 460 - 17% open Β· ⏱️ 12.11.2023): ``` - git clone https://github.com/allegroai/clearml + git clone https://github.com/lanpa/tensorboardX ``` -- [PyPi](https://pypi.org/project/clearml) (πŸ“₯ 340K / month Β· πŸ“¦ 40 Β· ⏱️ 01.10.2024): +- [PyPi](https://pypi.org/project/tensorboardX) (πŸ“₯ 3.5M / month Β· πŸ“¦ 620 Β· ⏱️ 20.08.2023): ``` - pip install clearml + pip install tensorboardX ``` -- [Docker Hub](https://hub.docker.com/r/allegroai/trains) (πŸ“₯ 30K Β· ⏱️ 05.10.2020): +- [Conda](https://anaconda.org/conda-forge/tensorboardx) (πŸ“₯ 1.2M Β· ⏱️ 20.08.2023): ``` - docker pull allegroai/trains + conda install -c conda-forge tensorboardx ```
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snakemake (πŸ₯ˆ34 Β· ⭐ 2.2K) - This is the development home of the workflow management system.. MIT +
snakemake (πŸ₯ˆ34 Β· ⭐ 2.3K) - This is the development home of the workflow management system.. MIT -- [GitHub](https://github.com/snakemake/snakemake) (πŸ‘¨β€πŸ’» 340 Β· πŸ”€ 550 Β· πŸ“¦ 2.1K Β· πŸ“‹ 1.8K - 62% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/snakemake/snakemake) (πŸ‘¨β€πŸ’» 340 Β· πŸ”€ 550 Β· πŸ“¦ 2.1K Β· πŸ“‹ 1.8K - 62% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/snakemake/snakemake ``` -- [PyPi](https://pypi.org/project/snakemake) (πŸ“₯ 120K / month Β· πŸ“¦ 230 Β· ⏱️ 07.10.2024): +- [PyPi](https://pypi.org/project/snakemake) (πŸ“₯ 130K / month Β· πŸ“¦ 230 Β· ⏱️ 23.10.2024): ``` pip install snakemake ``` -- [Conda](https://anaconda.org/bioconda/snakemake) (πŸ“₯ 1.2M Β· ⏱️ 07.10.2024): +- [Conda](https://anaconda.org/bioconda/snakemake) (πŸ“₯ 1.2M Β· ⏱️ 24.10.2024): ``` conda install -c bioconda snakemake ```
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tensorboardX (πŸ₯ˆ33 Β· ⭐ 7.9K Β· πŸ’€) - tensorboard for pytorch (and chainer, mxnet, numpy, ...). MIT +
ClearML (πŸ₯ˆ33 Β· ⭐ 5.6K) - ClearML - Auto-Magical CI/CD to streamline your AI workload... Apache-2 -- [GitHub](https://github.com/lanpa/tensorboardX) (πŸ‘¨β€πŸ’» 82 Β· πŸ”€ 860 Β· πŸ“₯ 450 Β· πŸ“¦ 49K Β· πŸ“‹ 460 - 17% open Β· ⏱️ 12.11.2023): +- [GitHub](https://github.com/allegroai/clearml) (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 650 Β· πŸ“₯ 2.9K Β· πŸ“¦ 1.3K Β· πŸ“‹ 1.1K - 46% open Β· ⏱️ 23.10.2024): ``` - git clone https://github.com/lanpa/tensorboardX + git clone https://github.com/allegroai/clearml ``` -- [PyPi](https://pypi.org/project/tensorboardX) (πŸ“₯ 3.2M / month Β· πŸ“¦ 620 Β· ⏱️ 20.08.2023): +- [PyPi](https://pypi.org/project/clearml) (πŸ“₯ 330K / month Β· πŸ“¦ 40 Β· ⏱️ 01.10.2024): ``` - pip install tensorboardX + pip install clearml ``` -- [Conda](https://anaconda.org/conda-forge/tensorboardx) (πŸ“₯ 1.2M Β· ⏱️ 20.08.2023): +- [Docker Hub](https://hub.docker.com/r/allegroai/trains) (πŸ“₯ 30K Β· ⏱️ 05.10.2020): ``` - conda install -c conda-forge tensorboardx + docker pull allegroai/trains ```
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kaggle (πŸ₯ˆ32 Β· ⭐ 6.2K) - Official Kaggle API. Apache-2 +
aim (πŸ₯ˆ33 Β· ⭐ 5.2K) - Aim An easy-to-use & supercharged open-source experiment tracker. Apache-2 -- [GitHub](https://github.com/Kaggle/kaggle-api) (πŸ‘¨β€πŸ’» 47 Β· πŸ”€ 1.1K Β· πŸ“¦ 21 Β· πŸ“‹ 490 - 30% open Β· ⏱️ 07.10.2024): +- [GitHub](https://github.com/aimhubio/aim) (πŸ‘¨β€πŸ’» 76 Β· πŸ”€ 320 Β· πŸ“¦ 710 Β· πŸ“‹ 1.1K - 36% open Β· ⏱️ 02.10.2024): ``` - git clone https://github.com/Kaggle/kaggle-api + git clone https://github.com/aimhubio/aim ``` -- [PyPi](https://pypi.org/project/kaggle) (πŸ“₯ 220K / month Β· πŸ“¦ 210 Β· ⏱️ 24.07.2024): +- [PyPi](https://pypi.org/project/aim) (πŸ“₯ 890K / month Β· πŸ“¦ 38 Β· ⏱️ 23.10.2024): ``` - pip install kaggle + pip install aim ``` -- [Conda](https://anaconda.org/conda-forge/kaggle) (πŸ“₯ 180K Β· ⏱️ 27.07.2024): +- [Conda](https://anaconda.org/conda-forge/aim) (πŸ“₯ 82K Β· ⏱️ 14.06.2024): ``` - conda install -c conda-forge kaggle + conda install -c conda-forge aim ```
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aim (πŸ₯ˆ32 Β· ⭐ 5.2K) - Aim An easy-to-use & supercharged open-source experiment tracker. Apache-2 +
kaggle (πŸ₯ˆ32 Β· ⭐ 6.2K) - Official Kaggle API. Apache-2 -- [GitHub](https://github.com/aimhubio/aim) (πŸ‘¨β€πŸ’» 76 Β· πŸ”€ 320 Β· πŸ“¦ 700 Β· πŸ“‹ 1K - 36% open Β· ⏱️ 02.10.2024): +- [GitHub](https://github.com/Kaggle/kaggle-api) (πŸ‘¨β€πŸ’» 47 Β· πŸ”€ 1.1K Β· πŸ“¦ 21 Β· πŸ“‹ 480 - 30% open Β· ⏱️ 07.10.2024): ``` - git clone https://github.com/aimhubio/aim + git clone https://github.com/Kaggle/kaggle-api ``` -- [PyPi](https://pypi.org/project/aim) (πŸ“₯ 350K / month Β· πŸ“¦ 38 Β· ⏱️ 09.10.2024): +- [PyPi](https://pypi.org/project/kaggle) (πŸ“₯ 220K / month Β· πŸ“¦ 210 Β· ⏱️ 24.07.2024): ``` - pip install aim + pip install kaggle ``` -- [Conda](https://anaconda.org/conda-forge/aim) (πŸ“₯ 80K Β· ⏱️ 14.06.2024): +- [Conda](https://anaconda.org/conda-forge/kaggle) (πŸ“₯ 190K Β· ⏱️ 27.07.2024): ``` - conda install -c conda-forge aim + conda install -c conda-forge kaggle ```
sacred (πŸ₯ˆ32 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“¦ 3.2K Β· πŸ“‹ 560 - 18% open Β· ⏱️ 26.08.2024): +- [GitHub](https://github.com/IDSIA/sacred) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 380 Β· πŸ“¦ 3.2K Β· πŸ“‹ 560 - 18% open Β· ⏱️ 22.10.2024): ``` git clone https://github.com/IDSIA/sacred ``` -- [PyPi](https://pypi.org/project/sacred) (πŸ“₯ 210K / month Β· πŸ“¦ 60 Β· ⏱️ 26.08.2024): +- [PyPi](https://pypi.org/project/sacred) (πŸ“₯ 99K / month Β· πŸ“¦ 60 Β· ⏱️ 26.08.2024): ``` pip install sacred ``` -- [Conda](https://anaconda.org/conda-forge/sacred) (πŸ“₯ 6.6K Β· ⏱️ 28.11.2023): +- [Conda](https://anaconda.org/conda-forge/sacred) (πŸ“₯ 6.8K Β· ⏱️ 28.11.2023): ``` conda install -c conda-forge sacred ```
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AzureML SDK (πŸ₯ˆ31 Β· ⭐ 4.1K) - Python notebooks with ML and deep learning examples with Azure.. MIT +
AzureML SDK (πŸ₯ˆ32 Β· ⭐ 4.1K) - Python notebooks with ML and deep learning examples with Azure.. MIT -- [GitHub](https://github.com/Azure/MachineLearningNotebooks) (πŸ‘¨β€πŸ’» 64 Β· πŸ”€ 2.5K Β· πŸ“₯ 660 Β· πŸ“‹ 1.5K - 26% open Β· ⏱️ 08.08.2024): +- [GitHub](https://github.com/Azure/MachineLearningNotebooks) (πŸ‘¨β€πŸ’» 64 Β· πŸ”€ 2.5K Β· πŸ“₯ 660 Β· πŸ“‹ 1.5K - 26% open Β· ⏱️ 21.10.2024): ``` git clone https://github.com/Azure/MachineLearningNotebooks ``` -- [PyPi](https://pypi.org/project/azureml-sdk) (πŸ“₯ 430K / month Β· πŸ“¦ 31 Β· ⏱️ 05.08.2024): +- [PyPi](https://pypi.org/project/azureml-sdk) (πŸ“₯ 430K / month Β· πŸ“¦ 31 Β· ⏱️ 16.10.2024): ``` pip install azureml-sdk ```
Neptune.ai (πŸ₯ˆ29 Β· ⭐ 580) - The experiment tracker for foundation model training. Apache-2 -- [GitHub](https://github.com/neptune-ai/neptune-client) (πŸ‘¨β€πŸ’» 54 Β· πŸ”€ 63 Β· πŸ“¦ 620 Β· πŸ“‹ 240 - 12% open Β· ⏱️ 26.09.2024): +- [GitHub](https://github.com/neptune-ai/neptune-client) (πŸ‘¨β€πŸ’» 54 Β· πŸ”€ 63 Β· πŸ“¦ 630 Β· πŸ“‹ 240 - 11% open Β· ⏱️ 26.09.2024): ``` git clone https://github.com/neptune-ai/neptune-client ``` -- [PyPi](https://pypi.org/project/neptune-client) (πŸ“₯ 510K / month Β· πŸ“¦ 77 Β· ⏱️ 02.10.2024): +- [PyPi](https://pypi.org/project/neptune-client) (πŸ“₯ 500K / month Β· πŸ“¦ 77 Β· ⏱️ 02.10.2024): ``` pip install neptune-client ``` -- [Conda](https://anaconda.org/conda-forge/neptune-client) (πŸ“₯ 280K Β· ⏱️ 02.10.2024): +- [Conda](https://anaconda.org/conda-forge/neptune-client) (πŸ“₯ 290K Β· ⏱️ 02.10.2024): ``` conda install -c conda-forge neptune-client ```
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VisualDL (πŸ₯ˆ28 Β· ⭐ 4.8K) - Deep Learning Visualization Toolkit. Apache-2 + +- [GitHub](https://github.com/PaddlePaddle/VisualDL) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 630 Β· πŸ“₯ 460 Β· πŸ“¦ 2 Β· πŸ“‹ 500 - 28% open Β· ⏱️ 14.10.2024): + + ``` + git clone https://github.com/PaddlePaddle/VisualDL + ``` +- [PyPi](https://pypi.org/project/visualdl) (πŸ“₯ 170K / month Β· πŸ“¦ 82 Β· ⏱️ 05.06.2023): + ``` + pip install visualdl + ``` +
Labml (πŸ₯ˆ28 Β· ⭐ 2K) - Monitor deep learning model training and hardware usage from your mobile phone. MIT -- [GitHub](https://github.com/labmlai/labml) (πŸ‘¨β€πŸ’» 9 Β· πŸ”€ 140 Β· πŸ“¦ 170 Β· πŸ“‹ 47 - 10% open Β· ⏱️ 07.10.2024): +- [GitHub](https://github.com/labmlai/labml) (πŸ‘¨β€πŸ’» 9 Β· πŸ”€ 140 Β· πŸ“¦ 170 Β· πŸ“‹ 47 - 10% open Β· ⏱️ 22.10.2024): ``` git clone https://github.com/labmlai/labml ``` -- [PyPi](https://pypi.org/project/labml) (πŸ“₯ 9.4K / month Β· πŸ“¦ 14 Β· ⏱️ 15.09.2024): +- [PyPi](https://pypi.org/project/labml) (πŸ“₯ 13K / month Β· πŸ“¦ 14 Β· ⏱️ 15.09.2024): ``` pip install labml ```
TNT (πŸ₯‰26 Β· ⭐ 1.7K) - A lightweight library for PyTorch training tools and utilities. BSD-3 -- [GitHub](https://github.com/pytorch/tnt) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 270 Β· πŸ“‹ 140 - 54% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/pytorch/tnt) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 270 Β· πŸ“‹ 140 - 54% open Β· ⏱️ 20.10.2024): ``` git clone https://github.com/pytorch/tnt ``` -- [PyPi](https://pypi.org/project/torchnet) (πŸ“₯ 5.7K / month Β· πŸ“¦ 24 Β· ⏱️ 29.07.2018): +- [PyPi](https://pypi.org/project/torchnet) (πŸ“₯ 6.3K / month Β· πŸ“¦ 24 Β· ⏱️ 29.07.2018): ``` pip install torchnet ```
quinn (πŸ₯‰26 Β· ⭐ 630) - pyspark methods to enhance developer productivity. Apache-2 -- [GitHub](https://github.com/mrpowers-io/quinn) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 97 Β· πŸ“₯ 40 Β· πŸ“¦ 85 Β· πŸ“‹ 130 - 26% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/mrpowers-io/quinn) (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 97 Β· πŸ“₯ 41 Β· πŸ“¦ 86 Β· πŸ“‹ 130 - 26% open Β· ⏱️ 12.10.2024): ``` git clone https://github.com/MrPowers/quinn ``` -- [PyPi](https://pypi.org/project/quinn) (πŸ“₯ 650K / month Β· πŸ“¦ 7 Β· ⏱️ 13.02.2024): +- [PyPi](https://pypi.org/project/quinn) (πŸ“₯ 670K / month Β· πŸ“¦ 7 Β· ⏱️ 13.02.2024): ``` pip install quinn ``` @@ -5690,31 +5687,31 @@ _Libraries to organize, track, and visualize machine learning experiments._ ``` git clone https://github.com/google/ml-metadata ``` -- [PyPi](https://pypi.org/project/ml-metadata) (πŸ“₯ 77K / month Β· πŸ“¦ 31 Β· ⏱️ 01.10.2024): +- [PyPi](https://pypi.org/project/ml-metadata) (πŸ“₯ 80K / month Β· πŸ“¦ 31 Β· ⏱️ 01.10.2024): ``` pip install ml-metadata ```
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gokart (πŸ₯‰25 Β· ⭐ 310) - Gokart solves reproducibility, task dependencies, constraints of good code,.. MIT +
gokart (πŸ₯‰25 Β· ⭐ 320) - Gokart solves reproducibility, task dependencies, constraints of good code,.. MIT -- [GitHub](https://github.com/m3dev/gokart) (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 57 Β· πŸ“¦ 81 Β· πŸ“‹ 83 - 24% open Β· ⏱️ 29.09.2024): +- [GitHub](https://github.com/m3dev/gokart) (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 57 Β· πŸ“¦ 82 Β· πŸ“‹ 83 - 24% open Β· ⏱️ 29.09.2024): ``` git clone https://github.com/m3dev/gokart ``` -- [PyPi](https://pypi.org/project/gokart) (πŸ“₯ 5.5K / month Β· πŸ“¦ 8 Β· ⏱️ 19.09.2024): +- [PyPi](https://pypi.org/project/gokart) (πŸ“₯ 8.6K / month Β· πŸ“¦ 8 Β· ⏱️ 19.09.2024): ``` pip install gokart ```
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caliban (πŸ₯‰16 Β· ⭐ 490 Β· πŸ’€) - Research workflows made easy, locally and in the Cloud. Apache-2 +
caliban (πŸ₯‰17 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”€ 66 Β· πŸ“¦ 4 Β· πŸ“‹ 34 - 55% open Β· ⏱️ 25.01.2024): ``` git clone https://github.com/google/caliban ``` -- [PyPi](https://pypi.org/project/caliban) (πŸ“₯ 650 / month Β· ⏱️ 12.09.2020): +- [PyPi](https://pypi.org/project/caliban) (πŸ“₯ 1.5K / month Β· ⏱️ 12.09.2020): ``` pip install caliban ``` @@ -5726,7 +5723,7 @@ _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“₯ 670K / month Β· πŸ“¦ 77 Β· ⏱️ 26.09.2024): +- [PyPi](https://pypi.org/project/comet_ml) (πŸ“₯ 620K / month Β· πŸ“¦ 77 Β· ⏱️ 23.10.2024): ``` pip install comet_ml ``` @@ -5735,26 +5732,25 @@ _Libraries to organize, track, and visualize machine learning experiments._ conda install -c anaconda comet_ml ```
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Show 18 hidden projects... +
Show 17 hidden projects... - Catalyst (πŸ₯ˆ28 Β· ⭐ 3.3K Β· πŸ’€) - Accelerated deep learning R&D. Apache-2 -- VisualDL (πŸ₯‰27 Β· ⭐ 4.8K Β· πŸ’€) - Deep Learning Visualization Toolkit. 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₯‰25 Β· ⭐ 550) - SciKit-Learn Laboratory (SKLL) makes it easy to run machine.. ❗️BSD-1-Clause -- Guild AI (πŸ₯‰23 Β· ⭐ 870 Β· πŸ’€) - Experiment tracking, ML developer tools. Apache-2 +- Guild AI (πŸ₯‰24 Β· ⭐ 870 Β· πŸ’€) - Experiment tracking, ML developer tools. Apache-2 +- Studio.ml (πŸ₯‰23 Β· ⭐ 380 Β· πŸ’€) - Studio: Simplify and expedite model building process. Apache-2 - hiddenlayer (πŸ₯‰22 Β· ⭐ 1.8K Β· πŸ’€) - Neural network graphs and training metrics for.. MIT -- Studio.ml (πŸ₯‰22 Β· ⭐ 380 Β· πŸ’€) - Studio: Simplify and expedite model building process. Apache-2 -- lore (πŸ₯‰21 Β· ⭐ 1.6K Β· πŸ’€) - Lore makes machine learning approachable for Software Engineers and.. MIT +- lore (πŸ₯‰22 Β· ⭐ 1.6K Β· πŸ’€) - Lore makes machine learning approachable for Software Engineers and.. MIT +- TensorWatch (πŸ₯‰21 Β· ⭐ 3.4K Β· πŸ’€) - Debugging, monitoring and visualization for Python Machine.. MIT - TensorBoard Logger (πŸ₯‰21 Β· ⭐ 630 Β· πŸ’€) - Log TensorBoard events without touching TensorFlow. 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₯‰19 Β· ⭐ 1.6K Β· πŸ’€) - Version control for machine learning. Apache-2 -- datmo (πŸ₯‰18 Β· ⭐ 340 Β· πŸ’€) - Open source production model management tool for data scientists. MIT +- datmo (πŸ₯‰19 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 - steppy (πŸ₯‰17 Β· ⭐ 130 Β· πŸ’€) - Lightweight, Python library for fast and reproducible experimentation. MIT -- ModelChimp (πŸ₯‰13 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 +- ModelChimp (πŸ₯‰14 Β· ⭐ 130 Β· πŸ’€) - Experiment tracking for machine and deep learning projects. BSD-2 +- traintool (πŸ₯‰10 Β· ⭐ 12 Β· πŸ’€) - Train off-the-shelf machine learning models in one.. Apache-2

@@ -5766,115 +5762,115 @@ _Libraries to serialize models to files, convert between a variety of model form
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”€ 3.7K Β· πŸ“₯ 22K Β· πŸ“¦ 34K Β· πŸ“‹ 2.9K - 12% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/onnx/onnx) (πŸ‘¨β€πŸ’» 320 Β· πŸ”€ 3.7K Β· πŸ“₯ 22K Β· πŸ“¦ 35K Β· πŸ“‹ 2.9K - 12% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/onnx/onnx ``` -- [PyPi](https://pypi.org/project/onnx) (πŸ“₯ 5.5M / month Β· πŸ“¦ 1.1K Β· ⏱️ 01.10.2024): +- [PyPi](https://pypi.org/project/onnx) (πŸ“₯ 6M / month Β· πŸ“¦ 1.1K Β· ⏱️ 01.10.2024): ``` pip install onnx ``` -- [Conda](https://anaconda.org/conda-forge/onnx) (πŸ“₯ 1.3M Β· ⏱️ 05.10.2024): +- [Conda](https://anaconda.org/conda-forge/onnx) (πŸ“₯ 1.3M Β· ⏱️ 21.10.2024): ``` conda install -c conda-forge onnx ```
triton (πŸ₯‡43 Β· ⭐ 13K) - Development repository for the Triton language and compiler. MIT -- [GitHub](https://github.com/triton-lang/triton) (πŸ‘¨β€πŸ’» 330 Β· πŸ”€ 1.6K Β· πŸ“¦ 39K Β· πŸ“‹ 1.4K - 45% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/triton-lang/triton) (πŸ‘¨β€πŸ’» 340 Β· πŸ”€ 1.6K Β· πŸ“¦ 40K Β· πŸ“‹ 1.5K - 45% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/openai/triton ``` -- [PyPi](https://pypi.org/project/triton) (πŸ“₯ 15M / month Β· πŸ“¦ 250 Β· ⏱️ 09.07.2024): +- [PyPi](https://pypi.org/project/triton) (πŸ“₯ 15M / month Β· πŸ“¦ 260 Β· ⏱️ 14.10.2024): ``` pip install triton ```
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huggingface_hub (πŸ₯ˆ38 Β· ⭐ 2K) - The official Python client for the Huggingface Hub. Apache-2 +
huggingface_hub (πŸ₯ˆ38 Β· ⭐ 2.1K) - The official Python client for the Huggingface Hub. Apache-2 -- [GitHub](https://github.com/huggingface/huggingface_hub) (πŸ‘¨β€πŸ’» 200 Β· πŸ”€ 530 Β· πŸ“‹ 970 - 15% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/huggingface/huggingface_hub) (πŸ‘¨β€πŸ’» 200 Β· πŸ”€ 540 Β· πŸ“‹ 980 - 15% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/huggingface/huggingface_hub ``` -- [PyPi](https://pypi.org/project/huggingface_hub) (πŸ“₯ 43M / month Β· πŸ“¦ 1.9K Β· ⏱️ 09.10.2024): +- [PyPi](https://pypi.org/project/huggingface_hub) (πŸ“₯ 49M / month Β· πŸ“¦ 1.9K Β· ⏱️ 21.10.2024): ``` pip install huggingface_hub ``` -- [Conda](https://anaconda.org/conda-forge/huggingface_hub) (πŸ“₯ 2.2M Β· ⏱️ 09.10.2024): +- [Conda](https://anaconda.org/conda-forge/huggingface_hub) (πŸ“₯ 2.2M Β· ⏱️ 21.10.2024): ``` conda install -c conda-forge huggingface_hub ```
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BentoML (πŸ₯ˆ35 Β· ⭐ 7.1K) - The easiest way to serve AI apps and models - Build reliable.. Apache-2 +
Core ML Tools (πŸ₯ˆ36 Β· ⭐ 4.4K Β· πŸ“ˆ) - Core ML tools contain supporting tools for Core ML model.. BSD-3 + +- [GitHub](https://github.com/apple/coremltools) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 630 Β· πŸ“₯ 12K Β· πŸ“¦ 4.2K Β· πŸ“‹ 1.4K - 24% open Β· ⏱️ 21.10.2024): + + ``` + git clone https://github.com/apple/coremltools + ``` +- [PyPi](https://pypi.org/project/coremltools) (πŸ“₯ 620K / month Β· πŸ“¦ 81 Β· ⏱️ 16.09.2024): + ``` + pip install coremltools + ``` +- [Conda](https://anaconda.org/conda-forge/coremltools) (πŸ“₯ 72K Β· ⏱️ 16.06.2023): + ``` + conda install -c conda-forge coremltools + ``` +
+
BentoML (πŸ₯ˆ35 Β· ⭐ 7.1K) - The easiest way to serve AI apps and models - Build Model Inference.. Apache-2 -- [GitHub](https://github.com/bentoml/BentoML) (πŸ‘¨β€πŸ’» 210 Β· πŸ”€ 780 Β· πŸ“₯ 1.2K Β· πŸ“¦ 2.1K Β· πŸ“‹ 1.1K - 15% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/bentoml/BentoML) (πŸ‘¨β€πŸ’» 210 Β· πŸ”€ 780 Β· πŸ“₯ 1.1K Β· πŸ“¦ 2.1K Β· πŸ“‹ 1.1K - 15% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/bentoml/BentoML ``` -- [PyPi](https://pypi.org/project/bentoml) (πŸ“₯ 110K / month Β· πŸ“¦ 28 Β· ⏱️ 25.09.2024): +- [PyPi](https://pypi.org/project/bentoml) (πŸ“₯ 120K / month Β· πŸ“¦ 28 Β· ⏱️ 16.10.2024): ``` pip install bentoml ```
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TorchServe (πŸ₯ˆ35 Β· ⭐ 4.2K) - Serve, optimize and scale PyTorch models in production. Apache-2 +
TorchServe (πŸ₯ˆ34 Β· ⭐ 4.2K) - Serve, optimize and scale PyTorch models in production. Apache-2 -- [GitHub](https://github.com/pytorch/serve) (πŸ‘¨β€πŸ’» 220 Β· πŸ”€ 850 Β· πŸ“₯ 6.9K Β· πŸ“¦ 730 Β· πŸ“‹ 1.7K - 24% open Β· ⏱️ 03.10.2024): +- [GitHub](https://github.com/pytorch/serve) (πŸ‘¨β€πŸ’» 220 Β· πŸ”€ 860 Β· πŸ“₯ 7K Β· πŸ“¦ 740 Β· πŸ“‹ 1.7K - 24% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/pytorch/serve ``` -- [PyPi](https://pypi.org/project/torchserve) (πŸ“₯ 53K / month Β· πŸ“¦ 22 Β· ⏱️ 30.09.2024): +- [PyPi](https://pypi.org/project/torchserve) (πŸ“₯ 55K / month Β· πŸ“¦ 22 Β· ⏱️ 30.09.2024): ``` pip install torchserve ``` -- [Conda](https://anaconda.org/pytorch/torchserve): +- [Conda](https://anaconda.org/pytorch/torchserve) (πŸ“₯ 330K Β· ⏱️ 30.09.2024): ``` conda install -c pytorch torchserve ``` -- [Docker Hub](https://hub.docker.com/r/pytorch/torchserve) (πŸ“₯ 1.3M Β· ⭐ 28 Β· ⏱️ 30.09.2024): +- [Docker Hub](https://hub.docker.com/r/pytorch/torchserve) (πŸ“₯ 1.4M Β· ⭐ 29 Β· ⏱️ 30.09.2024): ``` docker pull pytorch/torchserve ```
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Core ML Tools (πŸ₯ˆ34 Β· ⭐ 4.4K) - Core ML tools contain supporting tools for Core ML model.. BSD-3 - -- [GitHub](https://github.com/apple/coremltools) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 630 Β· πŸ“₯ 12K Β· πŸ“¦ 4.2K Β· πŸ“‹ 1.4K - 24% open Β· ⏱️ 08.10.2024): - - ``` - git clone https://github.com/apple/coremltools - ``` -- [PyPi](https://pypi.org/project/coremltools) (πŸ“₯ 400K / month Β· πŸ“¦ 81 Β· ⏱️ 16.09.2024): - ``` - pip install coremltools - ``` -- [Conda](https://anaconda.org/conda-forge/coremltools) (πŸ“₯ 71K Β· ⏱️ 16.06.2023): - ``` - conda install -c conda-forge coremltools - ``` -
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hls4ml (πŸ₯ˆ26 Β· ⭐ 1.2K) - Machine learning on FPGAs using HLS. Apache-2 +
hls4ml (πŸ₯ˆ26 Β· ⭐ 1.3K) - Machine learning on FPGAs using HLS. Apache-2 -- [GitHub](https://github.com/fastmachinelearning/hls4ml) (πŸ‘¨β€πŸ’» 62 Β· πŸ”€ 390 Β· πŸ“‹ 430 - 40% open Β· ⏱️ 02.10.2024): +- [GitHub](https://github.com/fastmachinelearning/hls4ml) (πŸ‘¨β€πŸ’» 62 Β· πŸ”€ 390 Β· πŸ“‹ 430 - 40% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/fastmachinelearning/hls4ml ``` -- [PyPi](https://pypi.org/project/hls4ml) (πŸ“₯ 1.4K / month Β· ⏱️ 19.12.2023): +- [PyPi](https://pypi.org/project/hls4ml) (πŸ“₯ 2K / month Β· ⏱️ 19.12.2023): ``` pip install hls4ml ``` -- [Conda](https://anaconda.org/conda-forge/hls4ml) (πŸ“₯ 8.7K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/hls4ml) (πŸ“₯ 8.9K 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 -- [GitHub](https://github.com/microsoft/hummingbird) (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 280 Β· πŸ“₯ 700 Β· πŸ“‹ 330 - 21% open Β· ⏱️ 27.09.2024): +- [GitHub](https://github.com/microsoft/hummingbird) (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 280 Β· πŸ“₯ 700 Β· πŸ“‹ 330 - 21% open Β· ⏱️ 16.10.2024): ``` git clone https://github.com/microsoft/hummingbird @@ -5883,7 +5879,7 @@ _Libraries to serialize models to files, convert between a variety of model form ``` pip install hummingbird-ml ``` -- [Conda](https://anaconda.org/conda-forge/hummingbird-ml) (πŸ“₯ 49K Β· ⏱️ 08.03.2024): +- [Conda](https://anaconda.org/conda-forge/hummingbird-ml) (πŸ“₯ 50K Β· ⏱️ 08.03.2024): ``` conda install -c conda-forge hummingbird-ml ``` @@ -5895,7 +5891,7 @@ _Libraries to serialize models to files, convert between a variety of model form ``` git clone https://github.com/nebuly-ai/nebullvm ``` -- [PyPi](https://pypi.org/project/nebullvm) (πŸ“₯ 1.4K / month Β· πŸ“¦ 2 Β· ⏱️ 18.06.2023): +- [PyPi](https://pypi.org/project/nebullvm) (πŸ“₯ 1.7K / month Β· πŸ“¦ 2 Β· ⏱️ 18.06.2023): ``` pip install nebullvm ``` @@ -5907,7 +5903,7 @@ _Libraries to serialize models to files, convert between a variety of model form ``` git clone https://github.com/riga/tfdeploy ``` -- [PyPi](https://pypi.org/project/tfdeploy) (πŸ“₯ 520 / month Β· ⏱️ 30.03.2017): +- [PyPi](https://pypi.org/project/tfdeploy) (πŸ“₯ 740 / month Β· ⏱️ 30.03.2017): ``` pip install tfdeploy ``` @@ -5935,7 +5931,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin
shap (πŸ₯‡43 Β· ⭐ 23K) - A game theoretic approach to explain the output of any machine learning model. MIT -- [GitHub](https://github.com/shap/shap) (πŸ‘¨β€πŸ’» 250 Β· πŸ”€ 3.3K Β· πŸ“¦ 21K Β· πŸ“‹ 2.5K - 29% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/shap/shap) (πŸ‘¨β€πŸ’» 250 Β· πŸ”€ 3.3K Β· πŸ“¦ 21K Β· πŸ“‹ 2.5K - 29% open Β· ⏱️ 15.10.2024): ``` git clone https://github.com/slundberg/shap @@ -5944,31 +5940,31 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin ``` pip install shap ``` -- [Conda](https://anaconda.org/conda-forge/shap) (πŸ“₯ 4M Β· ⏱️ 08.05.2024): +- [Conda](https://anaconda.org/conda-forge/shap) (πŸ“₯ 4.1M Β· ⏱️ 08.05.2024): ``` conda install -c conda-forge shap ```
Netron (πŸ₯‡37 Β· ⭐ 28K) - Visualizer for neural network, deep learning and machine learning.. MIT -- [GitHub](https://github.com/lutzroeder/netron) (πŸ‘¨β€πŸ’» 2 Β· πŸ”€ 2.8K Β· πŸ“₯ 55K Β· πŸ“¦ 570 Β· πŸ“‹ 1.1K - 2% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/lutzroeder/netron) (πŸ‘¨β€πŸ’» 2 Β· πŸ”€ 2.8K Β· πŸ“₯ 150K Β· πŸ“¦ 580 Β· πŸ“‹ 1.1K - 1% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/lutzroeder/netron ``` -- [PyPi](https://pypi.org/project/netron) (πŸ“₯ 33K / month Β· πŸ“¦ 83 Β· ⏱️ 06.10.2024): +- [PyPi](https://pypi.org/project/netron) (πŸ“₯ 27K / month Β· πŸ“¦ 83 Β· ⏱️ 19.10.2024): ``` pip install netron ```
arviz (πŸ₯‡36 Β· ⭐ 1.6K) - Exploratory analysis of Bayesian models with Python. Apache-2 -- [GitHub](https://github.com/arviz-devs/arviz) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 400 Β· πŸ“₯ 160 Β· πŸ“¦ 7.8K Β· πŸ“‹ 870 - 20% open Β· ⏱️ 08.10.2024): +- [GitHub](https://github.com/arviz-devs/arviz) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 400 Β· πŸ“₯ 160 Β· πŸ“¦ 7.9K Β· πŸ“‹ 870 - 20% open Β· ⏱️ 08.10.2024): ``` git clone https://github.com/arviz-devs/arviz ``` -- [PyPi](https://pypi.org/project/arviz) (πŸ“₯ 1.7M / month Β· πŸ“¦ 310 Β· ⏱️ 28.09.2024): +- [PyPi](https://pypi.org/project/arviz) (πŸ“₯ 1.5M / month Β· πŸ“¦ 310 Β· ⏱️ 28.09.2024): ``` pip install arviz ``` @@ -5977,32 +5973,32 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin conda install -c conda-forge arviz ```
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InterpretML (πŸ₯‡33 Β· ⭐ 6.2K) - Fit interpretable models. Explain blackbox machine learning. MIT +
Captum (πŸ₯‡34 Β· ⭐ 4.9K) - Model interpretability and understanding for PyTorch. BSD-3 -- [GitHub](https://github.com/interpretml/interpret) (πŸ‘¨β€πŸ’» 46 Β· πŸ”€ 720 Β· πŸ“¦ 760 Β· πŸ“‹ 450 - 23% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/pytorch/captum) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 490 Β· πŸ“¦ 2.5K Β· πŸ“‹ 570 - 40% open Β· ⏱️ 24.10.2024): ``` - git clone https://github.com/interpretml/interpret + git clone https://github.com/pytorch/captum ``` -- [PyPi](https://pypi.org/project/interpret) (πŸ“₯ 98K / month Β· πŸ“¦ 49 Β· ⏱️ 28.09.2024): +- [PyPi](https://pypi.org/project/captum) (πŸ“₯ 220K / month Β· πŸ“¦ 130 Β· ⏱️ 05.12.2023): ``` - pip install interpret + pip install captum + ``` +- [Conda](https://anaconda.org/conda-forge/captum) (πŸ“₯ 76K Β· ⏱️ 16.06.2023): + ``` + conda install -c conda-forge captum ```
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Captum (πŸ₯‡33 Β· ⭐ 4.9K) - Model interpretability and understanding for PyTorch. BSD-3 +
InterpretML (πŸ₯‡33 Β· ⭐ 6.3K) - Fit interpretable models. Explain blackbox machine learning. MIT -- [GitHub](https://github.com/pytorch/captum) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 480 Β· πŸ“¦ 2.4K Β· πŸ“‹ 570 - 40% open Β· ⏱️ 26.09.2024): +- [GitHub](https://github.com/interpretml/interpret) (πŸ‘¨β€πŸ’» 48 Β· πŸ”€ 730 Β· πŸ“¦ 770 Β· πŸ“‹ 450 - 23% open Β· ⏱️ 24.10.2024): ``` - git clone https://github.com/pytorch/captum - ``` -- [PyPi](https://pypi.org/project/captum) (πŸ“₯ 260K / month Β· πŸ“¦ 130 Β· ⏱️ 05.12.2023): - ``` - pip install captum + git clone https://github.com/interpretml/interpret ``` -- [Conda](https://anaconda.org/conda-forge/captum) (πŸ“₯ 73K Β· ⏱️ 16.06.2023): +- [PyPi](https://pypi.org/project/interpret) (πŸ“₯ 110K / month Β· πŸ“¦ 49 Β· ⏱️ 24.10.2024): ``` - conda install -c conda-forge captum + pip install interpret ```
evaluate (πŸ₯‡32 Β· ⭐ 2K) - Evaluate: A library for easily evaluating machine learning models and.. Apache-2 @@ -6012,55 +6008,71 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin ``` git clone https://github.com/huggingface/evaluate ``` -- [PyPi](https://pypi.org/project/evaluate) (πŸ“₯ 2.5M / month Β· πŸ“¦ 400 Β· ⏱️ 11.09.2024): +- [PyPi](https://pypi.org/project/evaluate) (πŸ“₯ 2.4M / month Β· πŸ“¦ 400 Β· ⏱️ 11.09.2024): ``` pip install evaluate ```
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shapash (πŸ₯ˆ30 Β· ⭐ 2.7K) - Shapash: User-friendly Explainability and Interpretability to.. Apache-2 +
shapash (πŸ₯ˆ31 Β· ⭐ 2.7K) - Shapash: User-friendly Explainability and Interpretability to.. Apache-2 -- [GitHub](https://github.com/MAIF/shapash) (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 330 Β· πŸ“¦ 180 Β· πŸ“‹ 210 - 17% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/MAIF/shapash) (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 330 Β· πŸ“¦ 180 Β· πŸ“‹ 220 - 17% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/MAIF/shapash ``` -- [PyPi](https://pypi.org/project/shapash) (πŸ“₯ 29K / month Β· πŸ“¦ 4 Β· ⏱️ 10.10.2024): +- [PyPi](https://pypi.org/project/shapash) (πŸ“₯ 39K / month Β· πŸ“¦ 4 Β· ⏱️ 24.10.2024): ``` pip install shapash ```
DoWhy (πŸ₯ˆ29 Β· ⭐ 7.1K) - DoWhy is a Python library for causal inference that supports explicit.. MIT -- [GitHub](https://github.com/py-why/dowhy) (πŸ‘¨β€πŸ’» 94 Β· πŸ”€ 910 Β· πŸ“₯ 40 Β· πŸ“¦ 430 Β· πŸ“‹ 480 - 27% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/py-why/dowhy) (πŸ‘¨β€πŸ’» 95 Β· πŸ”€ 930 Β· πŸ“₯ 40 Β· πŸ“¦ 440 Β· πŸ“‹ 480 - 28% open Β· ⏱️ 22.10.2024): ``` git clone https://github.com/py-why/dowhy ``` -- [PyPi](https://pypi.org/project/dowhy) (πŸ“₯ 56K / month Β· πŸ“¦ 7 Β· ⏱️ 25.12.2023): +- [PyPi](https://pypi.org/project/dowhy) (πŸ“₯ 55K / month Β· πŸ“¦ 7 Β· ⏱️ 25.12.2023): ``` pip install dowhy ``` -- [Conda](https://anaconda.org/conda-forge/dowhy) (πŸ“₯ 33K Β· ⏱️ 26.01.2024): +- [Conda](https://anaconda.org/conda-forge/dowhy) (πŸ“₯ 34K Β· ⏱️ 26.01.2024): ``` conda install -c conda-forge dowhy ```
explainerdashboard (πŸ₯ˆ29 Β· ⭐ 2.3K) - Quickly build Explainable AI dashboards that show the inner.. MIT -- [GitHub](https://github.com/oegedijk/explainerdashboard) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 330 Β· πŸ“¦ 540 Β· πŸ“‹ 240 - 14% open Β· ⏱️ 20.06.2024): +- [GitHub](https://github.com/oegedijk/explainerdashboard) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 330 Β· πŸ“¦ 550 Β· πŸ“‹ 240 - 14% open Β· ⏱️ 20.06.2024): ``` git clone https://github.com/oegedijk/explainerdashboard ``` -- [PyPi](https://pypi.org/project/explainerdashboard) (πŸ“₯ 83K / month Β· πŸ“¦ 10 Β· ⏱️ 18.03.2024): +- [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“₯ 53K Β· ⏱️ 18.03.2024): +- [Conda](https://anaconda.org/conda-forge/explainerdashboard) (πŸ“₯ 54K Β· ⏱️ 18.03.2024): ``` conda install -c conda-forge explainerdashboard ```
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fairlearn (πŸ₯ˆ29 Β· ⭐ 1.9K) - A Python package to assess and improve fairness of machine.. MIT + +- [GitHub](https://github.com/fairlearn/fairlearn) (πŸ‘¨β€πŸ’» 84 Β· πŸ”€ 420 Β· πŸ“¦ 3 Β· πŸ“‹ 480 - 33% open Β· ⏱️ 24.10.2024): + + ``` + git clone https://github.com/fairlearn/fairlearn + ``` +- [PyPi](https://pypi.org/project/fairlearn) (πŸ“₯ 180K / month Β· πŸ“¦ 55 Β· ⏱️ 19.12.2023): + ``` + pip install fairlearn + ``` +- [Conda](https://anaconda.org/conda-forge/fairlearn) (πŸ“₯ 37K Β· ⏱️ 20.12.2023): + ``` + conda install -c conda-forge fairlearn + ``` +
pyLDAvis (πŸ₯ˆ29 Β· ⭐ 1.8K) - Python library for interactive topic model visualization. Port of.. BSD-3 - [GitHub](https://github.com/bmabey/pyLDAvis) (πŸ‘¨β€πŸ’» 42 Β· πŸ”€ 360 Β· πŸ“¦ 6.5K Β· πŸ“‹ 190 - 40% open Β· ⏱️ 29.04.2024): @@ -6079,7 +6091,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin
Model Analysis (πŸ₯ˆ29 Β· ⭐ 1.3K) - Model analysis tools for TensorFlow. Apache-2 -- [GitHub](https://github.com/tensorflow/model-analysis) (πŸ‘¨β€πŸ’» 58 Β· πŸ”€ 270 Β· πŸ“‹ 88 - 37% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/tensorflow/model-analysis) (πŸ‘¨β€πŸ’» 58 Β· πŸ”€ 270 Β· πŸ“‹ 88 - 37% open Β· ⏱️ 17.10.2024): ``` git clone https://github.com/tensorflow/model-analysis @@ -6089,46 +6101,46 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install tensorflow-model-analysis ```
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dtreeviz (πŸ₯ˆ28 Β· ⭐ 2.9K) - A python library for decision tree visualization and model interpretation. MIT +
LIT (πŸ₯ˆ28 Β· ⭐ 3.5K Β· πŸ“ˆ) - The Learning Interpretability Tool: Interactively analyze ML models.. Apache-2 -- [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): +- [GitHub](https://github.com/PAIR-code/lit) (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 350 Β· πŸ“¦ 40 Β· πŸ“‹ 200 - 57% open Β· ⏱️ 22.10.2024): ``` - git clone https://github.com/parrt/dtreeviz + git clone https://github.com/PAIR-code/lit ``` -- [PyPi](https://pypi.org/project/dtreeviz) (πŸ“₯ 120K / month Β· πŸ“¦ 53 Β· ⏱️ 07.07.2022): +- [PyPi](https://pypi.org/project/lit-nlp) (πŸ“₯ 4.2K / month Β· πŸ“¦ 3 Β· ⏱️ 22.10.2024): ``` - pip install dtreeviz + pip install lit-nlp ``` -- [Conda](https://anaconda.org/conda-forge/dtreeviz) (πŸ“₯ 85K Β· ⏱️ 13.07.2023): +- [Conda](https://anaconda.org/conda-forge/lit-nlp) (πŸ“₯ 92K Β· ⏱️ 16.06.2023): ``` - conda install -c conda-forge dtreeviz + conda install -c conda-forge lit-nlp ```
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fairlearn (πŸ₯ˆ28 Β· ⭐ 1.9K) - A Python package to assess and improve fairness of machine.. MIT +
dtreeviz (πŸ₯ˆ28 Β· ⭐ 3K) - A python library for decision tree visualization and model interpretation. MIT -- [GitHub](https://github.com/fairlearn/fairlearn) (πŸ‘¨β€πŸ’» 84 Β· πŸ”€ 410 Β· πŸ“¦ 3 Β· πŸ“‹ 480 - 33% open Β· ⏱️ 24.09.2024): +- [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/fairlearn/fairlearn + git clone https://github.com/parrt/dtreeviz ``` -- [PyPi](https://pypi.org/project/fairlearn) (πŸ“₯ 160K / month Β· πŸ“¦ 55 Β· ⏱️ 19.12.2023): +- [PyPi](https://pypi.org/project/dtreeviz) (πŸ“₯ 110K / month Β· πŸ“¦ 53 Β· ⏱️ 07.07.2022): ``` - pip install fairlearn + pip install dtreeviz ``` -- [Conda](https://anaconda.org/conda-forge/fairlearn) (πŸ“₯ 37K Β· ⏱️ 20.12.2023): +- [Conda](https://anaconda.org/conda-forge/dtreeviz) (πŸ“₯ 86K Β· ⏱️ 13.07.2023): ``` - conda install -c conda-forge fairlearn + conda install -c conda-forge dtreeviz ```
Fairness 360 (πŸ₯ˆ26 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”€ 830 Β· πŸ“¦ 490 Β· πŸ“‹ 300 - 66% open Β· ⏱️ 05.07.2024): +- [GitHub](https://github.com/Trusted-AI/AIF360) (πŸ‘¨β€πŸ’» 73 Β· πŸ”€ 830 Β· πŸ“¦ 500 Β· πŸ“‹ 300 - 66% open Β· ⏱️ 05.07.2024): ``` git clone https://github.com/Trusted-AI/AIF360 ``` -- [PyPi](https://pypi.org/project/aif360) (πŸ“₯ 36K / month Β· πŸ“¦ 32 Β· ⏱️ 08.04.2024): +- [PyPi](https://pypi.org/project/aif360) (πŸ“₯ 40K / month Β· πŸ“¦ 32 Β· ⏱️ 08.04.2024): ``` pip install aif360 ``` @@ -6137,68 +6149,64 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin conda install -c conda-forge aif360 ```
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responsible-ai-widgets (πŸ₯ˆ26 Β· ⭐ 1.4K) - Responsible AI Toolbox is a suite of tools providing.. MIT +
imodels (πŸ₯ˆ26 Β· ⭐ 1.4K) - Interpretable ML package for concise, transparent, and accurate.. MIT -- [GitHub](https://github.com/microsoft/responsible-ai-toolbox) (πŸ‘¨β€πŸ’» 43 Β· πŸ”€ 340 Β· πŸ“‹ 320 - 27% open Β· ⏱️ 07.08.2024): +- [GitHub](https://github.com/csinva/imodels) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 120 Β· πŸ“¦ 110 Β· πŸ“‹ 93 - 38% open Β· ⏱️ 16.10.2024): ``` - git clone https://github.com/microsoft/responsible-ai-toolbox + git clone https://github.com/csinva/imodels ``` -- [PyPi](https://pypi.org/project/raiwidgets) (πŸ“₯ 11K / month Β· πŸ“¦ 6 Β· ⏱️ 08.07.2024): +- [PyPi](https://pypi.org/project/imodels) (πŸ“₯ 32K / month Β· πŸ“¦ 9 Β· ⏱️ 15.10.2024): ``` - pip install raiwidgets + pip install imodels ```
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LIT (πŸ₯‰25 Β· ⭐ 3.5K) - The Learning Interpretability Tool: Interactively analyze ML models to.. Apache-2 +
responsible-ai-widgets (πŸ₯ˆ26 Β· ⭐ 1.4K) - Responsible AI Toolbox is a suite of tools providing.. MIT -- [GitHub](https://github.com/PAIR-code/lit) (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 350 Β· πŸ“¦ 39 Β· πŸ“‹ 190 - 56% open Β· ⏱️ 26.06.2024): +- [GitHub](https://github.com/microsoft/responsible-ai-toolbox) (πŸ‘¨β€πŸ’» 43 Β· πŸ”€ 350 Β· πŸ“‹ 320 - 27% open Β· ⏱️ 07.08.2024): ``` - git clone https://github.com/PAIR-code/lit - ``` -- [PyPi](https://pypi.org/project/lit-nlp) (πŸ“₯ 3.7K / month Β· πŸ“¦ 3 Β· ⏱️ 26.06.2024): - ``` - pip install lit-nlp + git clone https://github.com/microsoft/responsible-ai-toolbox ``` -- [Conda](https://anaconda.org/conda-forge/lit-nlp) (πŸ“₯ 90K Β· ⏱️ 16.06.2023): +- [PyPi](https://pypi.org/project/raiwidgets) (πŸ“₯ 12K / month Β· πŸ“¦ 6 Β· ⏱️ 08.07.2024): ``` - conda install -c conda-forge lit-nlp + pip install raiwidgets ```
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CausalNex (πŸ₯‰25 Β· ⭐ 2.2K Β· πŸ’€) - A Python library that helps data scientists to infer.. Apache-2 +
iNNvestigate (πŸ₯ˆ26 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”€ 260 Β· πŸ“¦ 130 Β· πŸ“‹ 140 - 16% open Β· ⏱️ 10.02.2024): +- [GitHub](https://github.com/albermax/innvestigate) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 240 Β· πŸ“₯ 160 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“₯ 10K / month Β· πŸ“¦ 4 Β· ⏱️ 22.06.2023): +- [PyPi](https://pypi.org/project/innvestigate) (πŸ“₯ 1.3K / month Β· πŸ“¦ 2 Β· ⏱️ 12.10.2023): ``` - pip install causalnex + pip install innvestigate ```
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imodels (πŸ₯‰25 Β· ⭐ 1.4K) - Interpretable ML package for concise, transparent, and accurate.. MIT +
CausalNex (πŸ₯‰25 Β· ⭐ 2.2K Β· πŸ’€) - A Python library that helps data scientists to infer.. Apache-2 -- [GitHub](https://github.com/csinva/imodels) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 120 Β· πŸ“¦ 110 Β· πŸ“‹ 92 - 39% open Β· ⏱️ 21.09.2024): +- [GitHub](https://github.com/mckinsey/causalnex) (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 260 Β· πŸ“¦ 130 Β· πŸ“‹ 140 - 17% open Β· ⏱️ 10.02.2024): ``` - git clone https://github.com/csinva/imodels + git clone https://github.com/quantumblacklabs/causalnex ``` -- [PyPi](https://pypi.org/project/imodels) (πŸ“₯ 40K / month Β· πŸ“¦ 9 Β· ⏱️ 02.07.2024): +- [PyPi](https://pypi.org/project/causalnex) (πŸ“₯ 11K / month Β· πŸ“¦ 4 Β· ⏱️ 22.06.2023): ``` - pip install imodels + pip install causalnex ```
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iNNvestigate (πŸ₯‰25 Β· ⭐ 1.3K Β· πŸ’€) - A toolbox to iNNvestigate neural networks predictions!. BSD-2 +
keract (πŸ₯‰25 Β· ⭐ 1K Β· πŸ’€) - Layers Outputs and Gradients in Keras. Made easy. MIT -- [GitHub](https://github.com/albermax/innvestigate) (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 240 Β· πŸ“₯ 150 Β· πŸ“¦ 140 Β· πŸ“‹ 260 - 21% open Β· ⏱️ 12.10.2023): +- [GitHub](https://github.com/philipperemy/keract) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 180 Β· πŸ“¦ 230 Β· πŸ“‹ 89 - 3% open Β· ⏱️ 17.11.2023): ``` - git clone https://github.com/albermax/innvestigate + git clone https://github.com/philipperemy/keract ``` -- [PyPi](https://pypi.org/project/innvestigate) (πŸ“₯ 970 / month Β· πŸ“¦ 2 Β· ⏱️ 12.10.2023): +- [PyPi](https://pypi.org/project/keract) (πŸ“₯ 12K / month Β· πŸ“¦ 9 Β· ⏱️ 25.09.2022): ``` - pip install innvestigate + pip install keract ```
aequitas (πŸ₯‰25 Β· ⭐ 680) - Bias Auditing & Fair ML Toolkit. MIT @@ -6208,31 +6216,19 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin ``` git clone https://github.com/dssg/aequitas ``` -- [PyPi](https://pypi.org/project/aequitas) (πŸ“₯ 26K / month Β· πŸ“¦ 8 Β· ⏱️ 30.01.2024): +- [PyPi](https://pypi.org/project/aequitas) (πŸ“₯ 35K / month Β· πŸ“¦ 8 Β· ⏱️ 30.01.2024): ``` pip install aequitas ```
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keract (πŸ₯‰24 Β· ⭐ 1K Β· πŸ’€) - Layers Outputs and Gradients in Keras. Made easy. MIT - -- [GitHub](https://github.com/philipperemy/keract) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 180 Β· πŸ“¦ 230 Β· πŸ“‹ 89 - 3% open Β· ⏱️ 17.11.2023): - - ``` - git clone https://github.com/philipperemy/keract - ``` -- [PyPi](https://pypi.org/project/keract) (πŸ“₯ 6.7K / month Β· πŸ“¦ 9 Β· ⏱️ 25.09.2022): - ``` - pip install keract - ``` -
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Explainability 360 (πŸ₯‰23 Β· ⭐ 1.6K) - Interpretability and explainability of data and.. Apache-2 +
Explainability 360 (πŸ₯‰24 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“¦ 100 Β· πŸ“‹ 85 - 63% open Β· ⏱️ 16.07.2024): ``` git clone https://github.com/Trusted-AI/AIX360 ``` -- [PyPi](https://pypi.org/project/aix360) (πŸ“₯ 1.4K / month Β· πŸ“¦ 1 Β· ⏱️ 31.07.2023): +- [PyPi](https://pypi.org/project/aix360) (πŸ“₯ 2.6K / month Β· πŸ“¦ 1 Β· ⏱️ 31.07.2023): ``` pip install aix360 ``` @@ -6244,7 +6240,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin ``` git clone https://github.com/PAIR-code/what-if-tool ``` -- [PyPi](https://pypi.org/project/witwidget) (πŸ“₯ 8.8K / month Β· πŸ“¦ 6 Β· ⏱️ 12.10.2021): +- [PyPi](https://pypi.org/project/witwidget) (πŸ“₯ 10K / month Β· πŸ“¦ 6 Β· ⏱️ 12.10.2021): ``` pip install witwidget ``` @@ -6252,7 +6248,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin ``` conda install -c conda-forge tensorboard-plugin-wit ``` -- [npm](https://www.npmjs.com/package/wit-widget) (πŸ“₯ 580 / month Β· πŸ“¦ 3 Β· ⏱️ 12.10.2021): +- [npm](https://www.npmjs.com/package/wit-widget) (πŸ“₯ 590 / month Β· πŸ“¦ 3 Β· ⏱️ 12.10.2021): ``` npm install wit-widget ``` @@ -6264,11 +6260,11 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin ``` git clone https://github.com/jalammar/ecco ``` -- [PyPi](https://pypi.org/project/ecco) (πŸ“₯ 1.1K / month Β· πŸ“¦ 1 Β· ⏱️ 09.01.2022): +- [PyPi](https://pypi.org/project/ecco) (πŸ“₯ 1.6K / month Β· πŸ“¦ 1 Β· ⏱️ 09.01.2022): ``` pip install ecco ``` -- [Conda](https://anaconda.org/conda-forge/ecco) (πŸ“₯ 5.5K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/ecco) (πŸ“₯ 5.6K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge ecco ``` @@ -6280,19 +6276,19 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin ``` git clone https://github.com/parrt/random-forest-importances ``` -- [PyPi](https://pypi.org/project/rfpimp) (πŸ“₯ 12K / month Β· πŸ“¦ 5 Β· ⏱️ 28.01.2021): +- [PyPi](https://pypi.org/project/rfpimp) (πŸ“₯ 13K / month Β· πŸ“¦ 5 Β· ⏱️ 28.01.2021): ``` pip install rfpimp ```
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DiCE (πŸ₯‰20 Β· ⭐ 1.3K) - Generate Diverse Counterfactual Explanations for any machine.. MIT +
DiCE (πŸ₯‰20 Β· ⭐ 1.4K) - 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): +- [GitHub](https://github.com/interpretml/DiCE) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 190 Β· πŸ“‹ 180 - 48% open Β· ⏱️ 17.04.2024): ``` git clone https://github.com/interpretml/DiCE ``` -- [PyPi](https://pypi.org/project/dice-ml) (πŸ“₯ 34K / month Β· πŸ“¦ 6 Β· ⏱️ 27.10.2023): +- [PyPi](https://pypi.org/project/dice-ml) (πŸ“₯ 31K / month Β· πŸ“¦ 6 Β· ⏱️ 27.10.2023): ``` pip install dice-ml ``` @@ -6304,7 +6300,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin ``` git clone https://github.com/tensorflow/fairness-indicators ``` -- [PyPi](https://pypi.org/project/fairness-indicators) (πŸ“₯ 2.3K / month Β· ⏱️ 26.04.2024): +- [PyPi](https://pypi.org/project/fairness-indicators) (πŸ“₯ 3.4K / month Β· ⏱️ 26.04.2024): ``` pip install fairness-indicators ``` @@ -6316,19 +6312,19 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin ``` git clone https://github.com/aerdem4/lofo-importance ``` -- [PyPi](https://pypi.org/project/lofo-importance) (πŸ“₯ 3.6K / month Β· πŸ“¦ 4 Β· ⏱️ 16.01.2024): +- [PyPi](https://pypi.org/project/lofo-importance) (πŸ“₯ 3.8K / month Β· πŸ“¦ 4 Β· ⏱️ 16.01.2024): ``` pip install lofo-importance ```
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ExplainX.ai (πŸ₯‰16 Β· ⭐ 410) - Explainable AI framework for data scientists. Explain & debug any.. MIT +
ExplainX.ai (πŸ₯‰16 Β· ⭐ 420) - Explainable AI framework for data scientists. Explain & debug any.. MIT -- [GitHub](https://github.com/explainX/explainx) (πŸ‘¨β€πŸ’» 5 Β· πŸ”€ 52 Β· πŸ“₯ 18 Β· πŸ“‹ 39 - 25% open Β· ⏱️ 21.08.2024): +- [GitHub](https://github.com/explainX/explainx) (πŸ‘¨β€πŸ’» 5 Β· πŸ”€ 52 Β· πŸ“₯ 19 Β· πŸ“‹ 39 - 25% open Β· ⏱️ 21.08.2024): ``` git clone https://github.com/explainX/explainx ``` -- [PyPi](https://pypi.org/project/explainx) (πŸ“₯ 1.7K / month Β· ⏱️ 04.02.2021): +- [PyPi](https://pypi.org/project/explainx) (πŸ“₯ 2.6K / month Β· ⏱️ 04.02.2021): ``` pip install explainx ``` @@ -6340,7 +6336,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin ``` git clone https://github.com/interpretml/interpret-text ``` -- [PyPi](https://pypi.org/project/interpret-text) (πŸ“₯ 310 / month Β· ⏱️ 07.12.2021): +- [PyPi](https://pypi.org/project/interpret-text) (πŸ“₯ 460 / month Β· ⏱️ 07.12.2021): ``` pip install interpret-text ``` @@ -6349,18 +6345,18 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin - Lime (πŸ₯‡32 Β· ⭐ 12K Β· πŸ’€) - Lime: Explaining the predictions of any machine learning classifier. BSD-2 - Deep Checks (πŸ₯ˆ29 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 +- scikit-plot (πŸ₯ˆ29 Β· ⭐ 2.4K Β· πŸ’€) - An intuitive library to add plotting functionality to.. MIT +- DALEX (πŸ₯ˆ28 Β· ⭐ 1.4K) - moDel Agnostic Language for Exploration and eXplanation. ❗️GPL-3.0 - yellowbrick (πŸ₯ˆ27 Β· ⭐ 4.3K Β· πŸ’€) - Visual analysis and diagnostic tools to facilitate.. Apache-2 -- DALEX (πŸ₯ˆ27 Β· ⭐ 1.4K) - moDel Agnostic Language for Exploration and eXplanation. ❗️GPL-3.0 +- Lucid (πŸ₯ˆ26 Β· ⭐ 4.7K Β· πŸ’€) - A collection of infrastructure and tools for research in.. Apache-2 - eli5 (πŸ₯ˆ26 Β· ⭐ 2.8K Β· πŸ’€) - A library for debugging/inspecting machine learning classifiers and.. MIT - Alibi (πŸ₯ˆ26 Β· ⭐ 2.4K) - Algorithms for explaining machine learning models. ❗️Intel -- Lucid (πŸ₯‰25 Β· ⭐ 4.7K 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 - checklist (πŸ₯‰24 Β· ⭐ 2K Β· πŸ’€) - Beyond Accuracy: Behavioral Testing of NLP models with CheckList. MIT - tf-explain (πŸ₯‰22 Β· ⭐ 1K Β· πŸ’€) - Interpretability Methods for tf.keras models with Tensorflow.. MIT -- deeplift (πŸ₯‰21 Β· ⭐ 820 Β· πŸ’€) - Public facing deeplift repo. MIT +- deeplift (πŸ₯‰22 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· ⭐ 540 Β· πŸ“ˆ) - Quantus is an eXplainable AI toolkit for responsible evaluation.. ❗️GPL-3.0 +- Quantus (πŸ₯‰21 Β· ⭐ 550) - Quantus is an eXplainable AI toolkit for responsible evaluation of.. ❗️GPL-3.0 - XAI (πŸ₯‰19 Β· ⭐ 1.1K Β· πŸ’€) - XAI - An eXplainability toolbox for machine learning. MIT - tcav (πŸ₯‰19 Β· ⭐ 630 Β· πŸ’€) - Code for the TCAV ML interpretability project. Apache-2 - sklearn-evaluation (πŸ₯‰19 Β· ⭐ 460 Β· πŸ’€) - Machine learning model evaluation made easy: plots,.. MIT @@ -6368,9 +6364,9 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin - Anchor (πŸ₯‰16 Β· ⭐ 800 Β· πŸ’€) - Code for High-Precision Model-Agnostic Explanations paper. BSD-2 - FlashTorch (πŸ₯‰16 Β· ⭐ 730 Β· πŸ’€) - Visualization toolkit for neural networks in PyTorch! Demo --. MIT - Skater (πŸ₯‰14 Β· ⭐ 1.1K Β· πŸ’€) - Python Library for Model Interpretation/Explanations. ❗️UPL-1.0 +- bias-detector (πŸ₯‰14 Β· ⭐ 44 Β· πŸ’€) - Bias Detector is a python package for detecting bias in machine.. MIT - Attribution Priors (πŸ₯‰13 Β· ⭐ 120 Β· πŸ’€) - Tools for training explainable models using.. MIT -- bias-detector (πŸ₯‰13 Β· ⭐ 44 Β· πŸ’€) - Bias Detector is a python package for detecting bias in machine.. MIT -- contextual-ai (πŸ₯‰12 Β· ⭐ 86 Β· πŸ’€) - Contextual AI adds explainability to different stages of.. Apache-2 +- contextual-ai (πŸ₯‰13 Β· ⭐ 86 Β· πŸ’€) - Contextual AI adds explainability to different stages of.. Apache-2

@@ -6384,55 +6380,55 @@ _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarit
Faiss (πŸ₯‡41 Β· ⭐ 31K) - A library for efficient similarity search and clustering of dense vectors. MIT -- [GitHub](https://github.com/facebookresearch/faiss) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 3.6K Β· πŸ“¦ 4K Β· πŸ“‹ 2.5K - 9% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/facebookresearch/faiss) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 3.6K Β· πŸ“¦ 4.1K Β· πŸ“‹ 2.5K - 9% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/facebookresearch/faiss ``` -- [PyPi](https://pypi.org/project/pymilvus) (πŸ“₯ 1M / month Β· πŸ“¦ 170 Β· ⏱️ 25.09.2024): +- [PyPi](https://pypi.org/project/pymilvus) (πŸ“₯ 1.1M / month Β· πŸ“¦ 170 Β· ⏱️ 12.10.2024): ``` pip install pymilvus ``` -- [Conda](https://anaconda.org/conda-forge/faiss) (πŸ“₯ 1.7M Β· ⏱️ 09.08.2024): +- [Conda](https://anaconda.org/conda-forge/faiss) (πŸ“₯ 1.8M Β· ⏱️ 09.08.2024): ``` conda install -c conda-forge faiss ```
Milvus (πŸ₯‡41 Β· ⭐ 30K) - A cloud-native vector database, storage for next generation AI.. Apache-2 -- [GitHub](https://github.com/milvus-io/milvus) (πŸ‘¨β€πŸ’» 290 Β· πŸ”€ 2.8K Β· πŸ“₯ 270K Β· πŸ“‹ 12K - 6% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/milvus-io/milvus) (πŸ‘¨β€πŸ’» 290 Β· πŸ”€ 2.9K Β· πŸ“₯ 270K Β· πŸ“‹ 12K - 6% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/milvus-io/milvus ``` -- [PyPi](https://pypi.org/project/pymilvus) (πŸ“₯ 1M / month Β· πŸ“¦ 170 Β· ⏱️ 25.09.2024): +- [PyPi](https://pypi.org/project/pymilvus) (πŸ“₯ 1.1M / month Β· πŸ“¦ 170 Β· ⏱️ 12.10.2024): ``` pip install pymilvus ``` -- [Docker Hub](https://hub.docker.com/r/milvusdb/milvus) (πŸ“₯ 67M Β· ⭐ 63 Β· ⏱️ 08.10.2024): +- [Docker Hub](https://hub.docker.com/r/milvusdb/milvus) (πŸ“₯ 67M Β· ⭐ 64 Β· ⏱️ 24.10.2024): ``` docker pull milvusdb/milvus ```
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“¦ 4.3K Β· πŸ“‹ 400 - 14% open Β· ⏱️ 29.07.2024): +- [GitHub](https://github.com/spotify/annoy) (πŸ‘¨β€πŸ’» 88 Β· πŸ”€ 1.2K Β· πŸ“¦ 4.3K Β· πŸ“‹ 400 - 14% open Β· ⏱️ 29.07.2024): ``` git clone https://github.com/spotify/annoy ``` -- [PyPi](https://pypi.org/project/annoy) (πŸ“₯ 1M / month Β· πŸ“¦ 200 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“₯ 530K Β· ⏱️ 05.09.2024): +- [Conda](https://anaconda.org/conda-forge/python-annoy) (πŸ“₯ 540K Β· ⏱️ 05.09.2024): ``` conda install -c conda-forge python-annoy ```
hnswlib (πŸ₯ˆ32 Β· ⭐ 4.3K) - Header-only C++/python library for fast approximate nearest neighbors. Apache-2 -- [GitHub](https://github.com/nmslib/hnswlib) (πŸ‘¨β€πŸ’» 72 Β· πŸ”€ 620 Β· πŸ“¦ 7K Β· πŸ“‹ 380 - 57% open Β· ⏱️ 17.06.2024): +- [GitHub](https://github.com/nmslib/hnswlib) (πŸ‘¨β€πŸ’» 72 Β· πŸ”€ 620 Β· πŸ“¦ 7.1K Β· πŸ“‹ 380 - 57% open Β· ⏱️ 17.06.2024): ``` git clone https://github.com/nmslib/hnswlib @@ -6453,7 +6449,7 @@ _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarit ``` git clone https://github.com/nmslib/nmslib ``` -- [PyPi](https://pypi.org/project/nmslib) (πŸ“₯ 230K / month Β· πŸ“¦ 63 Β· ⏱️ 03.02.2021): +- [PyPi](https://pypi.org/project/nmslib) (πŸ“₯ 340K / month Β· πŸ“¦ 63 Β· ⏱️ 03.02.2021): ``` pip install nmslib ``` @@ -6464,16 +6460,16 @@ _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarit
USearch (πŸ₯‰30 Β· ⭐ 2.2K) - Fast Open-Source Search & Clustering engine for Vectors & Strings in.. Apache-2 -- [GitHub](https://github.com/unum-cloud/usearch) (πŸ‘¨β€πŸ’» 54 Β· πŸ”€ 130 Β· πŸ“₯ 28K Β· πŸ“¦ 120 Β· πŸ“‹ 160 - 33% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/unum-cloud/usearch) (πŸ‘¨β€πŸ’» 54 Β· πŸ”€ 130 Β· πŸ“₯ 29K Β· πŸ“¦ 130 Β· πŸ“‹ 160 - 33% open Β· ⏱️ 10.10.2024): ``` git clone https://github.com/unum-cloud/usearch ``` -- [PyPi](https://pypi.org/project/usearch) (πŸ“₯ 170K / month Β· πŸ“¦ 21 Β· ⏱️ 10.10.2024): +- [PyPi](https://pypi.org/project/usearch) (πŸ“₯ 200K / month Β· πŸ“¦ 21 Β· ⏱️ 10.10.2024): ``` pip install usearch ``` -- [npm](https://www.npmjs.com/package/usearch) (πŸ“₯ 7K / month Β· πŸ“¦ 14 Β· ⏱️ 10.10.2024): +- [npm](https://www.npmjs.com/package/usearch) (πŸ“₯ 7.3K / month Β· πŸ“¦ 14 Β· ⏱️ 10.10.2024): ``` npm install usearch ``` @@ -6484,28 +6480,28 @@ _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarit
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”€ 110 Β· πŸ“¦ 8K Β· πŸ“‹ 140 - 52% open Β· ⏱️ 17.06.2024): +- [GitHub](https://github.com/lmcinnes/pynndescent) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 100 Β· πŸ“¦ 8.2K Β· πŸ“‹ 140 - 52% open Β· ⏱️ 17.06.2024): ``` git clone https://github.com/lmcinnes/pynndescent ``` -- [PyPi](https://pypi.org/project/pynndescent) (πŸ“₯ 1.4M / month Β· πŸ“¦ 160 Β· ⏱️ 17.06.2024): +- [PyPi](https://pypi.org/project/pynndescent) (πŸ“₯ 1.6M / month Β· πŸ“¦ 160 Β· ⏱️ 17.06.2024): ``` pip install pynndescent ``` -- [Conda](https://anaconda.org/conda-forge/pynndescent) (πŸ“₯ 2M Β· ⏱️ 17.06.2024): +- [Conda](https://anaconda.org/conda-forge/pynndescent) (πŸ“₯ 2.1M Β· ⏱️ 17.06.2024): ``` conda install -c conda-forge pynndescent ```
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NGT (πŸ₯‰22 Β· ⭐ 1.2K) - Nearest Neighbor Search with Neighborhood Graph and Tree for High-.. Apache-2 +
NGT (πŸ₯‰21 Β· ⭐ 1.2K) - Nearest Neighbor Search with Neighborhood Graph and Tree for High-.. Apache-2 -- [GitHub](https://github.com/yahoojapan/NGT) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 110 Β· πŸ“‹ 140 - 13% open Β· ⏱️ 18.09.2024): +- [GitHub](https://github.com/yahoojapan/NGT) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 110 Β· πŸ“‹ 140 - 14% open Β· ⏱️ 18.09.2024): ``` git clone https://github.com/yahoojapan/NGT ``` -- [PyPi](https://pypi.org/project/ngt) (πŸ“₯ 4.4K / month Β· πŸ“¦ 8 Β· ⏱️ 06.12.2023): +- [PyPi](https://pypi.org/project/ngt) (πŸ“₯ 6.2K / month Β· πŸ“¦ 8 Β· ⏱️ 06.12.2023): ``` pip install ngt ``` @@ -6527,28 +6523,28 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes
PyMC3 (πŸ₯‡41 Β· ⭐ 8.7K) - Bayesian Modeling and Probabilistic Programming in Python. Apache-2 -- [GitHub](https://github.com/pymc-devs/pymc) (πŸ‘¨β€πŸ’» 500 Β· πŸ”€ 2K Β· πŸ“₯ 2K Β· πŸ“¦ 4.3K Β· πŸ“‹ 3.4K - 9% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/pymc-devs/pymc) (πŸ‘¨β€πŸ’» 500 Β· πŸ”€ 2K Β· πŸ“₯ 2K Β· πŸ“¦ 4.4K Β· πŸ“‹ 3.4K - 9% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/pymc-devs/pymc ``` -- [PyPi](https://pypi.org/project/pymc3) (πŸ“₯ 280K / month Β· πŸ“¦ 190 Β· ⏱️ 31.05.2024): +- [PyPi](https://pypi.org/project/pymc3) (πŸ“₯ 240K / month Β· πŸ“¦ 190 Β· ⏱️ 31.05.2024): ``` pip install pymc3 ``` -- [Conda](https://anaconda.org/conda-forge/pymc3) (πŸ“₯ 600K Β· ⏱️ 02.06.2024): +- [Conda](https://anaconda.org/conda-forge/pymc3) (πŸ“₯ 610K Β· ⏱️ 02.06.2024): ``` conda install -c conda-forge pymc3 ```
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tensorflow-probability (πŸ₯‡35 Β· ⭐ 4.3K) - Probabilistic reasoning and statistical analysis in.. Apache-2 +
tensorflow-probability (πŸ₯‡36 Β· ⭐ 4.3K) - Probabilistic reasoning and statistical analysis in.. Apache-2 -- [GitHub](https://github.com/tensorflow/probability) (πŸ‘¨β€πŸ’» 500 Β· πŸ”€ 1.1K Β· πŸ“¦ 2 Β· πŸ“‹ 1.4K - 47% open Β· ⏱️ 03.10.2024): +- [GitHub](https://github.com/tensorflow/probability) (πŸ‘¨β€πŸ’» 500 Β· πŸ”€ 1.1K Β· πŸ“¦ 2 Β· πŸ“‹ 1.4K - 47% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/tensorflow/probability ``` -- [PyPi](https://pypi.org/project/tensorflow-probability) (πŸ“₯ 1.6M / month Β· πŸ“¦ 610 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 ``` @@ -6559,12 +6555,12 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes
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”€ 980 Β· πŸ“‹ 1.1K - 23% open Β· ⏱️ 28.09.2024): +- [GitHub](https://github.com/pyro-ppl/pyro) (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 980 Β· πŸ“‹ 1.1K - 23% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/pyro-ppl/pyro ``` -- [PyPi](https://pypi.org/project/pyro-ppl) (πŸ“₯ 320K / month Β· πŸ“¦ 190 Β· ⏱️ 02.06.2024): +- [PyPi](https://pypi.org/project/pyro-ppl) (πŸ“₯ 380K / month Β· πŸ“¦ 190 Β· ⏱️ 02.06.2024): ``` pip install pyro-ppl ``` @@ -6573,26 +6569,26 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes conda install -c conda-forge pyro-ppl ```
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pgmpy (πŸ₯ˆ33 Β· ⭐ 2.7K) - Python Library for learning (Structure and Parameter), inference.. MIT +
pgmpy (πŸ₯‡34 Β· ⭐ 2.7K) - Python Library for learning (Structure and Parameter), inference.. MIT -- [GitHub](https://github.com/pgmpy/pgmpy) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 700 Β· πŸ“₯ 540 Β· πŸ“¦ 1.2K Β· πŸ“‹ 930 - 31% open Β· ⏱️ 02.10.2024): +- [GitHub](https://github.com/pgmpy/pgmpy) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 700 Β· πŸ“₯ 540 Β· πŸ“¦ 1.2K Β· πŸ“‹ 930 - 31% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/pgmpy/pgmpy ``` -- [PyPi](https://pypi.org/project/pgmpy) (πŸ“₯ 120K / month Β· πŸ“¦ 53 Β· ⏱️ 09.08.2024): +- [PyPi](https://pypi.org/project/pgmpy) (πŸ“₯ 130K / month Β· πŸ“¦ 53 Β· ⏱️ 09.08.2024): ``` pip install pgmpy ```
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GPyTorch (πŸ₯ˆ32 Β· ⭐ 3.5K) - A highly efficient implementation of Gaussian Processes in PyTorch. MIT +
GPyTorch (πŸ₯ˆ32 Β· ⭐ 3.6K) - A highly efficient implementation of Gaussian Processes in PyTorch. MIT - [GitHub](https://github.com/cornellius-gp/gpytorch) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 550 Β· πŸ“¦ 2.4K Β· πŸ“‹ 1.3K - 27% open Β· ⏱️ 27.09.2024): ``` git clone https://github.com/cornellius-gp/gpytorch ``` -- [PyPi](https://pypi.org/project/gpytorch) (πŸ“₯ 260K / month Β· πŸ“¦ 170 Β· ⏱️ 06.09.2024): +- [PyPi](https://pypi.org/project/gpytorch) (πŸ“₯ 290K / month Β· πŸ“¦ 170 Β· ⏱️ 06.09.2024): ``` pip install gpytorch ``` @@ -6601,34 +6597,18 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes conda install -c conda-forge gpytorch ```
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SALib (πŸ₯ˆ32 Β· ⭐ 880) - Sensitivity Analysis Library in Python. Contains Sobol, Morris, FAST, and.. MIT - -- [GitHub](https://github.com/SALib/SALib) (πŸ‘¨β€πŸ’» 48 Β· πŸ”€ 230 Β· πŸ“¦ 1.3K Β· πŸ“‹ 340 - 15% open Β· ⏱️ 09.10.2024): - - ``` - git clone https://github.com/SALib/SALib - ``` -- [PyPi](https://pypi.org/project/salib) (πŸ“₯ 490K / month Β· πŸ“¦ 130 Β· ⏱️ 19.08.2024): - ``` - pip install salib - ``` -- [Conda](https://anaconda.org/conda-forge/salib) (πŸ“₯ 180K Β· ⏱️ 20.09.2024): - ``` - conda install -c conda-forge salib - ``` -
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hmmlearn (πŸ₯ˆ31 Β· ⭐ 3K) - Hidden Markov Models in Python, with scikit-learn like API. BSD-3 +
hmmlearn (πŸ₯ˆ31 Β· ⭐ 3.1K) - Hidden Markov Models in Python, with scikit-learn like API. BSD-3 - [GitHub](https://github.com/hmmlearn/hmmlearn) (πŸ‘¨β€πŸ’» 49 Β· πŸ”€ 740 Β· πŸ“¦ 2.8K Β· πŸ“‹ 440 - 15% open Β· ⏱️ 07.10.2024): ``` git clone https://github.com/hmmlearn/hmmlearn ``` -- [PyPi](https://pypi.org/project/hmmlearn) (πŸ“₯ 770K / month Β· πŸ“¦ 87 Β· ⏱️ 02.03.2024): +- [PyPi](https://pypi.org/project/hmmlearn) (πŸ“₯ 670K / month Β· πŸ“¦ 87 Β· ⏱️ 02.03.2024): ``` pip install hmmlearn ``` -- [Conda](https://anaconda.org/conda-forge/hmmlearn) (πŸ“₯ 280K Β· ⏱️ 11.09.2024): +- [Conda](https://anaconda.org/conda-forge/hmmlearn) (πŸ“₯ 290K Β· ⏱️ 11.09.2024): ``` conda install -c conda-forge hmmlearn ``` @@ -6640,7 +6620,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes ``` git clone https://github.com/dfm/emcee ``` -- [PyPi](https://pypi.org/project/emcee) (πŸ“₯ 1.4M / month Β· πŸ“¦ 440 Β· ⏱️ 19.04.2024): +- [PyPi](https://pypi.org/project/emcee) (πŸ“₯ 1.3M / month Β· πŸ“¦ 440 Β· ⏱️ 19.04.2024): ``` pip install emcee ``` @@ -6649,9 +6629,25 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes conda install -c conda-forge emcee ```
+
SALib (πŸ₯ˆ31 Β· ⭐ 880) - Sensitivity Analysis Library in Python. Contains Sobol, Morris, FAST, and.. MIT + +- [GitHub](https://github.com/SALib/SALib) (πŸ‘¨β€πŸ’» 48 Β· πŸ”€ 230 Β· πŸ“¦ 1.3K Β· πŸ“‹ 340 - 15% open Β· ⏱️ 10.10.2024): + + ``` + git clone https://github.com/SALib/SALib + ``` +- [PyPi](https://pypi.org/project/salib) (πŸ“₯ 320K / month Β· πŸ“¦ 130 Β· ⏱️ 19.08.2024): + ``` + pip install salib + ``` +- [Conda](https://anaconda.org/conda-forge/salib) (πŸ“₯ 190K Β· ⏱️ 20.09.2024): + ``` + conda install -c conda-forge salib + ``` +
pandas-ta (πŸ₯‰30 Β· ⭐ 5.3K) - Technical Analysis Indicators - Pandas TA is an easy to use.. MIT -- [GitHub](https://github.com/twopirllc/pandas-ta) (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 1K Β· πŸ“¦ 4.2K Β· πŸ“‹ 590 - 19% open Β· ⏱️ 24.06.2024): +- [GitHub](https://github.com/twopirllc/pandas-ta) (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 1K Β· πŸ“¦ 4.3K Β· πŸ“‹ 590 - 19% open Β· ⏱️ 24.06.2024): ``` git clone https://github.com/twopirllc/pandas-ta @@ -6672,23 +6668,23 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes ``` git clone https://github.com/GPflow/GPflow ``` -- [PyPi](https://pypi.org/project/gpflow) (πŸ“₯ 76K / month Β· πŸ“¦ 35 Β· ⏱️ 17.06.2024): +- [PyPi](https://pypi.org/project/gpflow) (πŸ“₯ 73K / month Β· πŸ“¦ 35 Β· ⏱️ 17.06.2024): ``` pip install gpflow ``` -- [Conda](https://anaconda.org/conda-forge/gpflow) (πŸ“₯ 34K Β· ⏱️ 26.06.2024): +- [Conda](https://anaconda.org/conda-forge/gpflow) (πŸ“₯ 35K Β· ⏱️ 26.06.2024): ``` conda install -c conda-forge gpflow ```
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patsy (πŸ₯‰30 Β· ⭐ 940 Β· πŸ’€) - Describing statistical models in Python using symbolic formulas. BSD-2 +
patsy (πŸ₯‰30 Β· ⭐ 950 Β· πŸ’€) - Describing statistical models in Python using symbolic formulas. BSD-2 -- [GitHub](https://github.com/pydata/patsy) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 100 Β· πŸ“¦ 110K Β· πŸ“‹ 150 - 46% open Β· ⏱️ 04.01.2024): +- [GitHub](https://github.com/pydata/patsy) (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 100 Β· πŸ“¦ 110K Β· πŸ“‹ 160 - 47% open Β· ⏱️ 04.01.2024): ``` git clone https://github.com/pydata/patsy ``` -- [PyPi](https://pypi.org/project/patsy) (πŸ“₯ 16M / month Β· πŸ“¦ 530 Β· ⏱️ 04.01.2024): +- [PyPi](https://pypi.org/project/patsy) (πŸ“₯ 15M / month Β· πŸ“¦ 530 Β· ⏱️ 04.01.2024): ``` pip install patsy ``` @@ -6697,46 +6693,46 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes conda install -c conda-forge patsy ```
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pomegranate (πŸ₯‰29 Β· ⭐ 3.4K) - Fast, flexible and easy to use probabilistic modelling in Python. MIT +
PyStan (πŸ₯‰28 Β· ⭐ 340) - PyStan, a Python interface to Stan, a platform for statistical modeling... ISC -- [GitHub](https://github.com/jmschrei/pomegranate) (πŸ‘¨β€πŸ’» 75 Β· πŸ”€ 590 Β· πŸ“¦ 1.2K Β· πŸ“‹ 780 - 2% open Β· ⏱️ 11.07.2024): +- [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/jmschrei/pomegranate + git clone https://github.com/stan-dev/pystan ``` -- [PyPi](https://pypi.org/project/pomegranate) (πŸ“₯ 18K / month Β· πŸ“¦ 59 Β· ⏱️ 11.07.2024): +- [PyPi](https://pypi.org/project/pystan) (πŸ“₯ 740K / month Β· πŸ“¦ 160 Β· ⏱️ 03.07.2024): ``` - pip install pomegranate + pip install pystan ``` -- [Conda](https://anaconda.org/conda-forge/pomegranate) (πŸ“₯ 170K Β· ⏱️ 10.12.2023): +- [Conda](https://anaconda.org/conda-forge/pystan) (πŸ“₯ 2.9M Β· ⏱️ 16.06.2023): ``` - conda install -c conda-forge pomegranate + conda install -c conda-forge pystan ```
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PyStan (πŸ₯‰28 Β· ⭐ 340) - PyStan, a Python interface to Stan, a platform for statistical modeling... ISC +
pomegranate (πŸ₯‰27 Β· ⭐ 3.4K Β· πŸ“‰) - Fast, flexible and easy to use probabilistic modelling in Python. MIT -- [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): +- [GitHub](https://github.com/jmschrei/pomegranate) (πŸ‘¨β€πŸ’» 75 Β· πŸ”€ 590 Β· πŸ“‹ 780 - 2% open Β· ⏱️ 18.10.2024): ``` - git clone https://github.com/stan-dev/pystan + git clone https://github.com/jmschrei/pomegranate ``` -- [PyPi](https://pypi.org/project/pystan) (πŸ“₯ 750K / month Β· πŸ“¦ 160 Β· ⏱️ 03.07.2024): +- [PyPi](https://pypi.org/project/pomegranate) (πŸ“₯ 26K / month Β· πŸ“¦ 59 Β· ⏱️ 18.10.2024): ``` - pip install pystan + pip install pomegranate ``` -- [Conda](https://anaconda.org/conda-forge/pystan) (πŸ“₯ 2.9M Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/pomegranate) (πŸ“₯ 180K Β· ⏱️ 10.12.2023): ``` - conda install -c conda-forge pystan + conda install -c conda-forge pomegranate ```
bambi (πŸ₯‰26 Β· ⭐ 1.1K) - BAyesian Model-Building Interface (Bambi) in Python. MIT -- [GitHub](https://github.com/bambinos/bambi) (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 120 Β· πŸ“¦ 150 Β· πŸ“‹ 410 - 19% open Β· ⏱️ 26.09.2024): +- [GitHub](https://github.com/bambinos/bambi) (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 120 Β· πŸ“¦ 150 Β· πŸ“‹ 420 - 19% open Β· ⏱️ 26.09.2024): ``` git clone https://github.com/bambinos/bambi ``` -- [PyPi](https://pypi.org/project/bambi) (πŸ“₯ 31K / month Β· πŸ“¦ 10 Β· ⏱️ 10.07.2024): +- [PyPi](https://pypi.org/project/bambi) (πŸ“₯ 35K / month Β· πŸ“¦ 10 Β· ⏱️ 10.07.2024): ``` pip install bambi ``` @@ -6745,42 +6741,42 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes conda install -c conda-forge bambi ```
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scikit-posthocs (πŸ₯‰26 Β· ⭐ 340 Β· πŸ“ˆ) - Multiple Pairwise Comparisons (Post Hoc) Tests in.. MIT +
scikit-posthocs (πŸ₯‰26 Β· ⭐ 340) - Multiple Pairwise Comparisons (Post Hoc) Tests in Python. MIT -- [GitHub](https://github.com/maximtrp/scikit-posthocs) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 40 Β· πŸ“₯ 64 Β· πŸ“¦ 840 Β· πŸ“‹ 58 - 10% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/maximtrp/scikit-posthocs) (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 40 Β· πŸ“₯ 64 Β· πŸ“¦ 860 Β· πŸ“‹ 62 - 9% open Β· ⏱️ 20.10.2024): ``` git clone https://github.com/maximtrp/scikit-posthocs ``` -- [PyPi](https://pypi.org/project/scikit-posthocs) (πŸ“₯ 80K / month Β· πŸ“¦ 54 Β· ⏱️ 09.10.2024): +- [PyPi](https://pypi.org/project/scikit-posthocs) (πŸ“₯ 83K / month Β· πŸ“¦ 54 Β· ⏱️ 20.10.2024): ``` pip install scikit-posthocs ``` -- [Conda](https://anaconda.org/conda-forge/scikit-posthocs) (πŸ“₯ 970K Β· ⏱️ 10.10.2024): +- [Conda](https://anaconda.org/conda-forge/scikit-posthocs) (πŸ“₯ 970K Β· ⏱️ 24.10.2024): ``` conda install -c conda-forge scikit-posthocs ```
Orbit (πŸ₯‰23 Β· ⭐ 1.9K) - A Python package for Bayesian forecasting with object-oriented design.. Apache-2 -- [GitHub](https://github.com/uber/orbit) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 140 Β· πŸ“¦ 63 Β· πŸ“‹ 400 - 12% open Β· ⏱️ 10.07.2024): +- [GitHub](https://github.com/uber/orbit) (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 140 Β· πŸ“¦ 64 Β· πŸ“‹ 400 - 12% open Β· ⏱️ 10.07.2024): ``` git clone https://github.com/uber/orbit ``` -- [PyPi](https://pypi.org/project/orbit-ml) (πŸ“₯ 14K / month Β· πŸ“¦ 1 Β· ⏱️ 01.04.2024): +- [PyPi](https://pypi.org/project/orbit-ml) (πŸ“₯ 19K / month Β· πŸ“¦ 1 Β· ⏱️ 01.04.2024): ``` pip install orbit-ml ```
Baal (πŸ₯‰22 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“¦ 61 Β· πŸ“‹ 110 - 17% open Β· ⏱️ 27.06.2024): +- [GitHub](https://github.com/baal-org/baal) (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 86 Β· πŸ“¦ 62 Β· πŸ“‹ 110 - 17% open Β· ⏱️ 27.06.2024): ``` git clone https://github.com/baal-org/baal ``` -- [PyPi](https://pypi.org/project/baal) (πŸ“₯ 2.7K / month Β· πŸ“¦ 2 Β· ⏱️ 11.06.2024): +- [PyPi](https://pypi.org/project/baal) (πŸ“₯ 5.3K / month Β· πŸ“¦ 2 Β· ⏱️ 11.06.2024): ``` pip install baal ``` @@ -6806,52 +6802,52 @@ _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· ⭐ 4.8K) - Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning.. MIT +
ART (πŸ₯‡35 Β· ⭐ 4.8K) - 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”€ 1.2K Β· πŸ“¦ 600 Β· πŸ“‹ 900 - 15% open Β· ⏱️ 07.10.2024): +- [GitHub](https://github.com/Trusted-AI/adversarial-robustness-toolbox) (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 1.2K Β· πŸ“¦ 600 Β· πŸ“‹ 900 - 15% open Β· ⏱️ 22.10.2024): ``` git clone https://github.com/Trusted-AI/adversarial-robustness-toolbox ``` -- [PyPi](https://pypi.org/project/adversarial-robustness-toolbox) (πŸ“₯ 43K / month Β· πŸ“¦ 20 Β· ⏱️ 02.10.2024): +- [PyPi](https://pypi.org/project/adversarial-robustness-toolbox) (πŸ“₯ 78K / month Β· πŸ“¦ 20 Β· ⏱️ 02.10.2024): ``` pip install adversarial-robustness-toolbox ``` -- [Conda](https://anaconda.org/conda-forge/adversarial-robustness-toolbox) (πŸ“₯ 50K Β· ⏱️ 03.10.2024): +- [Conda](https://anaconda.org/conda-forge/adversarial-robustness-toolbox) (πŸ“₯ 51K Β· ⏱️ 03.10.2024): ``` conda install -c conda-forge adversarial-robustness-toolbox ```
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Foolbox (πŸ₯ˆ27 Β· ⭐ 2.7K Β· πŸ’€) - A Python toolbox to create adversarial examples that fool neural.. MIT +
TextAttack (πŸ₯ˆ27 Β· ⭐ 2.9K) - TextAttack is a Python framework for adversarial attacks, data.. MIT -- [GitHub](https://github.com/bethgelab/foolbox) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 420 Β· πŸ“¦ 630 Β· πŸ“‹ 370 - 5% open Β· ⏱️ 04.03.2024): +- [GitHub](https://github.com/QData/TextAttack) (πŸ‘¨β€πŸ’» 66 Β· πŸ”€ 380 Β· πŸ“¦ 310 Β· πŸ“‹ 280 - 21% open Β· ⏱️ 25.07.2024): ``` - git clone https://github.com/bethgelab/foolbox + git clone https://github.com/QData/TextAttack ``` -- [PyPi](https://pypi.org/project/foolbox) (πŸ“₯ 5.6K / month Β· πŸ“¦ 14 Β· ⏱️ 04.03.2024): +- [PyPi](https://pypi.org/project/textattack) (πŸ“₯ 6.9K / month Β· πŸ“¦ 11 Β· ⏱️ 11.03.2024): ``` - pip install foolbox + pip install textattack ``` -- [Conda](https://anaconda.org/conda-forge/foolbox) (πŸ“₯ 15K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/textattack) (πŸ“₯ 8.7K Β· ⏱️ 16.06.2023): ``` - conda install -c conda-forge foolbox + conda install -c conda-forge textattack ```
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TextAttack (πŸ₯ˆ26 Β· ⭐ 2.9K) - TextAttack is a Python framework for adversarial attacks, data.. MIT +
Foolbox (πŸ₯ˆ27 Β· ⭐ 2.7K Β· πŸ’€) - A Python toolbox to create adversarial examples that fool neural.. MIT -- [GitHub](https://github.com/QData/TextAttack) (πŸ‘¨β€πŸ’» 66 Β· πŸ”€ 380 Β· πŸ“¦ 300 Β· πŸ“‹ 280 - 21% open Β· ⏱️ 25.07.2024): +- [GitHub](https://github.com/bethgelab/foolbox) (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 420 Β· πŸ“¦ 640 Β· πŸ“‹ 380 - 7% open Β· ⏱️ 04.03.2024): ``` - git clone https://github.com/QData/TextAttack + git clone https://github.com/bethgelab/foolbox ``` -- [PyPi](https://pypi.org/project/textattack) (πŸ“₯ 5K / month Β· πŸ“¦ 11 Β· ⏱️ 11.03.2024): +- [PyPi](https://pypi.org/project/foolbox) (πŸ“₯ 7.7K / month Β· πŸ“¦ 14 Β· ⏱️ 04.03.2024): ``` - pip install textattack + pip install foolbox ``` -- [Conda](https://anaconda.org/conda-forge/textattack) (πŸ“₯ 8.5K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/foolbox) (πŸ“₯ 15K Β· ⏱️ 16.06.2023): ``` - conda install -c conda-forge textattack + conda install -c conda-forge foolbox ```
Show 6 hidden projects... @@ -6859,9 +6855,9 @@ _Libraries for testing the robustness of machine learning models against attacks - CleverHans (πŸ₯ˆ29 Β· ⭐ 6.2K Β· πŸ’€) - An adversarial example library for constructing attacks,.. MIT - advertorch (πŸ₯‰23 Β· ⭐ 1.3K Β· πŸ’€) - A Toolbox for Adversarial Robustness Research. ❗️GPL-3.0 - AdvBox (πŸ₯‰20 Β· ⭐ 1.4K Β· πŸ’€) - Advbox is a toolbox to generate adversarial examples that fool.. Apache-2 -- robustness (πŸ₯‰19 Β· ⭐ 910 Β· πŸ’€) - A library for experimenting with, training and evaluating neural.. MIT +- robustness (πŸ₯‰20 Β· ⭐ 910 Β· πŸ’€) - A library for experimenting with, training and evaluating neural.. MIT - textflint (πŸ₯‰17 Β· ⭐ 640 Β· πŸ’€) - Unified Multilingual Robustness Evaluation Toolkit for.. ❗️GPL-3.0 -- Adversary (πŸ₯‰15 Β· ⭐ 400 Β· πŸ’€) - Tool to generate adversarial text examples and test machine.. MIT +- Adversary (πŸ₯‰16 Β· ⭐ 400 Β· πŸ’€) - Tool to generate adversarial text examples and test machine.. MIT

@@ -6871,102 +6867,102 @@ _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₯‡39 Β· ⭐ 9.3K) - NumPy & SciPy for GPU. MIT +
CuPy (πŸ₯‡39 Β· ⭐ 9.4K) - NumPy & SciPy for GPU. MIT -- [GitHub](https://github.com/cupy/cupy) (πŸ‘¨β€πŸ’» 390 Β· πŸ”€ 810 Β· πŸ“₯ 190K Β· πŸ“¦ 2.3K Β· πŸ“‹ 2.4K - 26% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/cupy/cupy) (πŸ‘¨β€πŸ’» 390 Β· πŸ”€ 820 Β· πŸ“₯ 190K Β· πŸ“¦ 2.3K Β· πŸ“‹ 2.4K - 26% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/cupy/cupy ``` -- [PyPi](https://pypi.org/project/cupy) (πŸ“₯ 57K / month Β· πŸ“¦ 270 Β· ⏱️ 22.08.2024): +- [PyPi](https://pypi.org/project/cupy) (πŸ“₯ 53K / month Β· πŸ“¦ 270 Β· ⏱️ 22.08.2024): ``` pip install cupy ``` -- [Conda](https://anaconda.org/conda-forge/cupy) (πŸ“₯ 4.8M Β· ⏱️ 22.08.2024): +- [Conda](https://anaconda.org/conda-forge/cupy) (πŸ“₯ 4.9M Β· ⏱️ 18.10.2024): ``` conda install -c conda-forge cupy ``` -- [Docker Hub](https://hub.docker.com/r/cupy/cupy) (πŸ“₯ 68K Β· ⭐ 13 Β· ⏱️ 22.08.2024): +- [Docker Hub](https://hub.docker.com/r/cupy/cupy) (πŸ“₯ 69K Β· ⭐ 13 Β· ⏱️ 22.08.2024): ``` docker pull cupy/cupy ```
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cuDF (πŸ₯‡35 Β· ⭐ 8.3K) - cuDF - GPU DataFrame Library. Apache-2 +
optimum (πŸ₯‡36 Β· ⭐ 2.5K Β· πŸ“ˆ) - Accelerate training and inference of Transformers and Diffusers.. Apache-2 -- [GitHub](https://github.com/rapidsai/cudf) (πŸ‘¨β€πŸ’» 300 Β· πŸ”€ 880 Β· πŸ“¦ 57 Β· πŸ“‹ 6.6K - 16% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/huggingface/optimum) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 450 Β· πŸ“¦ 3.7K Β· πŸ“‹ 850 - 49% open Β· ⏱️ 22.10.2024): ``` - git clone https://github.com/rapidsai/cudf + git clone https://github.com/huggingface/optimum ``` -- [PyPi](https://pypi.org/project/cudf) (πŸ“₯ 3.2K / month Β· πŸ“¦ 22 Β· ⏱️ 01.06.2020): +- [PyPi](https://pypi.org/project/optimum) (πŸ“₯ 990K / month Β· πŸ“¦ 170 Β· ⏱️ 22.10.2024): ``` - pip install cudf + pip install optimum + ``` +- [Conda](https://anaconda.org/conda-forge/optimum) (πŸ“₯ 25K Β· ⏱️ 29.05.2024): + ``` + conda install -c conda-forge optimum ```
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optimum (πŸ₯ˆ34 Β· ⭐ 2.5K) - Accelerate training and inference of Transformers and Diffusers with.. Apache-2 +
cuDF (πŸ₯ˆ35 Β· ⭐ 8.4K) - cuDF - GPU DataFrame Library. Apache-2 -- [GitHub](https://github.com/huggingface/optimum) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 450 Β· πŸ“¦ 3.5K Β· πŸ“‹ 840 - 49% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/rapidsai/cudf) (πŸ‘¨β€πŸ’» 300 Β· πŸ”€ 890 Β· πŸ“¦ 57 Β· πŸ“‹ 6.6K - 16% open Β· ⏱️ 24.10.2024): ``` - git clone https://github.com/huggingface/optimum - ``` -- [PyPi](https://pypi.org/project/optimum) (πŸ“₯ 950K / month Β· πŸ“¦ 170 Β· ⏱️ 10.10.2024): - ``` - pip install optimum + git clone https://github.com/rapidsai/cudf ``` -- [Conda](https://anaconda.org/conda-forge/optimum) (πŸ“₯ 24K Β· ⏱️ 29.05.2024): +- [PyPi](https://pypi.org/project/cudf) (πŸ“₯ 3.5K / month Β· πŸ“¦ 22 Β· ⏱️ 01.06.2020): ``` - conda install -c conda-forge optimum + pip install cudf ```
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PyCUDA (πŸ₯ˆ33 Β· ⭐ 1.8K) - CUDA integration for Python, plus shiny features. MIT +
PyCUDA (πŸ₯ˆ32 Β· ⭐ 1.8K) - CUDA integration for Python, plus shiny features. MIT -- [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): +- [GitHub](https://github.com/inducer/pycuda) (πŸ‘¨β€πŸ’» 82 Β· πŸ”€ 280 Β· πŸ“¦ 3.2K Β· πŸ“‹ 280 - 30% open Β· ⏱️ 17.10.2024): ``` git clone https://github.com/inducer/pycuda ``` -- [PyPi](https://pypi.org/project/pycuda) (πŸ“₯ 95K / month Β· πŸ“¦ 160 Β· ⏱️ 30.07.2024): +- [PyPi](https://pypi.org/project/pycuda) (πŸ“₯ 110K / month Β· πŸ“¦ 160 Β· ⏱️ 30.07.2024): ``` pip install pycuda ``` -- [Conda](https://anaconda.org/conda-forge/pycuda) (πŸ“₯ 590K Β· ⏱️ 17.08.2024): +- [Conda](https://anaconda.org/conda-forge/pycuda) (πŸ“₯ 600K Β· ⏱️ 17.08.2024): ``` conda install -c conda-forge pycuda ```
cuML (πŸ₯ˆ31 Β· ⭐ 4.2K) - cuML - RAPIDS Machine Learning Library. Apache-2 -- [GitHub](https://github.com/rapidsai/cuml) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 520 Β· πŸ“‹ 2.5K - 35% open Β· ⏱️ 08.10.2024): +- [GitHub](https://github.com/rapidsai/cuml) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 530 Β· πŸ“‹ 2.5K - 36% open Β· ⏱️ 17.10.2024): ``` git clone https://github.com/rapidsai/cuml ``` -- [PyPi](https://pypi.org/project/cuml) (πŸ“₯ 3.1K / month Β· πŸ“¦ 14 Β· ⏱️ 01.06.2020): +- [PyPi](https://pypi.org/project/cuml) (πŸ“₯ 3.2K / month Β· πŸ“¦ 14 Β· ⏱️ 01.06.2020): ``` pip install cuml ```
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Apex (πŸ₯ˆ30 Β· ⭐ 8.3K) - A PyTorch Extension: Tools for easy mixed precision and distributed.. BSD-3 +
Apex (πŸ₯ˆ30 Β· ⭐ 8.4K) - A PyTorch Extension: Tools for easy mixed precision and distributed.. BSD-3 -- [GitHub](https://github.com/NVIDIA/apex) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 1.4K Β· πŸ“¦ 2.8K Β· πŸ“‹ 1.3K - 58% open Β· ⏱️ 28.09.2024): +- [GitHub](https://github.com/NVIDIA/apex) (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 1.4K Β· πŸ“¦ 2.8K Β· πŸ“‹ 1.3K - 58% open Β· ⏱️ 17.10.2024): ``` git clone https://github.com/NVIDIA/apex ``` -- [Conda](https://anaconda.org/conda-forge/nvidia-apex) (πŸ“₯ 330K Β· ⏱️ 10.09.2024): +- [Conda](https://anaconda.org/conda-forge/nvidia-apex) (πŸ“₯ 340K Β· ⏱️ 10.09.2024): ``` conda install -c conda-forge nvidia-apex ```
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gpustat (πŸ₯ˆ30 Β· ⭐ 4K Β· πŸ’€) - A simple command-line utility for querying and monitoring GPU status. MIT +
gpustat (πŸ₯ˆ30 Β· ⭐ 4.1K 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”€ 280 Β· πŸ“¦ 6.1K Β· πŸ“‹ 120 - 22% open Β· ⏱️ 12.01.2024): ``` git clone https://github.com/wookayin/gpustat ``` -- [PyPi](https://pypi.org/project/gpustat) (πŸ“₯ 660K / month Β· πŸ“¦ 150 Β· ⏱️ 22.08.2023): +- [PyPi](https://pypi.org/project/gpustat) (πŸ“₯ 2.1M / month Β· πŸ“¦ 150 Β· ⏱️ 22.08.2023): ``` pip install gpustat ``` @@ -6975,21 +6971,21 @@ _Libraries that require and make use of CUDA/GPU or other accelerator hardware c conda install -c conda-forge gpustat ```
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ArrayFire (πŸ₯ˆ28 Β· ⭐ 4.5K) - ArrayFire: a general purpose GPU library. BSD-3 +
ArrayFire (πŸ₯ˆ28 Β· ⭐ 4.6K) - ArrayFire: a general purpose GPU library. BSD-3 -- [GitHub](https://github.com/arrayfire/arrayfire) (πŸ‘¨β€πŸ’» 94 Β· πŸ”€ 530 Β· πŸ“₯ 7.1K Β· πŸ“‹ 1.7K - 19% open Β· ⏱️ 01.10.2024): +- [GitHub](https://github.com/arrayfire/arrayfire) (πŸ‘¨β€πŸ’» 94 Β· πŸ”€ 530 Β· πŸ“₯ 7.1K Β· πŸ“‹ 1.7K - 19% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/arrayfire/arrayfire ``` -- [PyPi](https://pypi.org/project/arrayfire) (πŸ“₯ 4.1K / month Β· πŸ“¦ 10 Β· ⏱️ 22.02.2022): +- [PyPi](https://pypi.org/project/arrayfire) (πŸ“₯ 6.2K / month Β· πŸ“¦ 10 Β· ⏱️ 22.02.2022): ``` pip install arrayfire ```
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”€ 300 Β· πŸ“‹ 1.7K - 9% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/rapidsai/cugraph) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 300 Β· πŸ“‹ 1.8K - 10% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/rapidsai/cugraph @@ -7005,7 +7001,7 @@ _Libraries that require and make use of CUDA/GPU or other accelerator hardware c
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’» 93 Β· πŸ”€ 620 Β· πŸ“‹ 1.6K - 14% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/NVIDIA/DALI) (πŸ‘¨β€πŸ’» 94 Β· πŸ”€ 620 Β· πŸ“‹ 1.6K - 14% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/NVIDIA/DALI @@ -7018,31 +7014,31 @@ _Libraries that require and make use of CUDA/GPU or other accelerator hardware c ``` git clone https://github.com/lebedov/scikit-cuda ``` -- [PyPi](https://pypi.org/project/scikit-cuda) (πŸ“₯ 720 / month Β· πŸ“¦ 23 Β· ⏱️ 27.05.2019): +- [PyPi](https://pypi.org/project/scikit-cuda) (πŸ“₯ 730 / month Β· πŸ“¦ 23 Β· ⏱️ 27.05.2019): ``` pip install scikit-cuda ```
Vulkan Kompute (πŸ₯‰23 Β· ⭐ 2K) - General purpose GPU compute framework built on Vulkan to.. Apache-2 -- [GitHub](https://github.com/KomputeProject/kompute) (πŸ‘¨β€πŸ’» 28 Β· πŸ”€ 140 Β· πŸ“₯ 580 Β· πŸ“‹ 220 - 32% open Β· ⏱️ 28.09.2024): +- [GitHub](https://github.com/KomputeProject/kompute) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 140 Β· πŸ“₯ 600 Β· πŸ“‹ 220 - 32% open Β· ⏱️ 18.10.2024): ``` git clone https://github.com/KomputeProject/kompute ``` -- [PyPi](https://pypi.org/project/kp) (πŸ“₯ 640 / month Β· ⏱️ 20.01.2024): +- [PyPi](https://pypi.org/project/kp) (πŸ“₯ 920 / month Β· ⏱️ 20.01.2024): ``` pip install kp ```
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Merlin (πŸ₯‰20 Β· ⭐ 760) - NVIDIA Merlin is an open source library providing end-to-end GPU-.. Apache-2 +
Merlin (πŸ₯‰21 Β· ⭐ 760) - 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“‹ 460 - 46% open Β· ⏱️ 22.07.2024): ``` git clone https://github.com/NVIDIA-Merlin/Merlin ``` -- [PyPi](https://pypi.org/project/merlin-core) (πŸ“₯ 9.4K / month Β· πŸ“¦ 1 Β· ⏱️ 29.08.2023): +- [PyPi](https://pypi.org/project/merlin-core) (πŸ“₯ 11K / month Β· πŸ“¦ 1 Β· ⏱️ 29.08.2023): ``` pip install merlin-core ``` @@ -7053,9 +7049,9 @@ _Libraries that require and make use of CUDA/GPU or other accelerator hardware c - 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) - Python 3 Bindings for the NVIDIA Management Library. BSD-3 +- ipyexperiments (πŸ₯‰17 Β· ⭐ 200 Β· πŸ’€) - Automatic GPU+CPU memory profiling, re-use and memory.. Apache-2 - cuSignal (πŸ₯‰16 Β· ⭐ 710 Β· πŸ’€) - GPU accelerated signal processing. Apache-2 - SpeedTorch (πŸ₯‰16 Β· ⭐ 680 Β· πŸ’€) - Library for faster pinned CPU - GPU transfer in Pytorch. MIT -- ipyexperiments (πŸ₯‰16 Β· ⭐ 200 Β· πŸ’€) - Automatic GPU+CPU memory profiling, re-use and memory.. Apache-2

@@ -7067,28 +7063,28 @@ _Libraries that extend TensorFlow with additional capabilities._
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“¦ 20K Β· πŸ“‹ 1.4K - 48% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/tensorflow/datasets) (πŸ‘¨β€πŸ’» 320 Β· πŸ”€ 1.5K Β· πŸ“¦ 20K Β· πŸ“‹ 1.4K - 48% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/tensorflow/datasets ``` -- [PyPi](https://pypi.org/project/tensorflow-datasets) (πŸ“₯ 1.7M / month Β· πŸ“¦ 330 Β· ⏱️ 05.06.2024): +- [PyPi](https://pypi.org/project/tensorflow-datasets) (πŸ“₯ 1.8M / month Β· πŸ“¦ 330 Β· ⏱️ 05.06.2024): ``` pip install tensorflow-datasets ``` -- [Conda](https://anaconda.org/conda-forge/tensorflow-datasets) (πŸ“₯ 35K Β· ⏱️ 16.06.2023): +- [Conda](https://anaconda.org/conda-forge/tensorflow-datasets) (πŸ“₯ 36K Β· ⏱️ 16.06.2023): ``` conda install -c conda-forge tensorflow-datasets ```
TFX (πŸ₯‡35 Β· ⭐ 2.1K) - TFX is an end-to-end platform for deploying production ML pipelines. Apache-2 -- [GitHub](https://github.com/tensorflow/tfx) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 700 Β· πŸ“¦ 1.6K Β· πŸ“‹ 1.1K - 22% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/tensorflow/tfx) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 700 Β· πŸ“¦ 1.6K Β· πŸ“‹ 1.1K - 22% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/tensorflow/tfx ``` -- [PyPi](https://pypi.org/project/tfx) (πŸ“₯ 37K / month Β· πŸ“¦ 17 Β· ⏱️ 13.05.2024): +- [PyPi](https://pypi.org/project/tfx) (πŸ“₯ 41K / month Β· πŸ“¦ 17 Β· ⏱️ 13.05.2024): ``` pip install tfx ``` @@ -7128,7 +7124,7 @@ _Libraries that extend TensorFlow with additional capabilities._ ``` git clone https://github.com/tensorflow/io ``` -- [PyPi](https://pypi.org/project/tensorflow-io) (πŸ“₯ 1.4M / month Β· πŸ“¦ 61 Β· ⏱️ 01.07.2024): +- [PyPi](https://pypi.org/project/tensorflow-io) (πŸ“₯ 1.3M / month Β· πŸ“¦ 61 Β· ⏱️ 01.07.2024): ``` pip install tensorflow-io ``` @@ -7140,31 +7136,31 @@ _Libraries that extend TensorFlow with additional capabilities._ ``` git clone https://github.com/tensorflow/model-optimization ``` -- [PyPi](https://pypi.org/project/tensorflow-model-optimization) (πŸ“₯ 900K / month Β· πŸ“¦ 45 Β· ⏱️ 08.02.2024): +- [PyPi](https://pypi.org/project/tensorflow-model-optimization) (πŸ“₯ 810K / month Β· πŸ“¦ 45 Β· ⏱️ 08.02.2024): ``` pip install tensorflow-model-optimization ```
TensorFlow Transform (πŸ₯‰27 Β· ⭐ 980) - Input pipeline framework. Apache-2 -- [GitHub](https://github.com/tensorflow/transform) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 210 Β· πŸ“‹ 220 - 20% open Β· ⏱️ 10.09.2024): +- [GitHub](https://github.com/tensorflow/transform) (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 210 Β· πŸ“‹ 220 - 20% open Β· ⏱️ 21.10.2024): ``` git clone https://github.com/tensorflow/transform ``` -- [PyPi](https://pypi.org/project/tensorflow-transform) (πŸ“₯ 510K / month Β· πŸ“¦ 18 Β· ⏱️ 24.04.2024): +- [PyPi](https://pypi.org/project/tensorflow-transform) (πŸ“₯ 580K / month Β· πŸ“¦ 18 Β· ⏱️ 24.04.2024): ``` pip install tensorflow-transform ```
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“¦ 480 Β· πŸ“‹ 69 - 1% open Β· ⏱️ 18.06.2024): +- [GitHub](https://github.com/tensorflow/neural-structured-learning) (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 190 Β· πŸ“¦ 490 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“₯ 7.7K / month Β· πŸ“¦ 3 Β· ⏱️ 29.07.2022): +- [PyPi](https://pypi.org/project/neural-structured-learning) (πŸ“₯ 7.1K / month Β· πŸ“¦ 3 Β· ⏱️ 29.07.2022): ``` pip install neural-structured-learning ``` @@ -7176,7 +7172,7 @@ _Libraries that extend TensorFlow with additional capabilities._ ``` git clone https://github.com/PAIR-code/saliency ``` -- [PyPi](https://pypi.org/project/saliency) (πŸ“₯ 89K / month Β· πŸ“¦ 8 Β· ⏱️ 20.03.2024): +- [PyPi](https://pypi.org/project/saliency) (πŸ“₯ 60K / month Β· πŸ“¦ 8 Β· ⏱️ 20.03.2024): ``` pip install saliency ``` @@ -7188,19 +7184,19 @@ _Libraries that extend TensorFlow with additional capabilities._ ``` git clone https://github.com/tensorflow/compression ``` -- [PyPi](https://pypi.org/project/tensorflow-compression) (πŸ“₯ 3.6K / month Β· πŸ“¦ 2 Β· ⏱️ 02.02.2024): +- [PyPi](https://pypi.org/project/tensorflow-compression) (πŸ“₯ 5.3K / month Β· πŸ“¦ 2 Β· ⏱️ 02.02.2024): ``` pip install tensorflow-compression ```
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TensorFlow Cloud (πŸ₯‰21 Β· ⭐ 370 Β· πŸ’€) - The TensorFlow Cloud repository provides APIs that.. Apache-2 +
TensorFlow Cloud (πŸ₯‰21 Β· ⭐ 380 Β· πŸ’€) - The TensorFlow Cloud repository provides APIs that.. Apache-2 -- [GitHub](https://github.com/tensorflow/cloud) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 85 Β· πŸ“‹ 100 - 73% open Β· ⏱️ 25.02.2024): +- [GitHub](https://github.com/tensorflow/cloud) (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 88 Β· πŸ“‹ 100 - 73% open Β· ⏱️ 25.02.2024): ``` git clone https://github.com/tensorflow/cloud ``` -- [PyPi](https://pypi.org/project/tensorflow-cloud) (πŸ“₯ 32K / month Β· πŸ“¦ 7 Β· ⏱️ 17.06.2021): +- [PyPi](https://pypi.org/project/tensorflow-cloud) (πŸ“₯ 34K / month Β· πŸ“¦ 7 Β· ⏱️ 17.06.2021): ``` pip install tensorflow-cloud ``` @@ -7223,24 +7219,24 @@ _Libraries that extend Jax with additional capabilities._
equinox (πŸ₯‡31 Β· ⭐ 2.1K) - Elegant easy-to-use neural networks + scientific computing in.. Apache-2 -- [GitHub](https://github.com/patrick-kidger/equinox) (πŸ‘¨β€πŸ’» 55 Β· πŸ”€ 140 Β· πŸ“¦ 750 Β· πŸ“‹ 450 - 34% open Β· ⏱️ 08.10.2024): +- [GitHub](https://github.com/patrick-kidger/equinox) (πŸ‘¨β€πŸ’» 56 Β· πŸ”€ 140 Β· πŸ“¦ 790 Β· πŸ“‹ 450 - 34% open Β· ⏱️ 18.10.2024): ``` git clone https://github.com/patrick-kidger/equinox ``` -- [PyPi](https://pypi.org/project/equinox) (πŸ“₯ 230K / month Β· πŸ“¦ 160 Β· ⏱️ 18.09.2024): +- [PyPi](https://pypi.org/project/equinox) (πŸ“₯ 250K / month Β· πŸ“¦ 170 Β· ⏱️ 18.10.2024): ``` pip install equinox ```
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evojax (πŸ₯‰20 Β· ⭐ 830) - EvoJAX: Hardware-accelerated Neuroevolution. Apache-2 +
evojax (πŸ₯‰20 Β· ⭐ 840) - EvoJAX: Hardware-accelerated Neuroevolution. Apache-2 -- [GitHub](https://github.com/google/evojax) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 85 Β· πŸ“¦ 26 Β· πŸ“‹ 33 - 48% open Β· ⏱️ 27.06.2024): +- [GitHub](https://github.com/google/evojax) (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 85 Β· πŸ“¦ 27 Β· πŸ“‹ 33 - 48% open Β· ⏱️ 27.06.2024): ``` git clone https://github.com/google/evojax ``` -- [PyPi](https://pypi.org/project/evojax) (πŸ“₯ 1.8K / month Β· πŸ“¦ 6 Β· ⏱️ 18.06.2024): +- [PyPi](https://pypi.org/project/evojax) (πŸ“₯ 2.8K / month Β· πŸ“¦ 6 Β· ⏱️ 18.06.2024): ``` pip install evojax ``` @@ -7263,48 +7259,48 @@ _Libraries that extend scikit-learn with additional capabilities._
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’» 82 Β· πŸ”€ 170 Β· πŸ“¦ 12K Β· πŸ“‹ 280 - 32% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/intel/scikit-learn-intelex) (πŸ‘¨β€πŸ’» 82 Β· πŸ”€ 170 Β· πŸ“¦ 12K Β· πŸ“‹ 280 - 31% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/intel/scikit-learn-intelex ``` -- [PyPi](https://pypi.org/project/scikit-learn-intelex) (πŸ“₯ 85K / month Β· πŸ“¦ 55 Β· ⏱️ 17.09.2024): +- [PyPi](https://pypi.org/project/scikit-learn-intelex) (πŸ“₯ 99K / month Β· πŸ“¦ 55 Β· ⏱️ 17.09.2024): ``` pip install scikit-learn-intelex ``` -- [Conda](https://anaconda.org/conda-forge/scikit-learn-intelex) (πŸ“₯ 350K Β· ⏱️ 20.08.2024): +- [Conda](https://anaconda.org/conda-forge/scikit-learn-intelex) (πŸ“₯ 360K Β· ⏱️ 20.08.2024): ``` conda install -c conda-forge scikit-learn-intelex ```
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imbalanced-learn (πŸ₯‡33 Β· ⭐ 6.8K Β· πŸ“‰) - A Python Package to Tackle the Curse of Imbalanced.. MIT +
imbalanced-learn (πŸ₯‡33 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’» 85 Β· πŸ”€ 1.3K Β· πŸ“‹ 610 - 7% open Β· ⏱️ 06.10.2024): ``` git clone https://github.com/scikit-learn-contrib/imbalanced-learn ``` -- [PyPi](https://pypi.org/project/imbalanced-learn) (πŸ“₯ 17M / month Β· πŸ“¦ 450 Β· ⏱️ 04.10.2024): +- [PyPi](https://pypi.org/project/imbalanced-learn) (πŸ“₯ 20M / month Β· πŸ“¦ 450 Β· ⏱️ 04.10.2024): ``` pip install imbalanced-learn ``` -- [Conda](https://anaconda.org/conda-forge/imbalanced-learn) (πŸ“₯ 620K Β· ⏱️ 04.10.2024): +- [Conda](https://anaconda.org/conda-forge/imbalanced-learn) (πŸ“₯ 630K Β· ⏱️ 04.10.2024): ``` conda install -c conda-forge imbalanced-learn ```
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”€ 860 Β· πŸ“¦ 15K Β· πŸ“‹ 490 - 30% open Β· ⏱️ 02.07.2024): +- [GitHub](https://github.com/rasbt/mlxtend) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 860 Β· πŸ“¦ 16K Β· πŸ“‹ 490 - 30% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/rasbt/mlxtend ``` -- [PyPi](https://pypi.org/project/mlxtend) (πŸ“₯ 610K / month Β· πŸ“¦ 180 Β· ⏱️ 05.01.2024): +- [PyPi](https://pypi.org/project/mlxtend) (πŸ“₯ 600K / month Β· πŸ“¦ 180 Β· ⏱️ 05.01.2024): ``` pip install mlxtend ``` -- [Conda](https://anaconda.org/conda-forge/mlxtend) (πŸ“₯ 320K Β· ⏱️ 05.01.2024): +- [Conda](https://anaconda.org/conda-forge/mlxtend) (πŸ“₯ 330K Β· ⏱️ 05.01.2024): ``` conda install -c conda-forge mlxtend ``` @@ -7316,32 +7312,32 @@ _Libraries that extend scikit-learn with additional capabilities._ ``` git clone https://github.com/scikit-learn-contrib/category_encoders ``` -- [PyPi](https://pypi.org/project/category_encoders) (πŸ“₯ 1.4M / month Β· πŸ“¦ 280 Β· ⏱️ 01.10.2024): +- [PyPi](https://pypi.org/project/category_encoders) (πŸ“₯ 1.5M / month Β· πŸ“¦ 280 Β· ⏱️ 01.10.2024): ``` pip install category_encoders ``` -- [Conda](https://anaconda.org/conda-forge/category_encoders) (πŸ“₯ 280K Β· ⏱️ 02.10.2024): +- [Conda](https://anaconda.org/conda-forge/category_encoders) (πŸ“₯ 290K Β· ⏱️ 02.10.2024): ``` conda install -c conda-forge category_encoders ```
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scikit-lego (πŸ₯ˆ28 Β· ⭐ 1.3K) - Extra blocks for scikit-learn pipelines. MIT +
scikit-lego (πŸ₯ˆ27 Β· ⭐ 1.3K) - Extra blocks for scikit-learn pipelines. MIT -- [GitHub](https://github.com/koaning/scikit-lego) (πŸ‘¨β€πŸ’» 67 Β· πŸ”€ 120 Β· πŸ“¦ 160 Β· πŸ“‹ 320 - 9% open Β· ⏱️ 23.09.2024): +- [GitHub](https://github.com/koaning/scikit-lego) (πŸ‘¨β€πŸ’» 67 Β· πŸ”€ 120 Β· πŸ“¦ 160 Β· πŸ“‹ 320 - 10% open Β· ⏱️ 23.09.2024): ``` git clone https://github.com/koaning/scikit-lego ``` -- [PyPi](https://pypi.org/project/scikit-lego) (πŸ“₯ 27K / month Β· πŸ“¦ 11 Β· ⏱️ 10.07.2024): +- [PyPi](https://pypi.org/project/scikit-lego) (πŸ“₯ 31K / month Β· πŸ“¦ 11 Β· ⏱️ 10.07.2024): ``` pip install scikit-lego ``` -- [Conda](https://anaconda.org/conda-forge/scikit-lego) (πŸ“₯ 56K Β· ⏱️ 10.07.2024): +- [Conda](https://anaconda.org/conda-forge/scikit-lego) (πŸ“₯ 57K Β· ⏱️ 10.07.2024): ``` conda install -c conda-forge scikit-lego ```
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scikit-opt (πŸ₯‰25 Β· ⭐ 5.2K) - Genetic Algorithm, Particle Swarm Optimization, Simulated.. MIT +
scikit-opt (πŸ₯‰25 Β· ⭐ 5.3K) - Genetic Algorithm, Particle Swarm Optimization, Simulated.. MIT - [GitHub](https://github.com/guofei9987/scikit-opt) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 990 Β· πŸ“¦ 230 Β· πŸ“‹ 180 - 37% open Β· ⏱️ 23.06.2024): @@ -7353,38 +7349,38 @@ _Libraries that extend scikit-learn with additional capabilities._ pip install scikit-opt ```
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iterative-stratification (πŸ₯‰22 Β· ⭐ 850) - scikit-learn cross validators for iterative.. BSD-3 +
iterative-stratification (πŸ₯‰23 Β· ⭐ 850) - scikit-learn cross validators for iterative.. BSD-3 -- [GitHub](https://github.com/trent-b/iterative-stratification) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 75 Β· πŸ“¦ 480 Β· πŸ“‹ 27 - 11% open Β· ⏱️ 05.10.2024): +- [GitHub](https://github.com/trent-b/iterative-stratification) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 75 Β· πŸ“¦ 500 Β· πŸ“‹ 28 - 10% open Β· ⏱️ 12.10.2024): ``` git clone https://github.com/trent-b/iterative-stratification ``` -- [PyPi](https://pypi.org/project/iterative-stratification) (πŸ“₯ 34K / month Β· πŸ“¦ 15 Β· ⏱️ 05.10.2024): +- [PyPi](https://pypi.org/project/iterative-stratification) (πŸ“₯ 38K / month Β· πŸ“¦ 15 Β· ⏱️ 12.10.2024): ``` pip install iterative-stratification ```
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dabl (πŸ₯‰20 Β· ⭐ 720 Β· πŸ’€) - Data Analysis Baseline Library. BSD-3 +
dabl (πŸ₯‰20 Β· ⭐ 720) - Data Analysis Baseline Library. BSD-3 -- [GitHub](https://github.com/amueller/dabl) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 110 Β· ⏱️ 09.01.2024): +- [GitHub](https://github.com/amueller/dabl) (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 110 Β· ⏱️ 07.08.2024): ``` git clone https://github.com/amueller/dabl ``` -- [PyPi](https://pypi.org/project/dabl) (πŸ“₯ 5.5K / month Β· πŸ“¦ 3 Β· ⏱️ 07.08.2024): +- [PyPi](https://pypi.org/project/dabl) (πŸ“₯ 7.7K / month Β· πŸ“¦ 3 Β· ⏱️ 07.08.2024): ``` pip install dabl ```
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scikit-tda (πŸ₯‰18 Β· ⭐ 520) - 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”€ 54 Β· πŸ“¦ 62 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“₯ 1.2K / month Β· ⏱️ 19.07.2024): +- [PyPi](https://pypi.org/project/scikit-tda) (πŸ“₯ 1.4K / month Β· ⏱️ 19.07.2024): ``` pip install scikit-tda ``` @@ -7396,7 +7392,7 @@ _Libraries that extend scikit-learn with additional capabilities._ ``` git clone https://github.com/scikit-learn-contrib/DESlib ``` -- [PyPi](https://pypi.org/project/deslib) (πŸ“₯ 1.3K / month Β· πŸ“¦ 3 Β· ⏱️ 12.04.2024): +- [PyPi](https://pypi.org/project/deslib) (πŸ“₯ 1.9K / month Β· πŸ“¦ 3 Β· ⏱️ 12.04.2024): ``` pip install deslib ``` @@ -7404,9 +7400,9 @@ _Libraries that extend scikit-learn with additional capabilities._
Show 9 hidden projects... - scikit-survival (πŸ₯ˆ31 Β· ⭐ 1.1K) - Survival analysis built on top of scikit-learn. ❗️GPL-3.0 -- fancyimpute (πŸ₯ˆ27 Β· ⭐ 1.3K Β· πŸ’€) - Multivariate imputation and matrix completion.. Apache-2 +- fancyimpute (πŸ₯ˆ27 Β· ⭐ 1.2K Β· πŸ’€) - Multivariate imputation and matrix completion.. Apache-2 +- scikit-multilearn (πŸ₯ˆ27 Β· ⭐ 920 Β· πŸ’€) - A scikit-learn based module for multi-label et. al... BSD-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 - combo (πŸ₯‰21 Β· ⭐ 640 Β· πŸ’€) - (AAAI 20) A Python Toolbox for Machine Learning Model.. BSD-2 xgboost - skope-rules (πŸ₯‰21 Β· ⭐ 620 Β· πŸ’€) - machine learning with logical rules in Python. ❗️BSD-1-Clause @@ -7421,30 +7417,38 @@ _Libraries that extend scikit-learn with additional capabilities._ _Libraries that extend Pytorch with additional capabilities._ -
accelerate (πŸ₯‡40 Β· ⭐ 7.8K) - A simple way to launch, train, and use PyTorch models on.. Apache-2 +
accelerate (πŸ₯‡40 Β· ⭐ 7.9K) - A simple way to launch, train, and use PyTorch models on.. Apache-2 -- [GitHub](https://github.com/huggingface/accelerate) (πŸ‘¨β€πŸ’» 300 Β· πŸ”€ 940 Β· πŸ“¦ 53K Β· πŸ“‹ 1.6K - 7% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/huggingface/accelerate) (πŸ‘¨β€πŸ’» 300 Β· πŸ”€ 960 Β· πŸ“¦ 55K Β· πŸ“‹ 1.6K - 7% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/huggingface/accelerate ``` -- [PyPi](https://pypi.org/project/accelerate) (πŸ“₯ 7.7M / month Β· πŸ“¦ 1.5K Β· ⏱️ 07.10.2024): +- [PyPi](https://pypi.org/project/accelerate) (πŸ“₯ 7.9M / month Β· πŸ“¦ 1.5K Β· ⏱️ 12.10.2024): ``` pip install accelerate ``` -- [Conda](https://anaconda.org/conda-forge/accelerate) (πŸ“₯ 220K Β· ⏱️ 08.10.2024): +- [Conda](https://anaconda.org/conda-forge/accelerate) (πŸ“₯ 230K Β· ⏱️ 12.10.2024): ``` conda install -c conda-forge accelerate ```
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PML (πŸ₯‡34 Β· ⭐ 6K) - The easiest way to use deep metric learning in your application. Modular,.. MIT +
tinygrad (πŸ₯‡33 Β· ⭐ 27K) - You like pytorch? You like micrograd? You love tinygrad!. MIT + +- [GitHub](https://github.com/tinygrad/tinygrad) (πŸ‘¨β€πŸ’» 350 Β· πŸ”€ 2.9K Β· πŸ“¦ 120 Β· πŸ“‹ 780 - 15% open Β· ⏱️ 24.10.2024): + + ``` + git clone https://github.com/geohot/tinygrad + ``` +
+
PML (πŸ₯‡32 Β· ⭐ 6K Β· πŸ“‰) - The easiest way to use deep metric learning in your application... MIT - [GitHub](https://github.com/KevinMusgrave/pytorch-metric-learning) (πŸ‘¨β€πŸ’» 42 Β· πŸ”€ 660 Β· πŸ“¦ 1.9K Β· πŸ“‹ 510 - 12% open Β· ⏱️ 11.09.2024): ``` git clone https://github.com/KevinMusgrave/pytorch-metric-learning ``` -- [PyPi](https://pypi.org/project/pytorch-metric-learning) (πŸ“₯ 710K / month Β· πŸ“¦ 50 Β· ⏱️ 25.07.2024): +- [PyPi](https://pypi.org/project/pytorch-metric-learning) (πŸ“₯ 810K / month Β· πŸ“¦ 50 Β· ⏱️ 25.07.2024): ``` pip install pytorch-metric-learning ``` @@ -7453,22 +7457,14 @@ _Libraries that extend Pytorch with additional capabilities._ conda install -c metric-learning pytorch-metric-learning ```
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tinygrad (πŸ₯‡33 Β· ⭐ 26K) - You like pytorch? You like micrograd? You love tinygrad!. MIT - -- [GitHub](https://github.com/tinygrad/tinygrad) (πŸ‘¨β€πŸ’» 340 Β· πŸ”€ 2.9K Β· πŸ“¦ 110 Β· πŸ“‹ 750 - 15% open Β· ⏱️ 10.10.2024): - - ``` - 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”€ 910 Β· πŸ“¦ 3.9K Β· πŸ“‹ 220 - 33% open Β· ⏱️ 19.10.2023): +- [GitHub](https://github.com/rtqichen/torchdiffeq) (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 910 Β· πŸ“¦ 4K Β· πŸ“‹ 220 - 33% open Β· ⏱️ 19.10.2023): ``` git clone https://github.com/rtqichen/torchdiffeq ``` -- [PyPi](https://pypi.org/project/torchdiffeq) (πŸ“₯ 840K / month Β· πŸ“¦ 100 Β· ⏱️ 29.05.2024): +- [PyPi](https://pypi.org/project/torchdiffeq) (πŸ“₯ 860K / month Β· πŸ“¦ 100 Β· ⏱️ 29.05.2024): ``` pip install torchdiffeq ``` @@ -7484,11 +7480,11 @@ _Libraries that extend Pytorch with additional capabilities._ ``` git clone https://github.com/Lightning-AI/lightning-flash ``` -- [PyPi](https://pypi.org/project/lightning-flash) (πŸ“₯ 2.7K / month Β· πŸ“¦ 5 Β· ⏱️ 11.05.2022): +- [PyPi](https://pypi.org/project/lightning-flash) (πŸ“₯ 4K / month Β· πŸ“¦ 5 Β· ⏱️ 11.05.2022): ``` pip install lightning-flash ``` -- [Conda](https://anaconda.org/conda-forge/lightning-flash) (πŸ“₯ 22K Β· ⏱️ 04.07.2023): +- [Conda](https://anaconda.org/conda-forge/lightning-flash) (πŸ“₯ 23K Β· ⏱️ 04.07.2023): ``` conda install -c conda-forge lightning-flash ``` @@ -7512,47 +7508,47 @@ _Libraries that extend Pytorch with additional capabilities._ ``` git clone https://github.com/rusty1s/pytorch_scatter ``` -- [PyPi](https://pypi.org/project/torch-scatter) (πŸ“₯ 40K / month Β· πŸ“¦ 150 Β· ⏱️ 06.10.2023): +- [PyPi](https://pypi.org/project/torch-scatter) (πŸ“₯ 45K / month Β· πŸ“¦ 150 Β· ⏱️ 06.10.2023): ``` pip install torch-scatter ``` -- [Conda](https://anaconda.org/conda-forge/pytorch_scatter) (πŸ“₯ 500K Β· ⏱️ 08.10.2024): +- [Conda](https://anaconda.org/conda-forge/pytorch_scatter) (πŸ“₯ 510K Β· ⏱️ 08.10.2024): ``` conda install -c conda-forge pytorch_scatter ```
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PyTorch Sparse (πŸ₯‰23 Β· ⭐ 1K) - PyTorch Extension Library of Optimized Autograd Sparse Matrix.. MIT +
Pytorch Toolbelt (πŸ₯‰24 Β· ⭐ 1.5K Β· πŸ“ˆ) - PyTorch extensions for fast R&D prototyping and.. MIT -- [GitHub](https://github.com/rusty1s/pytorch_sparse) (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 150 Β· πŸ“‹ 280 - 10% open Β· ⏱️ 15.08.2024): +- [GitHub](https://github.com/BloodAxe/pytorch-toolbelt) (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 120 Β· πŸ“₯ 45 Β· πŸ“‹ 33 - 12% open Β· ⏱️ 14.10.2024): ``` - git clone https://github.com/rusty1s/pytorch_sparse - ``` -- [PyPi](https://pypi.org/project/torch-sparse) (πŸ“₯ 28K / month Β· πŸ“¦ 120 Β· ⏱️ 06.10.2023): - ``` - pip install torch-sparse + git clone https://github.com/BloodAxe/pytorch-toolbelt ``` -- [Conda](https://anaconda.org/conda-forge/pytorch_sparse) (πŸ“₯ 470K Β· ⏱️ 08.10.2024): +- [PyPi](https://pypi.org/project/pytorch_toolbelt) (πŸ“₯ 9.1K / month Β· πŸ“¦ 7 Β· ⏱️ 27.06.2022): ``` - conda install -c conda-forge pytorch_sparse + pip install pytorch_toolbelt ```
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Pytorch Toolbelt (πŸ₯‰22 Β· ⭐ 1.5K) - PyTorch extensions for fast R&D prototyping and Kaggle.. MIT +
PyTorch Sparse (πŸ₯‰23 Β· ⭐ 1K) - PyTorch Extension Library of Optimized Autograd Sparse Matrix.. MIT -- [GitHub](https://github.com/BloodAxe/pytorch-toolbelt) (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 120 Β· πŸ“₯ 44 Β· πŸ“‹ 33 - 12% open Β· ⏱️ 01.10.2024): +- [GitHub](https://github.com/rusty1s/pytorch_sparse) (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 150 Β· πŸ“‹ 280 - 10% open Β· ⏱️ 15.08.2024): ``` - git clone https://github.com/BloodAxe/pytorch-toolbelt + git clone https://github.com/rusty1s/pytorch_sparse ``` -- [PyPi](https://pypi.org/project/pytorch_toolbelt) (πŸ“₯ 7.8K / month Β· πŸ“¦ 7 Β· ⏱️ 27.06.2022): +- [PyPi](https://pypi.org/project/torch-sparse) (πŸ“₯ 32K / month Β· πŸ“¦ 120 Β· ⏱️ 06.10.2023): ``` - pip install pytorch_toolbelt + pip install torch-sparse + ``` +- [Conda](https://anaconda.org/conda-forge/pytorch_sparse) (πŸ“₯ 480K Β· ⏱️ 08.10.2024): + ``` + conda install -c conda-forge pytorch_sparse ```
Show 23 hidden projects... - pretrainedmodels (πŸ₯ˆ29 Β· ⭐ 9K Β· πŸ’€) - Pretrained ConvNets for pytorch: NASNet, ResNeXt,.. BSD-3 -- torchsde (πŸ₯ˆ28 Β· ⭐ 1.6K Β· πŸ’€) - Differentiable SDE solvers with GPU support and efficient.. Apache-2 +- torchsde (πŸ₯ˆ29 Β· ⭐ 1.6K Β· πŸ’€) - Differentiable SDE solvers with GPU support and efficient.. Apache-2 - EfficientNet-PyTorch (πŸ₯ˆ27 Β· ⭐ 7.9K 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 - pytorch-optimizer (πŸ₯ˆ26 Β· ⭐ 3K Β· πŸ’€) - torch-optimizer -- collection of optimizers for.. Apache-2 @@ -7568,9 +7564,9 @@ _Libraries that extend Pytorch with additional capabilities._ - 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 - Performer Pytorch (πŸ₯‰19 Β· ⭐ 1.1K Β· πŸ’€) - An implementation of Performer, a linear attention-.. MIT +- Tez (πŸ₯‰18 Β· ⭐ 1.2K Β· πŸ’€) - Tez is a super-simple and lightweight Trainer for PyTorch. It.. Apache-2 - 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₯‰18 Β· ⭐ 780 Β· πŸ’€) - The goal of this library is to generate more helpful.. MIT - Pywick (πŸ₯‰17 Β· ⭐ 400 Β· πŸ’€) - High-level batteries-included neural network training library for.. MIT - madgrad (πŸ₯‰16 Β· ⭐ 800 Β· πŸ’€) - MADGRAD Optimization Method. MIT - TorchDrift (πŸ₯‰15 Β· ⭐ 310 Β· πŸ’€) - Drift Detection for your PyTorch Models. Apache-2 @@ -7583,7 +7579,7 @@ _Libraries that extend Pytorch with additional capabilities._ _Libraries for connecting to, operating, and querying databases._ -πŸ”— best-of-python - DB Clients ( ⭐ 3.6K) - Collection of database clients for python. +πŸ”— best-of-python - DB Clients ( ⭐ 3.7K) - Collection of database clients for python.
@@ -7593,7 +7589,7 @@ _Libraries for connecting to, operating, and querying databases._
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’» 1.7K Β· πŸ”€ 5.2K Β· πŸ“₯ 420K Β· πŸ“¦ 1.1M Β· πŸ“‹ 11K - 16% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/scipy/scipy) (πŸ‘¨β€πŸ’» 1.7K Β· πŸ”€ 5.2K Β· πŸ“₯ 420K Β· πŸ“¦ 1.1M Β· πŸ“‹ 11K - 16% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/scipy/scipy @@ -7602,59 +7598,59 @@ _Libraries for connecting to, operating, and querying databases._ ``` pip install scipy ``` -- [Conda](https://anaconda.org/conda-forge/scipy) (πŸ“₯ 53M Β· ⏱️ 09.09.2024): +- [Conda](https://anaconda.org/conda-forge/scipy) (πŸ“₯ 54M Β· ⏱️ 21.10.2024): ``` conda install -c conda-forge scipy ```
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”€ 4.4K Β· πŸ“₯ 550K Β· πŸ“¦ 180K Β· πŸ“‹ 14K - 36% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/sympy/sympy) (πŸ‘¨β€πŸ’» 1.3K Β· πŸ”€ 4.4K Β· πŸ“₯ 550K Β· πŸ“¦ 180K Β· πŸ“‹ 14K - 36% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/sympy/sympy ``` -- [PyPi](https://pypi.org/project/sympy) (πŸ“₯ 30M / month Β· πŸ“¦ 3.5K Β· ⏱️ 18.09.2024): +- [PyPi](https://pypi.org/project/sympy) (πŸ“₯ 31M / month Β· πŸ“¦ 3.5K Β· ⏱️ 18.09.2024): ``` pip install sympy ``` -- [Conda](https://anaconda.org/conda-forge/sympy): +- [Conda](https://anaconda.org/conda-forge/sympy) (πŸ“₯ 6.9M Β· ⏱️ 09.10.2024): ``` conda install -c conda-forge sympy ```
Streamlit (πŸ₯‡46 Β· ⭐ 35K) - Streamlit A faster way to build and share data apps. Apache-2 -- [GitHub](https://github.com/streamlit/streamlit) (πŸ‘¨β€πŸ’» 240 Β· πŸ”€ 3K Β· πŸ“¦ 540K Β· πŸ“‹ 4.6K - 20% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/streamlit/streamlit) (πŸ‘¨β€πŸ’» 240 Β· πŸ”€ 3.1K Β· πŸ“¦ 560K Β· πŸ“‹ 4.7K - 21% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/streamlit/streamlit ``` -- [PyPi](https://pypi.org/project/streamlit) (πŸ“₯ 7.2M / month Β· πŸ“¦ 2.7K Β· ⏱️ 01.10.2024): +- [PyPi](https://pypi.org/project/streamlit) (πŸ“₯ 7.3M / month Β· πŸ“¦ 2.7K Β· ⏱️ 01.10.2024): ``` pip install streamlit ```
Gradio (πŸ₯‡44 Β· ⭐ 33K) - Wrap UIs around any model, share with anyone. Apache-2 -- [GitHub](https://github.com/gradio-app/gradio) (πŸ‘¨β€πŸ’» 410 Β· πŸ”€ 2.5K Β· πŸ“¦ 43K Β· πŸ“‹ 4.8K - 11% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/gradio-app/gradio) (πŸ‘¨β€πŸ’» 440 Β· πŸ”€ 2.5K Β· πŸ“¦ 44K Β· πŸ“‹ 5K - 10% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/gradio-app/gradio ``` -- [PyPi](https://pypi.org/project/gradio) (πŸ“₯ 6.4M / month Β· πŸ“¦ 800 Β· ⏱️ 09.10.2024): +- [PyPi](https://pypi.org/project/gradio) (πŸ“₯ 6.7M / month Β· πŸ“¦ 820 Β· ⏱️ 22.10.2024): ``` pip install gradio ```
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Autograd (πŸ₯‡36 Β· ⭐ 7K) - Efficiently computes derivatives of NumPy code. MIT +
Autograd (πŸ₯‡37 Β· ⭐ 7K) - Efficiently computes derivatives of NumPy code. MIT -- [GitHub](https://github.com/HIPS/autograd) (πŸ‘¨β€πŸ’» 59 Β· πŸ”€ 910 Β· πŸ“¦ 9.7K Β· πŸ“‹ 420 - 42% open Β· ⏱️ 07.10.2024): +- [GitHub](https://github.com/HIPS/autograd) (πŸ‘¨β€πŸ’» 60 Β· πŸ”€ 910 Β· πŸ“¦ 9.9K Β· πŸ“‹ 420 - 42% open Β· ⏱️ 21.10.2024): ``` git clone https://github.com/HIPS/autograd ``` -- [PyPi](https://pypi.org/project/autograd) (πŸ“₯ 2.6M / month Β· πŸ“¦ 280 Β· ⏱️ 22.08.2024): +- [PyPi](https://pypi.org/project/autograd) (πŸ“₯ 3.4M / month Β· πŸ“¦ 280 Β· ⏱️ 22.08.2024): ``` pip install autograd ``` @@ -7665,16 +7661,16 @@ _Libraries for connecting to, operating, and querying databases._
PennyLane (πŸ₯‡36 Β· ⭐ 2.3K) - PennyLane is a cross-platform Python library for quantum.. Apache-2 -- [GitHub](https://github.com/PennyLaneAI/pennylane) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 590 Β· πŸ“₯ 95 Β· πŸ“¦ 1.1K Β· πŸ“‹ 1.4K - 22% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/PennyLaneAI/pennylane) (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 600 Β· πŸ“₯ 96 Β· πŸ“¦ 1.1K Β· πŸ“‹ 1.4K - 22% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/PennyLaneAI/PennyLane ``` -- [PyPi](https://pypi.org/project/pennylane) (πŸ“₯ 72K / month Β· πŸ“¦ 120 Β· ⏱️ 12.09.2024): +- [PyPi](https://pypi.org/project/pennylane) (πŸ“₯ 75K / month Β· πŸ“¦ 120 Β· ⏱️ 12.09.2024): ``` pip install pennylane ``` -- [Conda](https://anaconda.org/conda-forge/pennylane) (πŸ“₯ 150K Β· ⏱️ 09.07.2024): +- [Conda](https://anaconda.org/conda-forge/pennylane) (πŸ“₯ 160K Β· ⏱️ 09.07.2024): ``` conda install -c conda-forge pennylane ``` @@ -7686,39 +7682,23 @@ _Libraries for connecting to, operating, and querying databases._ ``` git clone https://github.com/simonw/datasette ``` -- [PyPi](https://pypi.org/project/datasette) (πŸ“₯ 61K / month Β· πŸ“¦ 410 Β· ⏱️ 07.10.2024): +- [PyPi](https://pypi.org/project/datasette) (πŸ“₯ 76K / month Β· πŸ“¦ 410 Β· ⏱️ 07.10.2024): ``` pip install datasette ``` -- [Conda](https://anaconda.org/conda-forge/datasette) (πŸ“₯ 45K Β· ⏱️ 08.10.2024): +- [Conda](https://anaconda.org/conda-forge/datasette) (πŸ“₯ 46K Β· ⏱️ 08.10.2024): ``` conda install -c conda-forge datasette ```
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PyOD (πŸ₯‡35 Β· ⭐ 8.5K Β· πŸ“‰) - A Python Library for Outlier and Anomaly Detection, Integrating.. BSD-2 - -- [GitHub](https://github.com/yzhao062/pyod) (πŸ‘¨β€πŸ’» 60 Β· πŸ”€ 1.4K Β· πŸ“¦ 4.3K Β· πŸ“‹ 370 - 60% open Β· ⏱️ 05.09.2024): - - ``` - git clone https://github.com/yzhao062/pyod - ``` -- [PyPi](https://pypi.org/project/pyod) (πŸ“₯ 660K / month Β· πŸ“¦ 110 Β· ⏱️ 06.09.2024): - ``` - pip install pyod - ``` -- [Conda](https://anaconda.org/conda-forge/pyod) (πŸ“₯ 120K Β· ⏱️ 06.09.2024): - ``` - conda install -c conda-forge pyod - ``` -
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DeepChem (πŸ₯‡35 Β· ⭐ 5.4K) - Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry,.. MIT +
DeepChem (πŸ₯‡35 Β· ⭐ 5.5K) - Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry,.. MIT -- [GitHub](https://github.com/deepchem/deepchem) (πŸ‘¨β€πŸ’» 250 Β· πŸ”€ 1.7K Β· πŸ“¦ 440 Β· πŸ“‹ 1.9K - 33% open Β· ⏱️ 07.10.2024): +- [GitHub](https://github.com/deepchem/deepchem) (πŸ‘¨β€πŸ’» 250 Β· πŸ”€ 1.7K Β· πŸ“¦ 440 Β· πŸ“‹ 1.9K - 34% open Β· ⏱️ 21.10.2024): ``` git clone https://github.com/deepchem/deepchem ``` -- [PyPi](https://pypi.org/project/deepchem) (πŸ“₯ 70K / month Β· πŸ“¦ 13 Β· ⏱️ 07.10.2024): +- [PyPi](https://pypi.org/project/deepchem) (πŸ“₯ 99K / month Β· πŸ“¦ 13 Β· ⏱️ 21.10.2024): ``` pip install deepchem ``` @@ -7729,110 +7709,126 @@ _Libraries for connecting to, operating, and querying databases._
carla (πŸ₯ˆ34 Β· ⭐ 11K) - Open-source simulator for autonomous driving research. MIT -- [GitHub](https://github.com/carla-simulator/carla) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 3.6K Β· πŸ“¦ 810 Β· πŸ“‹ 5.6K - 19% open Β· ⏱️ 08.10.2024): +- [GitHub](https://github.com/carla-simulator/carla) (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 3.6K Β· πŸ“¦ 830 Β· πŸ“‹ 5.6K - 19% open Β· ⏱️ 18.10.2024): ``` git clone https://github.com/carla-simulator/carla ``` -- [PyPi](https://pypi.org/project/carla) (πŸ“₯ 19K / month Β· πŸ“¦ 11 Β· ⏱️ 14.11.2023): +- [PyPi](https://pypi.org/project/carla) (πŸ“₯ 16K / month Β· πŸ“¦ 11 Β· ⏱️ 14.11.2023): ``` pip install carla ```
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tensorly (πŸ₯ˆ34 Β· ⭐ 1.5K) - TensorLy: Tensor Learning in Python. BSD-2 +
PyOD (πŸ₯ˆ34 Β· ⭐ 8.5K) - A Python Library for Outlier and Anomaly Detection, Integrating Classical.. BSD-2 -- [GitHub](https://github.com/tensorly/tensorly) (πŸ‘¨β€πŸ’» 69 Β· πŸ”€ 290 Β· πŸ“¦ 770 Β· πŸ“‹ 270 - 21% open Β· ⏱️ 28.09.2024): +- [GitHub](https://github.com/yzhao062/pyod) (πŸ‘¨β€πŸ’» 60 Β· πŸ”€ 1.4K Β· πŸ“¦ 4.3K Β· πŸ“‹ 370 - 60% open Β· ⏱️ 05.09.2024): ``` - git clone https://github.com/tensorly/tensorly + git clone https://github.com/yzhao062/pyod ``` -- [PyPi](https://pypi.org/project/tensorly) (πŸ“₯ 110K / month Β· πŸ“¦ 92 Β· ⏱️ 08.03.2023): +- [PyPi](https://pypi.org/project/pyod) (πŸ“₯ 660K / month Β· πŸ“¦ 110 Β· ⏱️ 06.09.2024): ``` - pip install tensorly + pip install pyod ``` -- [Conda](https://anaconda.org/conda-forge/tensorly) (πŸ“₯ 370K Β· ⏱️ 10.06.2024): +- [Conda](https://anaconda.org/conda-forge/pyod) (πŸ“₯ 120K Β· ⏱️ 06.09.2024): ``` - conda install -c conda-forge tensorly + conda install -c conda-forge pyod ```
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hdbscan (πŸ₯ˆ33 Β· ⭐ 2.8K) - A high performance implementation of HDBSCAN clustering. BSD-3 +
hdbscan (πŸ₯ˆ34 Β· ⭐ 2.8K) - A high performance implementation of HDBSCAN clustering. BSD-3 -- [GitHub](https://github.com/scikit-learn-contrib/hdbscan) (πŸ‘¨β€πŸ’» 92 Β· πŸ”€ 500 Β· πŸ“¦ 4.1K Β· πŸ“‹ 530 - 67% open Β· ⏱️ 08.10.2024): +- [GitHub](https://github.com/scikit-learn-contrib/hdbscan) (πŸ‘¨β€πŸ’» 94 Β· πŸ”€ 500 Β· πŸ“¦ 4.2K Β· πŸ“‹ 530 - 67% open Β· ⏱️ 23.10.2024): ``` git clone https://github.com/scikit-learn-contrib/hdbscan ``` -- [PyPi](https://pypi.org/project/hdbscan) (πŸ“₯ 620K / month Β· πŸ“¦ 330 Β· ⏱️ 08.10.2024): +- [PyPi](https://pypi.org/project/hdbscan) (πŸ“₯ 660K / month Β· πŸ“¦ 340 Β· ⏱️ 12.10.2024): ``` pip install hdbscan ``` -- [Conda](https://anaconda.org/conda-forge/hdbscan) (πŸ“₯ 2.2M Β· ⏱️ 08.10.2024): +- [Conda](https://anaconda.org/conda-forge/hdbscan) (πŸ“₯ 2.2M Β· ⏱️ 12.10.2024): ``` conda install -c conda-forge hdbscan ```
+
River (πŸ₯ˆ33 Β· ⭐ 5.1K) - Online machine learning in Python. BSD-3 + +- [GitHub](https://github.com/online-ml/river) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 540 Β· πŸ“¦ 580 Β· πŸ“‹ 610 - 18% open Β· ⏱️ 03.10.2024): + + ``` + git clone https://github.com/online-ml/river + ``` +- [PyPi](https://pypi.org/project/river) (πŸ“₯ 740K / month Β· πŸ“¦ 56 Β· ⏱️ 09.07.2024): + ``` + pip install river + ``` +- [Conda](https://anaconda.org/conda-forge/river) (πŸ“₯ 83K Β· ⏱️ 06.10.2023): + ``` + conda install -c conda-forge river + ``` +
Pythran (πŸ₯ˆ33 Β· ⭐ 2K) - Ahead of Time compiler for numeric kernels. BSD-3 -- [GitHub](https://github.com/serge-sans-paille/pythran) (πŸ‘¨β€πŸ’» 73 Β· πŸ”€ 190 Β· πŸ“¦ 2.7K Β· πŸ“‹ 870 - 15% open Β· ⏱️ 23.09.2024): +- [GitHub](https://github.com/serge-sans-paille/pythran) (πŸ‘¨β€πŸ’» 73 Β· πŸ”€ 190 Β· πŸ“¦ 2.7K Β· πŸ“‹ 870 - 15% open Β· ⏱️ 18.10.2024): ``` git clone https://github.com/serge-sans-paille/pythran ``` -- [PyPi](https://pypi.org/project/pythran) (πŸ“₯ 200K / month Β· πŸ“¦ 19 Β· ⏱️ 28.05.2024): +- [PyPi](https://pypi.org/project/pythran) (πŸ“₯ 250K / month Β· πŸ“¦ 19 Β· ⏱️ 28.05.2024): ``` pip install pythran ``` -- [Conda](https://anaconda.org/conda-forge/pythran) (πŸ“₯ 720K Β· ⏱️ 03.09.2024): +- [Conda](https://anaconda.org/conda-forge/pythran) (πŸ“₯ 740K Β· ⏱️ 03.09.2024): ``` conda install -c conda-forge pythran ```
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agate (πŸ₯ˆ33 Β· ⭐ 1.2K) - A Python data analysis library that is optimized for humans instead of.. MIT +
tensorly (πŸ₯ˆ33 Β· ⭐ 1.6K) - TensorLy: Tensor Learning in Python. BSD-2 -- [GitHub](https://github.com/wireservice/agate) (πŸ‘¨β€πŸ’» 53 Β· πŸ”€ 160 Β· πŸ“¦ 3.8K Β· πŸ“‹ 650 - 0% open Β· ⏱️ 30.07.2024): +- [GitHub](https://github.com/tensorly/tensorly) (πŸ‘¨β€πŸ’» 69 Β· πŸ”€ 290 Β· πŸ“¦ 780 Β· πŸ“‹ 270 - 21% open Β· ⏱️ 22.10.2024): ``` - git clone https://github.com/wireservice/agate + git clone https://github.com/tensorly/tensorly ``` -- [PyPi](https://pypi.org/project/agate) (πŸ“₯ 11M / month Β· πŸ“¦ 49 Β· ⏱️ 30.07.2024): +- [PyPi](https://pypi.org/project/tensorly) (πŸ“₯ 93K / month Β· πŸ“¦ 92 Β· ⏱️ 08.03.2023): ``` - pip install agate + pip install tensorly ``` -- [Conda](https://anaconda.org/conda-forge/agate) (πŸ“₯ 240K Β· ⏱️ 30.07.2024): +- [Conda](https://anaconda.org/conda-forge/tensorly) (πŸ“₯ 370K Β· ⏱️ 10.06.2024): ``` - conda install -c conda-forge agate + conda install -c conda-forge tensorly ```
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River (πŸ₯ˆ32 Β· ⭐ 5K) - Online machine learning in Python. BSD-3 +
agate (πŸ₯ˆ33 Β· ⭐ 1.2K) - A Python data analysis library that is optimized for humans instead of.. MIT -- [GitHub](https://github.com/online-ml/river) (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 540 Β· πŸ“¦ 570 Β· πŸ“‹ 610 - 18% open Β· ⏱️ 03.10.2024): +- [GitHub](https://github.com/wireservice/agate) (πŸ‘¨β€πŸ’» 53 Β· πŸ”€ 160 Β· πŸ“¦ 3.9K Β· πŸ“‹ 650 - 0% open Β· ⏱️ 30.07.2024): ``` - git clone https://github.com/online-ml/river + git clone https://github.com/wireservice/agate ``` -- [PyPi](https://pypi.org/project/river) (πŸ“₯ 78K / month Β· πŸ“¦ 56 Β· ⏱️ 09.07.2024): +- [PyPi](https://pypi.org/project/agate) (πŸ“₯ 11M / month Β· πŸ“¦ 49 Β· ⏱️ 30.07.2024): ``` - pip install river + pip install agate ``` -- [Conda](https://anaconda.org/conda-forge/river) (πŸ“₯ 81K Β· ⏱️ 06.10.2023): +- [Conda](https://anaconda.org/conda-forge/agate) (πŸ“₯ 240K Β· ⏱️ 30.07.2024): ``` - conda install -c conda-forge river + conda install -c conda-forge agate ```
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pyopencl (πŸ₯ˆ32 Β· ⭐ 1.1K) - OpenCL integration for Python, plus shiny features. MIT +
datalad (πŸ₯ˆ32 Β· ⭐ 530) - Keep code, data, containers under control with git and git-annex. MIT -- [GitHub](https://github.com/inducer/pyopencl) (πŸ‘¨β€πŸ’» 96 Β· πŸ”€ 240 Β· πŸ“¦ 2K Β· πŸ“‹ 350 - 20% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/datalad/datalad) (πŸ‘¨β€πŸ’» 57 Β· πŸ”€ 110 Β· πŸ“¦ 430 Β· πŸ“‹ 3.9K - 13% open Β· ⏱️ 14.10.2024): ``` - git clone https://github.com/inducer/pyopencl + git clone https://github.com/datalad/datalad ``` -- [PyPi](https://pypi.org/project/pyopencl) (πŸ“₯ 82K / month Β· πŸ“¦ 170 Β· ⏱️ 25.06.2024): +- [PyPi](https://pypi.org/project/datalad) (πŸ“₯ 50K / month Β· πŸ“¦ 95 Β· ⏱️ 08.08.2024): ``` - pip install pyopencl + pip install datalad ``` -- [Conda](https://anaconda.org/conda-forge/pyopencl) (πŸ“₯ 1.3M Β· ⏱️ 26.06.2024): +- [Conda](https://anaconda.org/conda-forge/datalad) (πŸ“₯ 640K Β· ⏱️ 08.08.2024): ``` - conda install -c conda-forge pyopencl + conda install -c conda-forge datalad ```
PaddleHub (πŸ₯ˆ31 Β· ⭐ 13K) - Awesome pre-trained models toolkit based on PaddlePaddle... Apache-2 @@ -7842,14 +7838,26 @@ _Libraries for connecting to, operating, and querying databases._ ``` git clone https://github.com/PaddlePaddle/PaddleHub ``` -- [PyPi](https://pypi.org/project/paddlehub) (πŸ“₯ 5.2K / month Β· πŸ“¦ 7 Β· ⏱️ 20.09.2023): +- [PyPi](https://pypi.org/project/paddlehub) (πŸ“₯ 6.2K / month Β· πŸ“¦ 7 Β· ⏱️ 20.09.2023): ``` pip install paddlehub ```
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pyjanitor (πŸ₯ˆ31 Β· ⭐ 1.3K) - Clean APIs for data cleaning. Python implementation of R package.. MIT +
causalml (πŸ₯ˆ31 Β· ⭐ 5.1K Β· πŸ“ˆ) - Uplift modeling and causal inference with machine learning.. Apache-2 + +- [GitHub](https://github.com/uber/causalml) (πŸ‘¨β€πŸ’» 64 Β· πŸ”€ 780 Β· πŸ“¦ 230 Β· πŸ“‹ 400 - 13% open Β· ⏱️ 16.10.2024): + + ``` + git clone https://github.com/uber/causalml + ``` +- [PyPi](https://pypi.org/project/causalml) (πŸ“₯ 60K / month Β· πŸ“¦ 2 Β· ⏱️ 01.10.2024): + ``` + pip install causalml + ``` +
+
pyjanitor (πŸ₯ˆ31 Β· ⭐ 1.4K) - Clean APIs for data cleaning. Python implementation of R package.. MIT -- [GitHub](https://github.com/pyjanitor-devs/pyjanitor) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 170 Β· πŸ“¦ 720 Β· πŸ“‹ 560 - 19% open Β· ⏱️ 08.10.2024): +- [GitHub](https://github.com/pyjanitor-devs/pyjanitor) (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 170 Β· πŸ“¦ 730 Β· πŸ“‹ 560 - 19% open Β· ⏱️ 20.10.2024): ``` git clone https://github.com/pyjanitor-devs/pyjanitor @@ -7858,66 +7866,70 @@ _Libraries for connecting to, operating, and querying databases._ ``` pip install pyjanitor ``` -- [Conda](https://anaconda.org/conda-forge/pyjanitor) (πŸ“₯ 210K Β· ⏱️ 28.09.2024): +- [Conda](https://anaconda.org/conda-forge/pyjanitor) (πŸ“₯ 220K Β· ⏱️ 28.09.2024): ``` conda install -c conda-forge pyjanitor ```
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datalad (πŸ₯ˆ31 Β· ⭐ 530) - Keep code, data, containers under control with git and git-annex. MIT +
pyopencl (πŸ₯ˆ31 Β· ⭐ 1.1K) - OpenCL integration for Python, plus shiny features. MIT -- [GitHub](https://github.com/datalad/datalad) (πŸ‘¨β€πŸ’» 57 Β· πŸ”€ 110 Β· πŸ“¦ 420 Β· πŸ“‹ 3.9K - 13% open Β· ⏱️ 30.09.2024): +- [GitHub](https://github.com/inducer/pyopencl) (πŸ‘¨β€πŸ’» 96 Β· πŸ”€ 240 Β· πŸ“¦ 2.1K Β· πŸ“‹ 360 - 21% open Β· ⏱️ 18.10.2024): ``` - git clone https://github.com/datalad/datalad + git clone https://github.com/inducer/pyopencl ``` -- [PyPi](https://pypi.org/project/datalad) (πŸ“₯ 46K / month Β· πŸ“¦ 95 Β· ⏱️ 08.08.2024): +- [PyPi](https://pypi.org/project/pyopencl) (πŸ“₯ 98K / month Β· πŸ“¦ 170 Β· ⏱️ 18.10.2024): ``` - pip install datalad + pip install pyopencl ``` -- [Conda](https://anaconda.org/conda-forge/datalad) (πŸ“₯ 630K Β· ⏱️ 08.08.2024): +- [Conda](https://anaconda.org/conda-forge/pyopencl) (πŸ“₯ 1.3M Β· ⏱️ 22.10.2024): ``` - conda install -c conda-forge datalad + conda install -c conda-forge pyopencl ```
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causalml (πŸ₯ˆ29 Β· ⭐ 5K) - Uplift modeling and causal inference with machine learning algorithms. Apache-2 +
anomalib (πŸ₯ˆ30 Β· ⭐ 3.8K) - An anomaly detection library comprising state-of-the-art algorithms.. Apache-2 -- [GitHub](https://github.com/uber/causalml) (πŸ‘¨β€πŸ’» 64 Β· πŸ”€ 770 Β· πŸ“¦ 220 Β· πŸ“‹ 400 - 13% open Β· ⏱️ 07.10.2024): +- [GitHub](https://github.com/openvinotoolkit/anomalib) (πŸ‘¨β€πŸ’» 81 Β· πŸ”€ 660 Β· πŸ“₯ 15K Β· πŸ“¦ 100 Β· πŸ“‹ 940 - 15% open Β· ⏱️ 24.10.2024): ``` - git clone https://github.com/uber/causalml + git clone https://github.com/openvinotoolkit/anomalib ``` -- [PyPi](https://pypi.org/project/causalml) (πŸ“₯ 51K / month Β· πŸ“¦ 2 Β· ⏱️ 01.10.2024): +- [PyPi](https://pypi.org/project/anomalib) (πŸ“₯ 68K / month Β· πŸ“¦ 5 Β· ⏱️ 12.08.2024): ``` - pip install causalml + pip install anomalib ```
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anomalib (πŸ₯ˆ29 Β· ⭐ 3.7K) - An anomaly detection library comprising state-of-the-art algorithms.. Apache-2 +
TabPy (πŸ₯ˆ29 Β· ⭐ 1.6K) - Execute Python code on the fly and display results in Tableau visualizations:. MIT -- [GitHub](https://github.com/openvinotoolkit/anomalib) (πŸ‘¨β€πŸ’» 81 Β· πŸ”€ 660 Β· πŸ“₯ 14K Β· πŸ“¦ 98 Β· πŸ“‹ 920 - 15% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/tableau/TabPy) (πŸ‘¨β€πŸ’» 51 Β· πŸ”€ 590 Β· πŸ“¦ 180 Β· πŸ“‹ 320 - 6% open Β· ⏱️ 23.09.2024): ``` - git clone https://github.com/openvinotoolkit/anomalib + git clone https://github.com/tableau/TabPy ``` -- [PyPi](https://pypi.org/project/anomalib) (πŸ“₯ 59K / month Β· πŸ“¦ 5 Β· ⏱️ 12.08.2024): +- [PyPi](https://pypi.org/project/tabpy) (πŸ“₯ 42K / month Β· πŸ“¦ 2 Β· ⏱️ 23.09.2024): ``` - pip install anomalib + pip install tabpy + ``` +- [Conda](https://anaconda.org/anaconda/tabpy-client) (πŸ“₯ 4.6K Β· ⏱️ 16.06.2023): + ``` + conda install -c anaconda tabpy-client ```
dstack (πŸ₯ˆ29 Β· ⭐ 1.4K) - dstack is an open-source alternative to Kubernetes, designed to.. MPL-2.0 -- [GitHub](https://github.com/dstackai/dstack) (πŸ‘¨β€πŸ’» 36 Β· πŸ”€ 120 Β· πŸ“¦ 16 Β· πŸ“‹ 960 - 11% open Β· ⏱️ 10.10.2024): +- [GitHub](https://github.com/dstackai/dstack) (πŸ‘¨β€πŸ’» 42 Β· πŸ”€ 140 Β· πŸ“¦ 16 Β· πŸ“‹ 980 - 10% open Β· ⏱️ 24.10.2024): ``` git clone https://github.com/dstackai/dstack ``` -- [PyPi](https://pypi.org/project/dstack) (πŸ“₯ 9.7K / month Β· ⏱️ 09.10.2024): +- [PyPi](https://pypi.org/project/dstack) (πŸ“₯ 18K / month Β· ⏱️ 23.10.2024): ``` pip install dstack ```
Prince (πŸ₯ˆ29 Β· ⭐ 1.3K) - 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“¦ 610 Β· πŸ“‹ 140 - 6% open Β· ⏱️ 07.09.2024): +- [GitHub](https://github.com/MaxHalford/prince) (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 180 Β· πŸ“¦ 620 Β· πŸ“‹ 140 - 6% open Β· ⏱️ 07.09.2024): ``` git clone https://github.com/MaxHalford/prince @@ -7931,20 +7943,16 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge prince-factor-analysis ```
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TabPy (πŸ₯ˆ28 Β· ⭐ 1.6K) - Execute Python code on the fly and display results in Tableau visualizations:. MIT +
pycm (πŸ₯ˆ28 Β· ⭐ 1.4K Β· πŸ“ˆ) - Multi-class confusion matrix library in Python. MIT -- [GitHub](https://github.com/tableau/TabPy) (πŸ‘¨β€πŸ’» 51 Β· πŸ”€ 590 Β· πŸ“¦ 180 Β· πŸ“‹ 320 - 6% open Β· ⏱️ 23.09.2024): +- [GitHub](https://github.com/sepandhaghighi/pycm) (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 120 Β· πŸ“¦ 340 Β· πŸ“‹ 200 - 5% open Β· ⏱️ 15.10.2024): ``` - git clone https://github.com/tableau/TabPy - ``` -- [PyPi](https://pypi.org/project/tabpy) (πŸ“₯ 7.2K / month Β· πŸ“¦ 2 Β· ⏱️ 23.09.2024): + git clone https://github.com/sepandhaghighi/pycm ``` - pip install tabpy - ``` -- [Conda](https://anaconda.org/anaconda/tabpy-client) (πŸ“₯ 4.6K Β· ⏱️ 16.06.2023): +- [PyPi](https://pypi.org/project/pycm) (πŸ“₯ 41K / month Β· πŸ“¦ 24 Β· ⏱️ 17.10.2024): ``` - conda install -c anaconda tabpy-client + pip install pycm ```
kmodes (πŸ₯ˆ28 Β· ⭐ 1.2K Β· πŸ’€) - Python implementations of the k-modes and k-prototypes clustering.. MIT @@ -7954,7 +7962,7 @@ _Libraries for connecting to, operating, and querying databases._ ``` git clone https://github.com/nicodv/kmodes ``` -- [PyPi](https://pypi.org/project/kmodes) (πŸ“₯ 280K / month Β· πŸ“¦ 38 Β· ⏱️ 06.09.2022): +- [PyPi](https://pypi.org/project/kmodes) (πŸ“₯ 260K / month Β· πŸ“¦ 38 Β· ⏱️ 06.09.2022): ``` pip install kmodes ``` @@ -7963,14 +7971,14 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge kmodes ```
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adapter-transformers (πŸ₯‰27 Β· ⭐ 2.5K) - A Unified Library for Parameter-Efficient and Modular.. Apache-2 huggingface +
adapter-transformers (πŸ₯‰27 Β· ⭐ 2.6K) - A Unified Library for Parameter-Efficient and Modular.. Apache-2 huggingface -- [GitHub](https://github.com/adapter-hub/adapters) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 340 Β· πŸ“¦ 110 Β· πŸ“‹ 380 - 10% open Β· ⏱️ 22.08.2024): +- [GitHub](https://github.com/adapter-hub/adapters) (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 340 Β· πŸ“¦ 110 Β· πŸ“‹ 390 - 11% open Β· ⏱️ 13.10.2024): ``` git clone https://github.com/Adapter-Hub/adapter-transformers ``` -- [PyPi](https://pypi.org/project/adapter-transformers) (πŸ“₯ 24K / month Β· πŸ“¦ 12 Β· ⏱️ 07.07.2024): +- [PyPi](https://pypi.org/project/adapter-transformers) (πŸ“₯ 32K / month Β· πŸ“¦ 12 Β· ⏱️ 07.07.2024): ``` pip install adapter-transformers ``` @@ -7982,11 +7990,11 @@ _Libraries for connecting to, operating, and querying databases._ ``` git clone https://github.com/annoviko/pyclustering ``` -- [PyPi](https://pypi.org/project/pyclustering) (πŸ“₯ 28K / month Β· πŸ“¦ 32 Β· ⏱️ 25.11.2020): +- [PyPi](https://pypi.org/project/pyclustering) (πŸ“₯ 30K / month Β· πŸ“¦ 32 Β· ⏱️ 25.11.2020): ``` pip install pyclustering ``` -- [Conda](https://anaconda.org/conda-forge/pyclustering) (πŸ“₯ 90K Β· ⏱️ 16.11.2023): +- [Conda](https://anaconda.org/conda-forge/pyclustering) (πŸ“₯ 92K Β· ⏱️ 16.11.2023): ``` conda install -c conda-forge pyclustering ``` @@ -7998,7 +8006,7 @@ _Libraries for connecting to, operating, and querying databases._ ``` git clone https://github.com/google/trax ``` -- [PyPi](https://pypi.org/project/trax) (πŸ“₯ 6K / month Β· πŸ“¦ 1 Β· ⏱️ 26.10.2021): +- [PyPi](https://pypi.org/project/trax) (πŸ“₯ 5.8K / month Β· πŸ“¦ 1 Β· ⏱️ 26.10.2021): ``` pip install trax ``` @@ -8010,35 +8018,35 @@ _Libraries for connecting to, operating, and querying databases._ ``` git clone https://github.com/solegalli/feature_engine ``` -- [PyPi](https://pypi.org/project/feature_engine) (πŸ“₯ 180K / month Β· πŸ“¦ 160 Β· ⏱️ 31.08.2024): +- [PyPi](https://pypi.org/project/feature_engine) (πŸ“₯ 220K / month Β· πŸ“¦ 160 Β· ⏱️ 31.08.2024): ``` pip install feature_engine ``` -- [Conda](https://anaconda.org/conda-forge/feature_engine) (πŸ“₯ 58K Β· ⏱️ 01.09.2024): +- [Conda](https://anaconda.org/conda-forge/feature_engine) (πŸ“₯ 59K Β· ⏱️ 01.09.2024): ``` conda install -c conda-forge feature_engine ```
avalanche (πŸ₯‰26 Β· ⭐ 1.8K) - Avalanche: an End-to-End Library for Continual Learning based on.. MIT -- [GitHub](https://github.com/ContinualAI/avalanche) (πŸ‘¨β€πŸ’» 80 Β· πŸ”€ 290 Β· πŸ“₯ 35 Β· πŸ“¦ 110 Β· πŸ“‹ 810 - 11% open Β· ⏱️ 03.06.2024): +- [GitHub](https://github.com/ContinualAI/avalanche) (πŸ‘¨β€πŸ’» 80 Β· πŸ”€ 290 Β· πŸ“₯ 35 Β· πŸ“¦ 110 Β· πŸ“‹ 820 - 11% open Β· ⏱️ 03.06.2024): ``` git clone https://github.com/ContinualAI/avalanche ``` -- [PyPi](https://pypi.org/project/avalanche-lib) (πŸ“₯ 2.2K / month Β· πŸ“¦ 3 Β· ⏱️ 27.02.2024): +- [PyPi](https://pypi.org/project/avalanche-lib) (πŸ“₯ 2.8K / month Β· πŸ“¦ 3 Β· ⏱️ 27.02.2024): ``` pip install avalanche-lib ```
AugLy (πŸ₯‰25 Β· ⭐ 5K) - A data augmentations library for audio, image, text, and video. MIT -- [GitHub](https://github.com/facebookresearch/AugLy) (πŸ‘¨β€πŸ’» 37 Β· πŸ”€ 300 Β· πŸ“¦ 140 Β· πŸ“‹ 78 - 30% open Β· ⏱️ 09.10.2024): +- [GitHub](https://github.com/facebookresearch/AugLy) (πŸ‘¨β€πŸ’» 37 Β· πŸ”€ 300 Β· πŸ“¦ 150 Β· πŸ“‹ 78 - 30% open Β· ⏱️ 09.10.2024): ``` git clone https://github.com/facebookresearch/AugLy ``` -- [PyPi](https://pypi.org/project/augly) (πŸ“₯ 3K / month Β· πŸ“¦ 4 Β· ⏱️ 05.12.2023): +- [PyPi](https://pypi.org/project/augly) (πŸ“₯ 4.4K / month Β· πŸ“¦ 4 Β· ⏱️ 05.12.2023): ``` pip install augly ``` @@ -8050,7 +8058,7 @@ _Libraries for connecting to, operating, and querying databases._ ``` git clone https://github.com/scikit-learn-contrib/metric-learn ``` -- [PyPi](https://pypi.org/project/metric-learn) (πŸ“₯ 5.2K / month Β· πŸ“¦ 7 Β· ⏱️ 09.10.2023): +- [PyPi](https://pypi.org/project/metric-learn) (πŸ“₯ 5.4K / month Β· πŸ“¦ 7 Β· ⏱️ 09.10.2023): ``` pip install metric-learn ``` @@ -8066,11 +8074,23 @@ _Libraries for connecting to, operating, and querying databases._ ``` git clone https://github.com/mars-project/mars ``` -- [PyPi](https://pypi.org/project/pymars) (πŸ“₯ 25K / month Β· πŸ“¦ 2 Β· ⏱️ 12.06.2022): +- [PyPi](https://pypi.org/project/pymars) (πŸ“₯ 44K / month Β· πŸ“¦ 2 Β· ⏱️ 12.06.2022): ``` pip install pymars ```
+
MONAILabel (πŸ₯‰24 Β· ⭐ 600) - MONAI Label is an intelligent open source image labeling and.. Apache-2 + +- [GitHub](https://github.com/Project-MONAI/MONAILabel) (πŸ‘¨β€πŸ’» 62 Β· πŸ”€ 190 Β· πŸ“₯ 98K Β· πŸ“‹ 530 - 24% open Β· ⏱️ 22.10.2024): + + ``` + git clone https://github.com/Project-MONAI/MONAILabel + ``` +- [PyPi](https://pypi.org/project/monailabel-weekly) (πŸ“₯ 5.1K / month Β· ⏱️ 01.10.2023): + ``` + pip install monailabel-weekly + ``` +
BioPandas (πŸ₯‰23 Β· ⭐ 710) - Working with molecular structures in pandas DataFrames. BSD-3 - [GitHub](https://github.com/BioPandas/biopandas) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 120 Β· πŸ“¦ 290 Β· πŸ“‹ 59 - 35% open Β· ⏱️ 01.08.2024): @@ -8087,26 +8107,14 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge biopandas ```
-
MONAILabel (πŸ₯‰23 Β· ⭐ 600) - MONAI Label is an intelligent open source image labeling and.. Apache-2 - -- [GitHub](https://github.com/Project-MONAI/MONAILabel) (πŸ‘¨β€πŸ’» 61 Β· πŸ”€ 190 Β· πŸ“₯ 95K Β· πŸ“‹ 530 - 24% open Β· ⏱️ 27.09.2024): - - ``` - git clone https://github.com/Project-MONAI/MONAILabel - ``` -- [PyPi](https://pypi.org/project/monailabel-weekly) (πŸ“₯ 2.4K / month Β· ⏱️ 01.10.2023): - ``` - pip install monailabel-weekly - ``` -
AstroML (πŸ₯‰22 Β· ⭐ 1.1K Β· πŸ’€) - Machine learning, statistics, and data mining for astronomy.. BSD-2 -- [GitHub](https://github.com/astroML/astroML) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 290 Β· πŸ“‹ 160 - 38% open Β· ⏱️ 04.01.2024): +- [GitHub](https://github.com/astroML/astroML) (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 300 Β· πŸ“‹ 160 - 38% open Β· ⏱️ 04.01.2024): ``` git clone https://github.com/astroML/astroML ``` -- [PyPi](https://pypi.org/project/astroML) (πŸ“₯ 2.3K / month Β· πŸ“¦ 16 Β· ⏱️ 01.03.2022): +- [PyPi](https://pypi.org/project/astroML) (πŸ“₯ 3.6K / month Β· πŸ“¦ 16 Β· ⏱️ 01.03.2022): ``` pip install astroML ``` @@ -8115,6 +8123,18 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge astroml ```
+
benchmark_VAE (πŸ₯‰21 Β· ⭐ 1.8K) - Unifying Variational Autoencoder (VAE) implementations.. Apache-2 + +- [GitHub](https://github.com/clementchadebec/benchmark_VAE) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 160 Β· πŸ“¦ 33 Β· πŸ“‹ 66 - 36% open Β· ⏱️ 17.07.2024): + + ``` + git clone https://github.com/clementchadebec/benchmark_VAE + ``` +- [PyPi](https://pypi.org/project/pythae) (πŸ“₯ 2.2K / month Β· ⏱️ 06.09.2023): + ``` + pip install pythae + ``` +
pykale (πŸ₯‰21 Β· ⭐ 440) - Knowledge-Aware machine LEarning (KALE): accessible machine learning.. MIT - [GitHub](https://github.com/pykale/pykale) (πŸ‘¨β€πŸ’» 25 Β· πŸ”€ 64 Β· πŸ“¦ 4 Β· πŸ“‹ 120 - 8% open Β· ⏱️ 24.09.2024): @@ -8122,7 +8142,7 @@ _Libraries for connecting to, operating, and querying databases._ ``` git clone https://github.com/pykale/pykale ``` -- [PyPi](https://pypi.org/project/pykale) (πŸ“₯ 530 / month Β· ⏱️ 12.04.2022): +- [PyPi](https://pypi.org/project/pykale) (πŸ“₯ 780 / month Β· ⏱️ 12.04.2022): ``` pip install pykale ``` @@ -8134,70 +8154,57 @@ _Libraries for connecting to, operating, and querying databases._ ``` git clone https://github.com/yzhao062/SUOD ``` -- [PyPi](https://pypi.org/project/suod) (πŸ“₯ 9.4K / month Β· πŸ“¦ 8 Β· ⏱️ 08.02.2024): +- [PyPi](https://pypi.org/project/suod) (πŸ“₯ 9.2K / month Β· πŸ“¦ 8 Β· ⏱️ 08.02.2024): ``` pip install suod ```
-
benchmark_VAE (πŸ₯‰20 Β· ⭐ 1.8K) - Unifying Variational Autoencoder (VAE) implementations.. Apache-2 - -- [GitHub](https://github.com/clementchadebec/benchmark_VAE) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 160 Β· πŸ“¦ 33 Β· πŸ“‹ 65 - 36% open Β· ⏱️ 17.07.2024): - - ``` - git clone https://github.com/clementchadebec/benchmark_VAE - ``` -- [PyPi](https://pypi.org/project/pythae) (πŸ“₯ 2.2K / month Β· ⏱️ 06.09.2023): - ``` - pip install pythae - ``` -
-
pymdp (πŸ₯‰18 Β· ⭐ 450) - A Python implementation of active inference for Markov Decision Processes. MIT +
pymdp (πŸ₯‰20 Β· ⭐ 460) - A Python implementation of active inference for Markov Decision Processes. MIT -- [GitHub](https://github.com/infer-actively/pymdp) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 84 Β· πŸ“¦ 13 Β· πŸ“‹ 42 - 35% open Β· ⏱️ 16.07.2024): +- [GitHub](https://github.com/infer-actively/pymdp) (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 85 Β· πŸ“¦ 13 Β· πŸ“‹ 44 - 38% open Β· ⏱️ 16.07.2024): ``` git clone https://github.com/infer-actively/pymdp ``` -- [PyPi](https://pypi.org/project/inferactively-pymdp) (πŸ“₯ 770 / month Β· ⏱️ 08.12.2022): +- [PyPi](https://pypi.org/project/inferactively-pymdp) (πŸ“₯ 1.3K / month Β· ⏱️ 08.12.2022): ``` pip install inferactively-pymdp ```
NeuralCompression (πŸ₯‰16 Β· ⭐ 500) - A collection of tools for neural compression enthusiasts. MIT -- [GitHub](https://github.com/facebookresearch/NeuralCompression) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 44 Β· πŸ“‹ 71 - 8% open Β· ⏱️ 20.09.2024): +- [GitHub](https://github.com/facebookresearch/NeuralCompression) (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 43 Β· πŸ“‹ 71 - 8% open Β· ⏱️ 20.09.2024): ``` git clone https://github.com/facebookresearch/NeuralCompression ``` -- [PyPi](https://pypi.org/project/neuralcompression) (πŸ“₯ 320 / month Β· ⏱️ 03.10.2023): +- [PyPi](https://pypi.org/project/neuralcompression) (πŸ“₯ 440 / month Β· ⏱️ 03.10.2023): ``` pip install neuralcompression ```
-
Show 25 hidden projects... +
Show 24 hidden projects... -- cleanlab (πŸ₯ˆ31 Β· ⭐ 9.6K Β· πŸ“‰) - The standard data-centric AI package for data quality and.. ❗️AGPL-3.0 -- Cython BLIS (πŸ₯ˆ31 Β· ⭐ 220) - Fast matrix-multiplication as a self-contained Python library no.. BSD-3 -- alibi-detect (πŸ₯ˆ28 Β· ⭐ 2.2K) - Algorithms for outlier, adversarial and drift detection. ❗️Intel +- cleanlab (πŸ₯ˆ31 Β· ⭐ 9.6K) - The standard data-centric AI package for data quality and machine.. ❗️AGPL-3.0 +- Cython BLIS (πŸ₯ˆ30 Β· ⭐ 220) - Fast matrix-multiplication as a self-contained Python library no.. BSD-3 +- pysc2 (πŸ₯ˆ28 Β· ⭐ 8K Β· πŸ’€) - StarCraft II Learning Environment. Apache-2 - modAL (πŸ₯ˆ28 Β· ⭐ 2.2K Β· πŸ’€) - A modular active learning framework for Python. MIT - minisom (πŸ₯ˆ28 Β· ⭐ 1.4K) - MiniSom is a minimalistic implementation of the Self Organizing.. ❗️CC-BY-3.0 - PySwarms (πŸ₯ˆ28 Β· ⭐ 1.3K Β· πŸ’€) - A research toolkit for particle swarm optimization in Python. MIT -- pysc2 (πŸ₯‰27 Β· ⭐ 8K Β· πŸ’€) - StarCraft II Learning Environment. Apache-2 +- alibi-detect (πŸ₯‰27 Β· ⭐ 2.2K) - Algorithms for outlier, adversarial and drift detection. ❗️Intel - 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 - findspark (πŸ₯‰24 Β· ⭐ 510 Β· πŸ’€) - Find pyspark to make it importable. BSD-3 - vecstack (πŸ₯‰23 Β· ⭐ 680 Β· πŸ’€) - Python package for stacking (machine learning technique). MIT - pandas-ai (πŸ₯‰22 Β· ⭐ 13K) - Chat with your database (SQL, CSV, pandas, polars, mongodb,.. ❗Unlicensed - opyrator (πŸ₯‰22 Β· ⭐ 3.1K Β· πŸ’€) - Turns your machine learning code into microservices with web API,.. MIT - mlens (πŸ₯‰22 Β· ⭐ 850 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 +- apricot (πŸ₯‰22 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· ⭐ 2.9K Β· πŸ’€) - StreamAlert is a serverless, realtime data analysis.. Apache-2 - rrcf (πŸ₯‰20 Β· ⭐ 500 Β· πŸ’€) - Implementation of the Robust Random Cut Forest algorithm for anomaly.. MIT +- baikal (πŸ₯‰19 Β· ⭐ 590 Β· πŸ’€) - A graph-based functional API for building complex scikit-learn.. BSD-3 - scikit-rebate (πŸ₯‰19 Β· ⭐ 410 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 - KD-Lib (πŸ₯‰16 Β· ⭐ 600 Β· πŸ’€) - A Pytorch Knowledge Distillation library for benchmarking and.. MIT - pandas-ml (πŸ₯‰16 Β· ⭐ 320 Β· πŸ’€) - pandas, scikit-learn, xgboost and seaborn integration. BSD-3 - nylon (πŸ₯‰14 Β· ⭐ 83 Β· πŸ’€) - An intelligent, flexible grammar of machine learning. MIT diff --git a/history/2024-10-24_changes.md b/history/2024-10-24_changes.md new file mode 100644 index 0000000..65fb75e --- /dev/null +++ b/history/2024-10-24_changes.md @@ -0,0 +1,30 @@ +## 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._ + +- Core ML Tools (πŸ₯ˆ36 Β· ⭐ 4.4K Β· πŸ“ˆ) - Core ML tools contain supporting tools for Core ML model.. BSD-3 +- optimum (πŸ₯‡36 Β· ⭐ 2.5K Β· πŸ“ˆ) - Accelerate training and inference of Transformers and Diffusers.. Apache-2 +- cartopy (πŸ₯ˆ36 Β· ⭐ 1.4K Β· πŸ“ˆ) - Cartopy - a cartographic python library with matplotlib support. BSD-3 +- SpeechRecognition (πŸ₯‡35 Β· ⭐ 8.4K Β· πŸ“ˆ) - Speech recognition module for Python, supporting.. BSD-3 +- causalml (πŸ₯ˆ31 Β· ⭐ 5.1K Β· πŸ“ˆ) - Uplift modeling and causal inference with machine learning.. Apache-2 +- LIT (πŸ₯ˆ28 Β· ⭐ 3.5K Β· πŸ“ˆ) - The Learning Interpretability Tool: Interactively analyze ML models.. Apache-2 +- pycm (πŸ₯ˆ28 Β· ⭐ 1.4K Β· πŸ“ˆ) - Multi-class confusion matrix library in Python. MIT +- tinytag (πŸ₯‰28 Β· ⭐ 700 Β· πŸ“ˆ) - Python library for reading audio file metadata. MIT +- Chartify (πŸ₯‰27 Β· ⭐ 3.5K Β· πŸ“ˆ) - Python library that makes it easy for data scientists to create.. Apache-2 +- Pytorch Toolbelt (πŸ₯‰24 Β· ⭐ 1.5K Β· πŸ“ˆ) - PyTorch extensions for fast R&D prototyping and.. MIT + +## 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._ + +- PyTorch (πŸ₯‡55 Β· ⭐ 83K Β· πŸ“‰) - Tensors and Dynamic neural networks in Python with strong GPU.. BSD-3 +- PaddleOCR (πŸ₯‡40 Β· ⭐ 44K Β· πŸ“‰) - Awesome multilingual OCR toolkits based on PaddlePaddle.. Apache-2 +- gensim (πŸ₯‡39 Β· ⭐ 16K Β· πŸ“‰) - Topic Modelling for Humans. ❗️LGPL-2.1 +- flair (πŸ₯‡38 Β· ⭐ 14K Β· πŸ“‰) - A very simple framework for state-of-the-art Natural Language.. MIT +- dgl (πŸ₯‡38 Β· ⭐ 13K Β· πŸ“‰) - Python package built to ease deep learning on graph, on top of.. Apache-2 +- EasyOCR (πŸ₯‡35 Β· ⭐ 24K Β· πŸ“‰) - Ready-to-use OCR with 80+ supported languages and all popular.. Apache-2 +- spark-nlp (πŸ₯ˆ35 Β· ⭐ 3.9K Β· πŸ“‰) - State of the Art Natural Language Processing. Apache-2 +- VisPy (πŸ₯ˆ34 Β· ⭐ 3.3K Β· πŸ“‰) - High-performance interactive 2D/3D data visualization library. BSD-3 +- PML (πŸ₯‡32 Β· ⭐ 6K Β· πŸ“‰) - The easiest way to use deep metric learning in your application... MIT +- pomegranate (πŸ₯‰27 Β· ⭐ 3.4K Β· πŸ“‰) - Fast, flexible and easy to use probabilistic modelling in Python. MIT + diff --git a/history/2024-10-24_projects.csv b/history/2024-10-24_projects.csv new file mode 100644 index 0000000..054d289 --- /dev/null +++ b/history/2024-10-24_projects.csv @@ -0,0 +1,920 @@ +,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,dockerhub_id,docs_url,labels,dependent_project_count,github_dependent_project_count,pypi_url,pypi_latest_release_published_at,pypi_dependent_project_count,pypi_monthly_downloads,monthly_downloads,conda_url,conda_latest_release_published_at,conda_total_downloads,dockerhub_url,dockerhub_latest_release_published_at,dockerhub_stars,dockerhub_pulls,projectrank_placing,github_release_downloads,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,maven_id,maven_url,maven_latest_release_published_at,maven_dependent_project_count,dnf_id,yay_id,snap_id +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 06:22:28,1567.0,3.0,739.0,118.0,340.0,71.0,145.0,4924.0,Benchmarks of approximate nearest neighbor libraries in Python.,107.0,0,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,,169.0,58.0,205.0,,3.0,2310.0,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 02:31:07,360.0,1.0,257.0,93.0,199.0,7.0,6.0,3666.0,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 02:31:07,360.0,1.0,257.0,93.0,199.0,7.0,6.0,3666.0,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 02:31:07,360.0,1.0,257.0,93.0,199.0,7.0,6.0,3666.0,"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 02:31:07,360.0,1.0,257.0,93.0,199.0,7.0,6.0,3666.0,"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,Tensorflow,tensorflow/tensorflow,ml-frameworks,,https://github.com/tensorflow/tensorflow,https://github.com/tensorflow/tensorflow,Apache-2.0,2015-11-07 01:19:20.000,2024-10-24 14:17:12.000000,2024-10-24 14:17:02,171353.0,3810.0,74277.0,7589.0,38111.0,5512.0,38439.0,188783.0,An Open Source Machine Learning Framework for Everyone.,4699.0,55,True,2024-07-11 16:45:52.000,2.17.0,200.0,tensorflow,conda-forge/tensorflow,tensorflow/tensorflow,https://www.tensorflow.org/overview,['tensorflow'],429074.0,421070.0,https://pypi.org/project/tensorflow,2024-10-16 18:29:33.000,8004.0,18707254.0,19538216.0,https://anaconda.org/conda-forge/tensorflow,2024-10-17 06:34:48.464,5033566.0,https://hub.docker.com/r/tensorflow/tensorflow,2024-10-24 12:51:22.898468,2587.0,78352366.0,1.0,,,,,,,,,,,,,,,,,,,, +7,PyTorch,pytorch/pytorch,ml-frameworks,,https://github.com/pytorch/pytorch,https://github.com/pytorch/pytorch,BSD-3-Clause,2016-08-13 05:26:41.000,2024-10-24 14:15:51.000000,2024-10-24 12:39:31,79944.0,3746.0,22412.0,1739.0,92590.0,15161.0,31775.0,83280.0,Tensors and Dynamic neural networks in Python with strong GPU acceleration.,5197.0,55,True,2024-10-17 16:26:53.000,2.5.0,56.0,torch,pytorch/pytorch,,https://pytorch.org/docs/stable/index.html,['pytorch'],570667.0,551245.0,https://pypi.org/project/torch,2024-10-17 14:44:26.000,19422.0,34897258.0,35550172.0,https://anaconda.org/pytorch/pytorch,2024-10-16 16:20:15.870,24134171.0,,,,,1.0,62137.0,-1.0,,,,,,,,,,,,,,,,,, +8,transformers,huggingface/transformers,nlp,,https://github.com/huggingface/transformers,https://github.com/huggingface/transformers,Apache-2.0,2018-10-29 13:56:00.000,2024-10-24 14:19:45.000000,2024-10-24 13:22:50,17239.0,784.0,26783.0,1122.0,17896.0,1448.0,14971.0,133898.0,"Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.",2897.0,52,True,2024-10-24 08:15:48.000,4.46.0,161.0,transformers,conda-forge/transformers,,,"['pytorch', 'tensorflow']",237640.0,231125.0,https://pypi.org/project/transformers,2024-10-24 08:15:07.000,6515.0,45099705.0,45141777.0,https://anaconda.org/conda-forge/transformers,2024-10-24 11:52:28.443,2145712.0,,,,,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 09:43:38.000,2024-10-24 13:56:58.000000,2024-10-24 13:56:58,31839.0,280.0,25351.0,2141.0,17913.0,2073.0,9651.0,59867.0,scikit-learn: machine learning in Python.,3203.0,52,True,2024-09-11 15:52:05.000,1.5.2,81.0,scikit-learn,conda-forge/scikit-learn,,,['sklearn'],950361.0,925676.0,https://pypi.org/project/scikit-learn,2024-09-11 15:49:19.000,24685.0,82019037.0,82616841.0,https://anaconda.org/conda-forge/scikit-learn,2024-09-11 20:00:28.266,31683101.0,,,,,1.0,1028.0,,,,,,,,,,,,,,,,,,, +10,scipy,scipy/scipy,others,,https://github.com/scipy/scipy,https://github.com/scipy/scipy,BSD-3-Clause,2011-03-09 18:52:03.000,2024-10-24 00:39:38.000000,2024-10-24 00:39:38,33648.0,570.0,5160.0,348.0,11378.0,1745.0,8882.0,13016.0,"Ecosystem of open-source software for mathematics, science, and engineering.",1698.0,50,True,2024-08-21 00:10:50.000,1.14.1,108.0,scipy,conda-forge/scipy,,,,1169778.0,1123902.0,https://pypi.org/project/scipy,2024-08-21 00:03:32.000,45876.0,138310150.0,139454226.0,https://anaconda.org/conda-forge/scipy,2024-10-21 07:19:53.878,53593571.0,,,,,1.0,420491.0,,,,,,,,,,,,,,,,,,, +11,SymPy,sympy/sympy,others,,https://github.com/sympy/sympy,https://github.com/sympy/sympy,BSD-3-Clause,2010-04-30 20:37:14.000,2024-10-24 12:06:47.000000,2024-10-24 12:06:47,59060.0,618.0,4410.0,291.0,13462.0,5137.0,8884.0,12934.0,A computer algebra system written in pure Python.,1333.0,49,True,2024-09-18 21:54:45.000,1.13.3,64.0,sympy,conda-forge/sympy,,,,184839.0,181339.0,https://pypi.org/project/sympy,2024-09-18 21:54:23.000,3500.0,31433120.0,31567221.0,https://anaconda.org/conda-forge/sympy,2024-10-09 14:38:28.134,6891599.0,,,,,1.0,549606.0,,,,,,,,,,,,,,,,,,, +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 00:35:42.000,2024-10-24 05:06:22.000000,2024-10-24 05:06:22,11073.0,225.0,19446.0,1910.0,7505.0,260.0,11936.0,61928.0,Deep Learning for humans.,1339.0,48,True,2024-10-03 19:44:54.000,3.6.0,103.0,keras,conda-forge/keras,,https://keras.io,['tensorflow'],1582.0,,https://pypi.org/project/keras,2024-10-03 19:44:54.000,1582.0,14023504.0,14095760.0,https://anaconda.org/conda-forge/keras,2024-10-07 20:46:42.672,3757346.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +13,Matplotlib,matplotlib/matplotlib,data-viz,,https://github.com/matplotlib/matplotlib,https://github.com/matplotlib/matplotlib,,2011-02-19 03:17:12.000,2024-10-24 07:31:47.000000,2024-10-24 05:02:26,51225.0,431.0,7601.0,592.0,18458.0,1590.0,9326.0,20181.0,matplotlib: plotting with Python.,1737.0,48,True,2024-08-13 01:44:21.000,3.9.2,127.0,matplotlib,conda-forge/matplotlib,,,,1432938.0,1383198.0,https://pypi.org/project/matplotlib,2024-08-13 01:44:21.000,49740.0,82342765.0,82851332.0,https://anaconda.org/conda-forge/matplotlib,2024-09-12 20:10:05.995,26445513.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +14,Pillow,python-pillow/Pillow,image,,https://github.com/python-pillow/Pillow,https://github.com/python-pillow/Pillow,PIL,2012-07-24 21:38:39.000,2024-10-23 04:30:40.000000,2024-10-23 04:30:34,18740.0,505.0,2218.0,219.0,5133.0,111.0,3095.0,12211.0,Python Imaging Library (Fork).,479.0,48,True,2024-10-15 14:29:17.000,11.0.0,99.0,Pillow,conda-forge/pillow,,,,1887410.0,1878515.0,https://pypi.org/project/Pillow,2024-10-15 14:21:49.000,8895.0,129905232.0,130797031.0,https://anaconda.org/conda-forge/pillow,2024-10-18 22:08:55.292,45481767.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +15,Streamlit,streamlit/streamlit,others,,https://github.com/streamlit/streamlit,https://github.com/streamlit/streamlit,Apache-2.0,2019-08-24 00:14:52.000,2024-10-24 07:59:51.000000,2024-10-24 07:59:51,6732.0,239.0,3064.0,320.0,5009.0,999.0,3656.0,35302.0,Streamlit A faster way to build and share data apps.,243.0,46,True,2024-10-01 17:36:45.000,1.39.0,228.0,streamlit,,,,,558951.0,556204.0,https://pypi.org/project/streamlit,2024-10-01 17:36:39.000,2747.0,7296709.0,7296709.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,, +16,XGBoost,dmlc/xgboost,ml-frameworks,,https://github.com/dmlc/xgboost,https://github.com/dmlc/xgboost,Apache-2.0,2014-02-06 17:28:03.000,2024-10-24 13:16:56.000000,2024-10-24 13:16:56,7146.0,143.0,8716.0,908.0,5611.0,461.0,4906.0,26221.0,"Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and..",652.0,46,True,2024-10-23 14:31:13.000,2.1.2,84.0,xgboost,conda-forge/xgboost,,https://xgboost.readthedocs.io/en/latest/,,114789.0,112743.0,https://pypi.org/project/xgboost,2024-10-23 14:19:26.000,2046.0,29173158.0,29278396.0,https://anaconda.org/conda-forge/xgboost,2024-09-29 19:48:48.053,5362629.0,,,,,1.0,11349.0,,,,,,,,,,,,,,,,,,, +17,PySpark,apache/spark,ml-frameworks,,https://github.com/apache/spark,https://github.com/apache/spark,Apache-2.0,2014-02-25 08:00:08.000,2024-10-24 13:09:30.000000,2024-10-24 13:09:25,42577.0,890.0,28255.0,2019.0,48605.0,233.0,,39551.0,Apache Spark Python API.,3133.0,45,True,2024-09-24 00:28:04.000,3.5.3,48.0,pyspark,conda-forge/pyspark,,,['spark'],1545.0,,https://pypi.org/project/pyspark,2024-09-27 14:56:40.000,1545.0,30637675.0,30704624.0,https://anaconda.org/conda-forge/pyspark,2024-03-03 13:07:40.821,3481354.0,,,,,1.0,,,stable/spark,,,,,,,,,,,,,,,,, +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 19:38:30.000,2024-10-24 06:38:57.000000,2024-10-24 06:38:56,22837.0,591.0,5696.0,473.0,29285.0,4201.0,15044.0,33559.0,Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML..,1084.0,45,True,2024-10-23 21:57:05.000,ray-2.38.0,118.0,ray,conda-forge/ray-tune,,,,19300.0,18512.0,https://pypi.org/project/ray,2024-10-23 19:27:39.000,788.0,6174350.0,6183836.0,https://anaconda.org/conda-forge/ray-tune,2024-10-23 01:52:29.788,436296.0,,,,,1.0,240.0,,,,,,,,,,,,,,,,,,, +19,jax,google/jax,ml-frameworks,,https://github.com/jax-ml/jax,https://github.com/jax-ml/jax,Apache-2.0,2018-10-25 21:25:02.000,2024-10-24 14:13:35.000000,2024-10-24 13:56:32,23750.0,1620.0,2776.0,338.0,15974.0,1409.0,4242.0,30316.0,"Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more.",771.0,45,True,2024-10-22 21:01:49.000,jax-v0.4.35,169.0,jax,conda-forge/jaxlib,,,,33517.0,31610.0,https://pypi.org/project/jax,2024-10-22 20:56:34.000,1907.0,4073441.0,4107715.0,https://anaconda.org/conda-forge/jaxlib,2024-10-24 10:52:07.546,1782257.0,,,,,1.0,,,,jax-ml/jax,,,,,,,,,,,,,,,, +20,spaCy,explosion/spaCy,nlp,,https://github.com/explosion/spaCy,https://github.com/explosion/spaCy,MIT,2014-07-03 15:15:40.000,2024-10-23 10:43:24.000000,2024-10-23 10:42:54,16212.0,78.0,4383.0,561.0,4026.0,150.0,5521.0,29931.0,Industrial-strength Natural Language Processing (NLP) in Python.,762.0,45,True,2024-10-01 18:20:24.000,3.8.2,237.0,spacy,conda-forge/spacy,,,,105171.0,102482.0,https://pypi.org/project/spacy,2024-10-01 18:20:24.000,2689.0,14211845.0,14295392.0,https://anaconda.org/conda-forge/spacy,2024-09-22 12:43:59.353,4344312.0,,,,,1.0,289.0,,,,,,,,,,,,,,,,,,, +21,PaddlePaddle,PaddlePaddle/Paddle,ml-frameworks,,https://github.com/PaddlePaddle/Paddle,https://github.com/PaddlePaddle/Paddle,Apache-2.0,2016-08-15 06:59:08.000,2024-10-24 09:58:40.000000,2024-10-24 09:58:40,51358.0,1535.0,5554.0,717.0,50334.0,1710.0,17410.0,22189.0,PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice &.,1291.0,45,True,2024-09-13 08:31:46.000,2.6.2,70.0,paddlepaddle,,,,['paddle'],6319.0,6141.0,https://pypi.org/project/paddlepaddle,2024-09-13 08:31:46.000,178.0,330138.0,330295.0,,,,,,,,1.0,15407.0,,,,,,,,,,,,,,,,,,, +22,Bokeh,bokeh/bokeh,data-viz,,https://github.com/bokeh/bokeh,https://github.com/bokeh/bokeh,BSD-3-Clause,2012-03-26 15:40:01.000,2024-10-24 08:54:19.000000,2024-10-22 17:15:27,20624.0,65.0,4178.0,442.0,6189.0,760.0,6985.0,19309.0,"Interactive Data Visualization in the browser, from Python.",702.0,45,True,2024-09-26 16:27:00.000,3.6.0,218.0,bokeh,conda-forge/bokeh,,,,95514.0,93770.0,https://pypi.org/project/bokeh,2024-09-26 16:55:03.000,1744.0,4354723.0,4646519.0,https://anaconda.org/conda-forge/bokeh,2024-10-14 19:05:13.977,15173396.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +23,Plotly,plotly/plotly.py,data-viz,,https://github.com/plotly/plotly.py,https://github.com/plotly/plotly.py,MIT,2013-11-21 05:53:08.000,2024-10-23 21:38:20.000000,2024-10-22 17:08:54,6880.0,266.0,2533.0,275.0,1725.0,527.0,2448.0,16168.0,The interactive graphing library for Python This project now includes Plotly Express!.,277.0,45,True,2024-09-12 15:42:27.000,5.24.1,301.0,plotly,conda-forge/plotly,,,,322442.0,316113.0,https://pypi.org/project/plotly,2024-09-12 15:36:24.000,6320.0,20516515.0,20659715.0,https://anaconda.org/conda-forge/plotly,2024-09-12 22:24:43.567,7268722.0,,,,,1.0,,,,,plotlywidget,https://www.npmjs.com/package/plotlywidget,2021-01-12 16:09:46.133,9.0,6055.0,,,,,,,,,,, +24,nltk,nltk/nltk,nlp,,https://github.com/nltk/nltk,https://github.com/nltk/nltk,Apache-2.0,2009-09-07 10:53:58.000,2024-09-25 08:35:09.000000,2024-09-25 08:35:04,14681.0,74.0,2878.0,462.0,1494.0,277.0,1558.0,13547.0,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,,,,319825.0,315128.0,https://pypi.org/project/nltk,2024-08-18 19:48:21.000,4697.0,22953483.0,23019232.0,https://anaconda.org/conda-forge/nltk,2024-08-18 23:14:52.073,2827238.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +25,StatsModels,statsmodels/statsmodels,ml-frameworks,,https://github.com/statsmodels/statsmodels,https://github.com/statsmodels/statsmodels,BSD-3-Clause,2011-06-12 17:04:50.000,2024-10-24 10:32:53.000000,2024-10-24 10:32:52,15559.0,98.0,2875.0,282.0,3949.0,2833.0,2796.0,10087.0,Statsmodels: statistical modeling and econometrics in Python.,446.0,45,True,2024-10-03 16:13:31.000,0.14.4,39.0,statsmodels,conda-forge/statsmodels,,,,144243.0,139774.0,https://pypi.org/project/statsmodels,2024-10-03 16:13:31.000,4469.0,16934558.0,17230657.0,https://anaconda.org/conda-forge/statsmodels,2024-10-03 20:40:26.151,15397156.0,,,,,1.0,35.0,,,,,,,,,,,,,,,,,,, +26,Gradio,gradio-app/gradio,others,,https://github.com/gradio-app/gradio,https://github.com/gradio-app/gradio,Apache-2.0,2018-12-19 08:24:04.000,2024-10-24 14:11:28.000000,2024-10-24 14:03:10,7162.0,307.0,2516.0,175.0,4537.0,522.0,4457.0,33431.0,"Wrap UIs around any model, share with anyone.",437.0,44,True,2024-10-22 02:47:32.000,5.3.0,603.0,gradio,,,,,45126.0,44310.0,https://pypi.org/project/gradio,2024-10-22 02:47:32.000,816.0,6717011.0,6717011.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,, +27,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 00:45:57.000,2024-10-21 15:15:33.000000,2024-10-21 15:15:31,10434.0,48.0,3374.0,250.0,10289.0,799.0,6306.0,28244.0,"Pretrain, finetune ANY AI model of ANY size on multiple GPUs, TPUs with zero code changes.",975.0,44,True,2024-08-07 09:46:38.000,2.4.0,277.0,pytorch-lightning,conda-forge/pytorch-lightning,,,['pytorch'],39190.0,37747.0,https://pypi.org/project/pytorch-lightning,2024-08-07 09:46:38.000,1443.0,6926958.0,6952485.0,https://anaconda.org/conda-forge/pytorch-lightning,2024-08-07 15:45:27.965,1315392.0,,,,,2.0,9274.0,,,Lightning-AI/pytorch-lightning,,,,,,,,,,,,,,,, +28,mlflow,mlflow/mlflow,ml-experiments,,https://github.com/mlflow/mlflow,https://github.com/mlflow/mlflow,Apache-2.0,2018-06-05 16:05:58.000,2024-10-24 11:34:14.000000,2024-10-24 11:34:14,6640.0,351.0,4208.0,301.0,9313.0,1644.0,2598.0,18579.0,Open source platform for the machine learning lifecycle.,780.0,44,True,2024-10-14 15:08:06.000,2.17.0,115.0,mlflow,conda-forge/mlflow,,,,45502.0,44619.0,https://pypi.org/project/mlflow,2024-10-12 01:37:13.000,883.0,16263001.0,16309272.0,https://anaconda.org/conda-forge/mlflow,2024-10-16 17:14:22.919,2406128.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +29,networkx,networkx/networkx,graph,,https://github.com/networkx/networkx,https://github.com/networkx/networkx,BSD-3-Clause,2010-09-06 00:53:44.000,2024-10-23 17:54:23.000000,2024-10-23 17:54:23,7818.0,67.0,3235.0,278.0,3908.0,343.0,3033.0,14869.0,Network Analysis in Python.,753.0,44,True,2024-10-21 12:40:41.000,networkx-3.4.2,98.0,networkx,conda-forge/networkx,,,,315763.0,306133.0,https://pypi.org/project/networkx,2024-10-21 12:39:36.000,9630.0,81093552.0,81457843.0,https://anaconda.org/conda-forge/networkx,2024-10-21 17:15:32.856,18214556.0,,,,,1.0,76.0,,,,,,,,,,,,,,,,,,, +30,dask,dask/dask,distributed-ml,,https://github.com/dask/dask,https://github.com/dask/dask,BSD-3-Clause,2015-01-04 18:50:00.000,2024-10-24 10:35:00.000000,2024-10-24 10:35:00,8342.0,95.0,1702.0,212.0,5984.0,1107.0,4278.0,12527.0,Parallel computing with task scheduling.,612.0,44,True,2024-10-17 09:20:07.000,2024.10.0,209.0,dask,conda-forge/dask,,,,68298.0,65862.0,https://pypi.org/project/dask,2024-10-17 09:13:37.000,2436.0,13078395.0,13306609.0,https://anaconda.org/conda-forge/dask,2024-10-18 13:49:42.706,12095389.0,,,,,1.0,,,stable/dask,,,,,,,,,,,,,,,,, +31,shap,slundberg/shap,interpretability,,https://github.com/shap/shap,https://github.com/shap/shap,MIT,2016-11-22 19:17:08.000,2024-10-21 22:22:20.000000,2024-10-15 08:44:34,2771.0,53.0,3262.0,243.0,974.0,744.0,1798.0,22732.0,A game theoretic approach to explain the output of any machine learning model.,251.0,43,True,2024-06-27 10:16:34.000,0.46.0,104.0,shap,conda-forge/shap,,,,21907.0,21159.0,https://pypi.org/project/shap,2024-06-27 10:16:34.000,748.0,6792141.0,6881703.0,https://anaconda.org/conda-forge/shap,2024-05-08 21:55:59.406,4119863.0,,,,,1.0,,,,shap/shap,,,,,,,,,,,,,,,, +32,dash,plotly/dash,data-viz,,https://github.com/plotly/dash,https://github.com/plotly/dash,MIT,2015-04-10 01:53:08.000,2024-10-23 19:41:39.000000,2024-10-23 19:41:35,7723.0,138.0,2057.0,423.0,1142.0,483.0,1358.0,21369.0,Data Apps & Dashboards for Python. No JavaScript Required.,167.0,43,True,2024-09-12 16:11:13.000,2.18.1,181.0,dash,conda-forge/dash,,,,72015.0,70732.0,https://pypi.org/project/dash,2024-09-12 16:08:23.000,1283.0,3561150.0,3590449.0,https://anaconda.org/conda-forge/dash,2024-09-14 04:47:51.793,1523545.0,,,,,1.0,85.0,,,,,,,,,,,,,,,,,,, +33,onnx,onnx/onnx,model-serialisation,,https://github.com/onnx/onnx,https://github.com/onnx/onnx,Apache-2.0,2017-09-07 04:53:45.000,2024-10-23 19:41:12.000000,2024-10-23 17:10:35,2880.0,105.0,3669.0,438.0,3422.0,345.0,2527.0,17819.0,Open standard for machine learning interoperability.,325.0,43,True,2024-10-01 21:45:45.000,1.17.0,35.0,onnx,conda-forge/onnx,,,,35910.0,34857.0,https://pypi.org/project/onnx,2024-10-01 21:45:45.000,1053.0,6023663.0,6048698.0,https://anaconda.org/conda-forge/onnx,2024-10-21 21:30:32.889,1288194.0,,,,,1.0,22099.0,,,,,,,,,,,,,,,,,,, +34,LightGBM,microsoft/LightGBM,ml-frameworks,,https://github.com/microsoft/LightGBM,https://github.com/microsoft/LightGBM,MIT,2016-08-05 05:45:50.000,2024-10-23 12:35:47.000000,2024-10-21 19:25:22,3587.0,50.0,3828.0,433.0,3275.0,371.0,3070.0,16638.0,"A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision..",319.0,43,True,2024-07-26 14:38:57.000,4.5.0,38.0,lightgbm,conda-forge/lightgbm,,,,39954.0,38877.0,https://pypi.org/project/lightgbm,2024-07-26 14:38:57.000,1077.0,9588023.0,9647379.0,https://anaconda.org/conda-forge/lightgbm,2024-10-10 08:17:38.424,2778969.0,,,,,2.0,237949.0,,,,,,,,,,,,,,,,,,, +35,triton,openai/triton,model-serialisation,,https://github.com/triton-lang/triton,https://github.com/triton-lang/triton,MIT,2014-08-30 17:07:16.000,2024-10-24 13:55:04.000000,2024-10-24 13:55:04,2828.0,321.0,1596.0,193.0,3383.0,662.0,797.0,13157.0,Development repository for the Triton language and compiler.,335.0,43,True,2024-10-14 16:05:32.000,3.1.0,196.0,triton,,,,,40725.0,40460.0,https://pypi.org/project/triton,2024-10-14 16:05:32.000,265.0,15120538.0,15120538.0,,,,,,,,1.0,,,,triton-lang/triton,,,,,,,,,,,,,,,, +36,pydeck,visgl/deck.gl,geospatial-data,,https://github.com/visgl/deck.gl,https://github.com/visgl/deck.gl,MIT,2015-12-15 08:38:29.000,2024-10-24 14:58:38.000000,2024-10-21 11:44:19,5007.0,60.0,2083.0,1671.0,4872.0,343.0,2728.0,12200.0,WebGL2 powered visualization framework.,273.0,43,True,2024-10-24 14:59:06.000,9.0.34,673.0,pydeck,conda-forge/pydeck,,,['jupyter'],8621.0,8202.0,https://pypi.org/project/pydeck,2024-05-10 15:36:17.000,120.0,5678182.0,6295138.0,https://anaconda.org/conda-forge/pydeck,2023-06-16 19:17:51.392,628974.0,,,,,1.0,,,,,deck.gl,https://www.npmjs.com/package/deck.gl,2024-10-08 18:05:20.283,299.0,605725.0,,,,,,,,,,, +37,Optuna,optuna/optuna,hyperopt,,https://github.com/optuna/optuna,https://github.com/optuna/optuna,MIT,2018-02-21 06:12:56.000,2024-10-24 05:29:52.000000,2024-10-24 05:29:52,18327.0,235.0,1021.0,117.0,3674.0,72.0,1612.0,10756.0,A hyperparameter optimization framework.,273.0,43,True,2024-09-02 05:17:47.000,4.0.0,66.0,optuna,conda-forge/optuna,,,,19450.0,18452.0,https://pypi.org/project/optuna,2024-09-02 05:17:47.000,998.0,3690735.0,3724714.0,https://anaconda.org/conda-forge/optuna,2024-09-03 06:05:16.374,1766915.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +38,scikit-image,scikit-image/scikit-image,image,,https://github.com/scikit-image/scikit-image,https://github.com/scikit-image/scikit-image,,2011-07-07 22:07:20.000,2024-10-23 16:25:54.000000,2024-10-23 16:25:54,14176.0,133.0,2224.0,186.0,4520.0,809.0,2111.0,6069.0,Image processing in Python.,673.0,43,False,2024-06-18 19:05:37.000,0.24.0,69.0,scikit-image,conda-forge/scikit-image,,,,206471.0,200169.0,https://pypi.org/project/scikit-image,2024-10-07 07:58:05.000,6302.0,26207115.0,26342344.0,https://anaconda.org/conda-forge/scikit-image,2024-08-17 02:34:14.270,7031944.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +39,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 05:51:12.000,2024-10-24 04:51:09.000000,2024-10-24 04:51:09,2519.0,131.0,4733.0,312.0,523.0,47.0,873.0,31971.0,"The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and..",151.0,42,True,2024-10-16 21:19:16.000,1.0.11,62.0,timm,conda-forge/timm,,,['pytorch'],39685.0,38731.0,https://pypi.org/project/timm,2024-10-16 21:17:47.000,954.0,5950487.0,6065148.0,https://anaconda.org/conda-forge/timm,2024-10-17 16:34:27.541,251587.0,,,,,1.0,7132381.0,,,huggingface/pytorch-image-models,,,,,,,,,,,,,,,, +40,torchvision,pytorch/vision,image,,https://github.com/pytorch/vision,https://github.com/pytorch/vision,BSD-3-Clause,2016-11-09 23:11:43.000,2024-10-24 11:34:56.000000,2024-10-23 10:36:26,3950.0,52.0,6941.0,433.0,5419.0,1020.0,2451.0,16141.0,"Datasets, Transforms and Models specific to Computer Vision.",612.0,42,True,2024-10-17 16:22:28.000,0.20.0,48.0,torchvision,conda-forge/torchvision,,,['pytorch'],5775.0,21.0,https://pypi.org/project/torchvision,2024-10-17 14:48:44.000,5754.0,14485011.0,14525229.0,https://anaconda.org/conda-forge/torchvision,2024-10-14 15:39:27.942,1710789.0,,,,,1.0,38999.0,,,,,,,,,,,,,,,,,,, +41,DVC,iterative/dvc,ml-experiments,,https://github.com/iterative/dvc,https://github.com/iterative/dvc,Apache-2.0,2017-03-04 08:16:33.000,2024-10-24 02:18:57.000000,2024-10-24 02:18:55,9350.0,54.0,1180.0,138.0,5529.0,234.0,4478.0,13803.0,Data Versioning and ML Experiments.,306.0,42,True,2024-10-23 02:16:24.000,3.56.0,539.0,dvc,conda-forge/dvc,,,,18680.0,18547.0,https://pypi.org/project/dvc,2024-10-23 02:16:24.000,133.0,693020.0,737303.0,https://anaconda.org/conda-forge/dvc,2024-10-23 06:04:08.856,2302718.0,,,,,1.0,,,,,,,,,,dvc,dvc,dvc,,,,,,,, +42,litellm,BerriAI/litellm,nlp,,https://github.com/BerriAI/litellm,https://github.com/BerriAI/litellm,MIT,2023-07-27 00:09:52.000,2024-10-24 12:41:09.000000,2024-10-24 12:41:09,18148.0,2863.0,1529.0,73.0,2853.0,687.0,2831.0,13204.0,"Python SDK, Proxy Server (LLM Gateway) to call 100+ LLM APIs in OpenAI format - [Bedrock, Azure, OpenAI, VertexAI,..",347.0,42,True,2024-10-23 12:43:51.000,1.50.1.de1,988.0,litellm,,,,others,4480.0,4014.0,https://pypi.org/project/litellm,2024-10-22 23:10:00.000,466.0,2998522.0,2998892.0,,,,,,,,1.0,370.0,,,,,,,,,,,,,,,,,,, +43,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,,1904.0,263.0,1123.0,176.0,2414.0,12505.0,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,,,,501777.0,490934.0,https://pypi.org/project/seaborn,2024-01-25 13:21:49.000,10843.0,19333875.0,19535919.0,https://anaconda.org/conda-forge/seaborn,2024-04-30 16:33:12.611,10506178.0,,,,,1.0,446.0,,,,,,,,,,,,,,,,,,, +44,Altair,altair-viz/altair,data-viz,,https://github.com/vega/altair,https://github.com/vega/altair,BSD-3-Clause,2015-09-19 03:14:04.000,2024-10-24 14:14:41.000000,2024-10-23 19:47:36,3795.0,83.0,793.0,140.0,1501.0,200.0,1822.0,9300.0,Declarative statistical visualization library for Python.,172.0,42,True,2024-08-27 04:41:23.000,5.4.1,42.0,altair,conda-forge/altair,,,,170895.0,170021.0,https://pypi.org/project/altair,2024-08-27 04:31:06.000,874.0,22920638.0,22993226.0,https://anaconda.org/conda-forge/altair,2024-10-02 18:03:41.017,2467944.0,,,,,1.0,195.0,,,vega/altair,,,,,,,,,,,,,,,, +45,wandb client,wandb/client,ml-experiments,,https://github.com/wandb/wandb,https://github.com/wandb/wandb,MIT,2017-03-24 05:46:23.000,2024-10-24 05:17:55.000000,2024-10-24 05:17:53,7187.0,454.0,671.0,60.0,5341.0,873.0,2482.0,9053.0,"The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation..",194.0,42,True,2024-10-17 22:45:42.000,0.18.5,291.0,wandb,conda-forge/wandb,,,,57777.0,56330.0,https://pypi.org/project/wandb,2024-10-17 22:09:55.000,1447.0,21486197.0,21499705.0,https://anaconda.org/conda-forge/wandb,2024-10-23 22:43:47.058,688595.0,,,,,1.0,346.0,,,wandb/wandb,,,,,,,,,,,,,,,, +46,Catboost,catboost/catboost,ml-frameworks,,https://github.com/catboost/catboost,https://github.com/catboost/catboost,Apache-2.0,2017-07-18 05:29:04.000,2024-10-24 12:18:41.000000,2024-10-24 12:06:01,48719.0,391.0,1176.0,191.0,398.0,553.0,1783.0,8065.0,"A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification,..",1280.0,42,True,2024-09-07 20:11:05.000,1.2.7,113.0,catboost,conda-forge/catboost,,,,550.0,15.0,https://pypi.org/project/catboost,2024-09-07 16:51:57.000,535.0,3408149.0,3448927.0,https://anaconda.org/conda-forge/catboost,2024-09-07 21:05:39.027,1741342.0,,,,,2.0,317043.0,,,,,,,,,,,,,,,,,,, +47,Tensorboard,tensorflow/tensorboard,ml-experiments,,https://github.com/tensorflow/tensorboard,https://github.com/tensorflow/tensorboard,Apache-2.0,2017-05-15 20:08:07.000,2024-10-18 17:32:05.000000,2024-10-18 17:32:05,5869.0,25.0,1655.0,189.0,5046.0,682.0,1240.0,6700.0,TensorFlows Visualization Toolkit.,321.0,42,True,2024-09-25 21:21:50.000,2.18.0,63.0,tensorboard,conda-forge/tensorboard,,,['tensorflow'],269410.0,267184.0,https://pypi.org/project/tensorboard,2024-09-25 21:21:50.000,2226.0,22375150.0,22472923.0,https://anaconda.org/conda-forge/tensorboard,2024-09-27 11:17:28.293,5084213.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +48,DeepSpeed,microsoft/DeepSpeed,distributed-ml,,https://github.com/microsoft/DeepSpeed,https://github.com/microsoft/DeepSpeed,Apache-2.0,2020-01-23 18:35:18.000,2024-10-24 11:10:51.000000,2024-10-23 20:29:30,2530.0,141.0,4071.0,343.0,2997.0,1099.0,1799.0,35202.0,"DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and..",347.0,41,True,2024-10-22 21:15:07.000,0.15.3,97.0,deepspeed,,deepspeed/deepspeed,,['pytorch'],9471.0,9259.0,https://pypi.org/project/deepspeed,2024-10-22 21:15:07.000,212.0,510019.0,510358.0,,,,https://hub.docker.com/r/deepspeed/deepspeed,2022-09-02 00:25:31.275782,4.0,19379.0,1.0,,,,,,,,,,,,,,,,,,,, +49,OpenAI Gym,openai/gym,reinforcement-learning,,https://github.com/openai/gym,https://github.com/openai/gym,MIT,2016-04-27 14:59:16.000,2024-10-11 20:07:05.000000,2023-01-30 18:15:21,1757.0,,8602.0,1060.0,1456.0,114.0,1723.0,34679.0,A toolkit for developing and comparing reinforcement learning algorithms.,383.0,41,False,2023-07-20 15:30:49.667,0.0.1,108.0,gym,conda-forge/gym,,,,59572.0,58024.0,https://pypi.org/project/gym,2023-07-20 15:30:49.667,1548.0,13149003.0,13155036.0,https://anaconda.org/conda-forge/gym,2023-06-16 19:18:41.854,325787.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +50,Faiss,facebookresearch/faiss,nn-search,,https://github.com/facebookresearch/faiss,https://github.com/facebookresearch/faiss,MIT,2017-02-07 16:07:05.000,2024-10-24 12:46:08.000000,2024-10-24 12:42:41,1292.0,134.0,3600.0,480.0,1238.0,247.0,2292.0,31081.0,A library for efficient similarity search and clustering of dense vectors.,193.0,41,True,2024-10-12 10:48:38.000,2.4.8,102.0,pymilvus,conda-forge/faiss,,,,4256.0,4084.0,https://pypi.org/project/pymilvus,2024-10-12 10:48:38.000,172.0,1089498.0,1123489.0,https://anaconda.org/conda-forge/faiss,2024-08-09 18:17:48.122,1767579.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +51,Milvus,milvus-io/milvus,nn-search,,https://github.com/milvus-io/milvus,https://github.com/milvus-io/milvus,Apache-2.0,2019-09-16 06:43:43.000,2024-10-24 11:52:02.970178,2024-10-24 11:23:29,21007.0,640.0,2871.0,280.0,22762.0,752.0,11276.0,30182.0,"A cloud-native vector database, storage for next generation AI applications.",291.0,41,True,2024-10-17 09:18:01.000,2.4.13-hotfix,102.0,pymilvus,,milvusdb/milvus,,,172.0,,https://pypi.org/project/pymilvus,2024-10-12 10:48:38.000,172.0,1089498.0,2190450.0,,,,https://hub.docker.com/r/milvusdb/milvus,2024-10-24 11:52:02.970178,64.0,66879819.0,1.0,273774.0,,,,,,,,,,,,,,,,,,, +52,Fastai,fastai/fastai,ml-frameworks,,https://github.com/fastai/fastai,https://github.com/fastai/fastai,Apache-2.0,2017-09-09 17:43:36.000,2024-10-19 04:07:45.000000,2024-10-19 04:07:43,2799.0,21.0,7554.0,604.0,2235.0,229.0,1593.0,26224.0,The fastai deep learning library.,670.0,41,True,2024-10-19 03:20:25.000,2.7.18,152.0,fastai,,,,['pytorch'],19405.0,19097.0,https://pypi.org/project/fastai,2024-10-19 03:20:25.000,308.0,457071.0,457071.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +53,sentence-transformers,UKPLab/sentence-transformers,nlp,,https://github.com/UKPLab/sentence-transformers,https://github.com/UKPLab/sentence-transformers,Apache-2.0,2019-07-24 10:53:51.000,2024-10-21 22:42:01.150000,2024-10-21 10:58:02,1571.0,51.0,2460.0,141.0,565.0,1175.0,1023.0,15128.0,State-of-the-Art Text Embeddings.,189.0,41,True,2024-10-21 12:19:51.000,3.2.1,57.0,sentence-transformers,conda-forge/sentence-transformers,,,['pytorch'],53458.0,51725.0,https://pypi.org/project/sentence-transformers,2024-10-21 12:19:46.000,1733.0,6074370.0,6082975.0,https://anaconda.org/conda-forge/sentence-transformers,2024-10-21 22:42:01.150,421667.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +54,yfinance,ranaroussi/yfinance,financial-data,,https://github.com/ranaroussi/yfinance,https://github.com/ranaroussi/yfinance,Apache-2.0,2017-05-21 10:16:15.000,2024-10-22 17:55:03.000000,2024-10-22 17:55:03,1338.0,79.0,2355.0,246.0,612.0,178.0,1194.0,14034.0,Download market data from Yahoo! Finances API.,125.0,41,True,2024-10-21 17:39:54.000,0.2.46,118.0,yfinance,ranaroussi/yfinance,,,,49799.0,49128.0,https://pypi.org/project/yfinance,2024-10-21 17:39:54.000,671.0,2440300.0,2442768.0,https://anaconda.org/ranaroussi/yfinance,2023-06-16 19:26:44.442,96254.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +55,speechbrain,speechbrain/speechbrain,audio,,https://github.com/speechbrain/speechbrain,https://github.com/speechbrain/speechbrain,Apache-2.0,2020-04-28 17:48:45.000,2024-10-22 12:33:18.000000,2024-10-22 12:33:18,10167.0,265.0,1368.0,134.0,1276.0,136.0,1003.0,8777.0,A PyTorch-based Speech Toolkit.,245.0,41,True,2024-10-01 10:55:15.000,1.0.1,17.0,speechbrain,,,,['pytorch'],2443.0,2381.0,https://pypi.org/project/speechbrain,2024-09-02 14:25:26.000,62.0,3821736.0,3821736.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,, +56,PyMC3,pymc-devs/pymc,probabilistics,,https://github.com/pymc-devs/pymc,https://github.com/pymc-devs/pymc,Apache-2.0,2009-05-05 09:43:50.000,2024-10-24 10:19:12.000000,2024-10-24 10:19:09,10099.0,96.0,1999.0,224.0,4077.0,311.0,3066.0,8688.0,Bayesian Modeling and Probabilistic Programming in Python.,505.0,41,True,2024-10-03 09:11:52.000,5.17.0,90.0,pymc3,conda-forge/pymc3,,,,4573.0,4381.0,https://pypi.org/project/pymc3,2024-05-31 12:35:21.000,192.0,240131.0,251836.0,https://anaconda.org/conda-forge/pymc3,2024-06-02 18:14:42.309,607842.0,,,,,1.0,1955.0,,,,,,,,,,,,,,,,,,, +57,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 01:03:33.000,2024-10-23 19:19:34.000000,2024-10-23 18:26:03,3866.0,96.0,1139.0,138.0,3207.0,323.0,1204.0,2099.0,A library for training and deploying machine learning models on Amazon SageMaker.,458.0,41,True,2024-10-03 22:43:56.000,2.232.2,607.0,sagemaker,conda-forge/sagemaker-python-sdk,,,"['mxnet', 'tensorflow']",4784.0,4634.0,https://pypi.org/project/sagemaker,2024-10-03 22:43:56.000,150.0,29248245.0,29270741.0,https://anaconda.org/conda-forge/sagemaker-python-sdk,2024-07-31 06:30:51.886,1124821.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +58,PaddleOCR,PaddlePaddle/PaddleOCR,ocr,,https://github.com/PaddlePaddle/PaddleOCR,https://github.com/PaddlePaddle/PaddleOCR,Apache-2.0,2020-05-08 10:38:16.000,2024-10-24 13:50:58.000000,2024-10-24 13:49:35,6324.0,91.0,7767.0,444.0,3130.0,186.0,9172.0,43676.0,"Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages..",266.0,40,True,2024-10-22 05:57:58.000,2.9.1,48.0,paddleocr,,,,['paddle'],3615.0,3507.0,https://pypi.org/project/paddleocr,2024-10-22 05:57:58.000,108.0,386166.0,396796.0,,,,,,,,1.0,520901.0,-1.0,,,,,,,,,,,,,,,,,, +59,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 16:03:03.000,2024-10-23 23:34:11.000000,2024-10-21 03:30:12,7633.0,54.0,3639.0,252.0,3146.0,1045.0,2660.0,21223.0,Graph Neural Network Library for PyTorch.,520.0,40,True,2024-09-26 08:11:27.000,2.6.1,46.0,torch-geometric,conda-forge/pytorch_geometric,,,['pytorch'],7072.0,6717.0,https://pypi.org/project/torch-geometric,2024-09-26 08:11:27.000,355.0,387191.0,389121.0,https://anaconda.org/conda-forge/pytorch_geometric,2024-09-26 16:16:39.995,98457.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +60,Jina,jina-ai/jina,ml-frameworks,,https://github.com/jina-ai/jina,https://github.com/jina-ai/jina,Apache-2.0,2020-02-13 17:04:44.000,2024-10-01 23:03:49.000000,2024-10-01 23:03:47,8605.0,45.0,2216.0,212.0,4214.0,22.0,1937.0,21089.0,Build multimodal AI applications with cloud-native stack.,177.0,40,True,2024-10-01 09:31:10.000,3.27.17,2481.0,jina,conda-forge/jina-core,jinaai/jina,,,1801.0,1774.0,https://pypi.org/project/jina,2024-10-01 09:22:15.000,27.0,159047.0,192371.0,https://anaconda.org/conda-forge/jina-core,2023-06-16 19:27:18.682,77249.0,https://hub.docker.com/r/jinaai/jina,2024-10-01 09:40:53.390346,8.0,1749294.0,2.0,,,,,,,,,,,,,,,,,,,, +61,Albumentations,albumentations-team/albumentations,image,,https://github.com/albumentations-team/albumentations,https://github.com/albumentations-team/albumentations,MIT,2018-06-06 03:10:50.000,2024-10-24 14:28:57.000000,2024-10-23 21:57:54,1041.0,94.0,1645.0,129.0,950.0,278.0,755.0,14163.0,Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125.,152.0,40,True,2024-10-23 20:36:45.000,1.4.19,74.0,albumentations,conda-forge/albumentations,,,['pytorch'],28691.0,28096.0,https://pypi.org/project/albumentations,2024-10-23 20:36:45.000,595.0,4626792.0,4630719.0,https://anaconda.org/conda-forge/albumentations,2024-09-22 17:25:30.224,200286.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +62,dlib,davisking/dlib,ml-frameworks,,https://github.com/davisking/dlib,https://github.com/davisking/dlib,BSL-1.0,2014-01-29 00:45:33.000,2024-10-23 02:26:25.000000,2024-10-23 02:26:14,8287.0,20.0,3366.0,478.0,726.0,53.0,2175.0,13505.0,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,,,,31166.0,30953.0,https://pypi.org/project/dlib,2024-08-09 19:21:06.000,213.0,173908.0,191360.0,https://anaconda.org/conda-forge/dlib,2024-09-11 22:57:26.780,895730.0,,,,,2.0,25510.0,,,,,,,,,,,,,,,,,,, +63,Tokenizers,huggingface/tokenizers,nlp,,https://github.com/huggingface/tokenizers,https://github.com/huggingface/tokenizers,Apache-2.0,2019-11-01 17:52:20.000,2024-10-21 13:45:28.000000,2024-10-14 06:40:17,1824.0,40.0,793.0,119.0,657.0,57.0,951.0,9002.0,Fast State-of-the-Art Tokenizers optimized for Research and Production.,95.0,40,True,2024-10-10 09:56:39.000,0.20.1,99.0,tokenizers,conda-forge/tokenizers,,,,110944.0,109948.0,https://pypi.org/project/tokenizers,2024-10-10 09:56:28.000,996.0,32955681.0,32997770.0,https://anaconda.org/conda-forge/tokenizers,2024-10-10 20:03:32.939,2146489.0,,,,,1.0,66.0,,,,,,,,,,,,,,,,,,, +64,accelerate,huggingface/accelerate,pytorch-utils,,https://github.com/huggingface/accelerate,https://github.com/huggingface/accelerate,Apache-2.0,2020-10-30 13:27:12.000,2024-10-24 14:16:49.000000,2024-10-24 14:16:47,1600.0,98.0,956.0,96.0,1577.0,124.0,1509.0,7863.0,"A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic..",299.0,40,True,2024-10-12 03:01:13.000,1.0.1,62.0,accelerate,conda-forge/accelerate,,,['pytorch'],56805.0,55278.0,https://pypi.org/project/accelerate,2024-10-12 02:59:19.000,1527.0,7921424.0,7927754.0,https://anaconda.org/conda-forge/accelerate,2024-10-12 14:55:25.760,227913.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +65,Shapely,shapely/shapely,geospatial-data,,https://github.com/shapely/shapely,https://github.com/shapely/shapely,BSD-3-Clause,2011-12-31 19:43:11.000,2024-10-17 22:09:19.000000,2024-10-17 22:09:19,2319.0,40.0,565.0,90.0,886.0,288.0,953.0,3875.0,Manipulation and analysis of geometric objects.,160.0,40,True,2024-08-19 21:56:13.000,2.0.6,125.0,shapely,conda-forge/shapely,,,,85552.0,82617.0,https://pypi.org/project/shapely,2024-08-19 21:56:13.000,2935.0,34021023.0,34231359.0,https://anaconda.org/conda-forge/shapely,2024-09-25 14:46:10.973,10511734.0,,,,,1.0,3687.0,,,,,,,,,,,,,,,,,,, +66,dask.distributed,dask/distributed,distributed-ml,,https://github.com/dask/distributed,https://github.com/dask/distributed,BSD-3-Clause,2015-09-13 18:42:29.000,2024-10-24 13:53:55.000000,2024-10-24 13:53:55,5910.0,69.0,718.0,57.0,5169.0,1568.0,2381.0,1576.0,A distributed task scheduler for Dask.,329.0,40,True,2024-10-17 09:14:52.000,2024.10.0,241.0,distributed,conda-forge/distributed,,,,37868.0,37016.0,https://pypi.org/project/distributed,2024-10-17 09:14:52.000,852.0,4943391.0,5230171.0,https://anaconda.org/conda-forge/distributed,2024-10-17 20:38:10.413,15199385.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +67,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 11:58:54,4534.0,2.0,4376.0,429.0,1708.0,384.0,1465.0,15636.0,Topic Modelling for Humans.,458.0,39,True,2024-07-19 14:39:26.000,4.3.3,94.0,gensim,conda-forge/gensim,,,,67114.0,65737.0,https://pypi.org/project/gensim,2024-07-19 14:39:26.000,1377.0,4557167.0,4589935.0,https://anaconda.org/conda-forge/gensim,2024-09-03 16:06:08.530,1407113.0,,,,,1.0,4905.0,-1.0,,piskvorky/gensim,,,,,,,,,,,,,,,, +68,deepface,serengil/deepface,image,,https://github.com/serengil/deepface,https://github.com/serengil/deepface,MIT,2020-02-08 20:42:28.000,2024-10-22 09:56:34.000000,2024-10-22 09:56:33,1671.0,128.0,2126.0,149.0,245.0,8.0,1120.0,13830.0,"A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python.",70.0,39,True,2024-08-17 07:30:49.000,0.0.93,92.0,deepface,,,,,4332.0,4288.0,https://pypi.org/project/deepface,2024-08-17 07:24:30.000,44.0,163055.0,163055.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,, +69,sentencepiece,google/sentencepiece,nlp,,https://github.com/google/sentencepiece,https://github.com/google/sentencepiece,Apache-2.0,2017-03-07 10:03:48.000,2024-10-22 12:12:44.992000,2024-08-18 00:47:35,986.0,10.0,1169.0,126.0,309.0,35.0,716.0,10207.0,Unsupervised text tokenizer for Neural Network-based text generation.,89.0,39,True,2024-02-19 17:03:42.000,0.2.0,35.0,sentencepiece,conda-forge/sentencepiece,,,,82478.0,80746.0,https://pypi.org/project/sentencepiece,2024-02-19 17:03:42.000,1732.0,24948276.0,24969888.0,https://anaconda.org/conda-forge/sentencepiece,2024-10-22 12:12:44.992,1071411.0,,,,,1.0,44766.0,,,,,,,,,,,,,,,,,,, +70,CuPy,cupy/cupy,gpu-utilities,,https://github.com/cupy/cupy,https://github.com/cupy/cupy,MIT,2016-11-01 09:54:45.000,2024-10-24 03:41:45.000000,2024-10-24 03:41:45,29164.0,449.0,817.0,128.0,6391.0,636.0,1769.0,9411.0,NumPy & SciPy for GPU.,393.0,39,True,2024-08-22 07:42:45.000,13.3.0,141.0,cupy,conda-forge/cupy,cupy/cupy,,,2568.0,2299.0,https://pypi.org/project/cupy,2024-08-22 07:08:16.000,269.0,52581.0,147803.0,https://anaconda.org/conda-forge/cupy,2024-10-18 20:21:57.477,4860441.0,https://hub.docker.com/r/cupy/cupy,2024-08-22 07:44:42.171252,13.0,68908.0,1.0,189794.0,,,,,,,,,,,,,,,,,,, +71,sktime,alan-turing-institute/sktime,time-series-data,,https://github.com/sktime/sktime,https://github.com/sktime/sktime,BSD-3-Clause,2018-11-06 15:08:24.000,2024-10-24 14:20:49.000000,2024-10-24 14:20:48,4994.0,278.0,1354.0,106.0,4313.0,963.0,1600.0,7876.0,A unified framework for machine learning with time series.,405.0,39,True,2024-10-19 19:36:24.000,0.34.0,83.0,sktime,conda-forge/sktime-all-extras,,,['sklearn'],3526.0,3398.0,https://pypi.org/project/sktime,2024-10-19 19:36:24.000,128.0,794578.0,820814.0,https://anaconda.org/conda-forge/sktime-all-extras,2024-10-19 20:31:28.372,1023181.0,,,,,1.0,102.0,,,sktime/sktime,,,,,,,,,,,,,,,, +72,folium,python-visualization/folium,geospatial-data,,https://github.com/python-visualization/folium,https://github.com/python-visualization/folium,MIT,2013-05-09 04:21:35.000,2024-10-23 09:05:15.000000,2024-10-23 09:00:43,1900.0,26.0,2224.0,163.0,882.0,84.0,1042.0,6895.0,Python Data. Leaflet.js Maps.,170.0,39,True,2024-10-22 13:40:31.000,0.18.0,33.0,folium,conda-forge/folium,,,,45365.0,44598.0,https://pypi.org/project/folium,2024-10-22 13:40:31.000,767.0,1510016.0,1580193.0,https://anaconda.org/conda-forge/folium,2024-10-23 06:24:47.661,3157984.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +73,GeoPandas,geopandas/geopandas,geospatial-data,,https://github.com/geopandas/geopandas,https://github.com/geopandas/geopandas,BSD-3-Clause,2013-06-27 17:03:47.000,2024-10-16 12:10:56.000000,2024-10-16 12:10:56,2031.0,25.0,928.0,104.0,1698.0,449.0,1266.0,4494.0,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'],45124.0,42285.0,https://pypi.org/project/geopandas,2024-07-02 12:26:50.000,2839.0,7912298.0,7990592.0,https://anaconda.org/conda-forge/geopandas,2024-09-21 05:55:22.256,4069935.0,,,,,1.0,2736.0,,,,,,,,,,,,,,,,,,, +74,TensorFlow Datasets,tensorflow/datasets,tensorflow-utils,,https://github.com/tensorflow/datasets,https://github.com/tensorflow/datasets,Apache-2.0,2018-09-10 21:27:22.000,2024-10-24 12:30:09.000000,2024-10-24 12:30:01,6542.0,140.0,1540.0,109.0,4492.0,699.0,744.0,4296.0,"TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...",323.0,39,True,2024-06-05 08:15:47.000,4.9.6,39.0,tensorflow-datasets,conda-forge/tensorflow-datasets,,,['tensorflow'],20133.0,19804.0,https://pypi.org/project/tensorflow-datasets,2024-06-05 08:15:42.000,329.0,1829915.0,1830799.0,https://anaconda.org/conda-forge/tensorflow-datasets,2023-06-16 19:25:46.849,36261.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +75,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 03:31:13.000,2024-10-24 14:11:01.000000,2024-10-23 13:06:06,18154.0,97.0,1313.0,83.0,8045.0,532.0,4370.0,2702.0,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,,,,4911.0,4523.0,https://pypi.org/project/mne,2024-08-19 02:18:45.000,388.0,163778.0,171969.0,https://anaconda.org/conda-forge/mne,2024-08-19 02:39:24.602,434173.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +76,PyFlink,apache/flink,ml-frameworks,,https://github.com/apache/flink,https://github.com/apache/flink,Apache-2.0,2014-06-07 07:00:10.000,2024-10-24 08:54:59.000000,2024-10-24 08:54:41,36050.0,418.0,13293.0,946.0,25558.0,1226.0,,23984.0,Apache Flink Python API.,1929.0,38,True,2024-06-14 14:43:26.000,1.19.1,49.0,apache-flink,,,,,56.0,21.0,https://pypi.org/project/apache-flink,2024-08-01 04:14:17.000,35.0,301601.0,301601.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +77,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,,6800.0,1069.0,11124.0,1805.0,7758.0,20779.0,"Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler;..",982.0,38,False,2022-10-24 07:38:03.000,1.9.1,983.0,mxnet,mxnet,,,['mxnet'],7674.0,7548.0,https://pypi.org/project/mxnet,2022-05-17 21:11:13.000,120.0,716639.0,717047.0,https://anaconda.org/anaconda/mxnet,2023-06-16 13:24:22.589,11149.0,,,,,2.0,27655.0,,,apache/mxnet,,,,,,,,,6.0,,,,,,, +78,Rasa,RasaHQ/rasa,nlp,,https://github.com/RasaHQ/rasa,https://github.com/RasaHQ/rasa,Apache-2.0,2016-10-14 12:27:49.000,2024-10-22 08:54:48.000000,2024-03-21 15:05:22,32610.0,,4626.0,355.0,6374.0,125.0,6642.0,18847.0,"Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management,..",597.0,38,True,2024-04-18 15:06:29.000,3.6.20,373.0,rasa,,,,['tensorflow'],4584.0,4524.0,https://pypi.org/project/rasa,2024-04-18 15:06:12.000,60.0,185921.0,185921.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,, +79,flair,flairNLP/flair,nlp,,https://github.com/flairNLP/flair,https://github.com/flairNLP/flair,MIT,2018-06-11 11:04:18.000,2024-10-16 11:09:02.000000,2024-10-11 11:07:14,6144.0,36.0,2097.0,203.0,1233.0,115.0,2221.0,13894.0,A very simple framework for state-of-the-art Natural Language Processing (NLP).,270.0,38,True,2024-07-25 12:21:58.000,0.14.0,33.0,flair,conda-forge/python-flair,,,['pytorch'],3718.0,3573.0,https://pypi.org/project/flair,2024-07-25 12:15:28.000,145.0,106992.0,107634.0,https://anaconda.org/conda-forge/python-flair,2024-01-05 20:59:40.138,32773.0,,,,,1.0,,-1.0,,,,,,,,,,,,,,,,,, +80,dgl,dmlc/dgl,graph,,https://github.com/dmlc/dgl,https://github.com/dmlc/dgl,Apache-2.0,2018-04-20 14:49:09.000,2024-10-18 03:43:55.000000,2024-10-18 03:43:55,4410.0,173.0,3010.0,175.0,5049.0,531.0,2357.0,13483.0,"Python package built to ease deep learning on graph, on top of existing DL frameworks.",295.0,38,True,2024-09-03 04:16:25.000,2.4.0,453.0,dgl,,,,,455.0,307.0,https://pypi.org/project/dgl,2024-05-13 01:10:39.000,148.0,171495.0,171495.0,,,,,,,,1.0,,-1.0,,,,,,,,,,,,,,,,,, +81,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,,1558.0,255.0,685.0,482.0,1060.0,12499.0,Video editing with Python.,161.0,38,True,2020-05-07 16:29:35.000,1.0.3,85.0,moviepy,conda-forge/moviepy,,,,48013.0,47070.0,https://pypi.org/project/moviepy,2021-12-15 14:41:26.454,943.0,1378816.0,1381924.0,https://anaconda.org/conda-forge/moviepy,2023-06-16 13:23:34.876,270450.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +82,Kornia,kornia/kornia,image,,https://github.com/kornia/kornia,https://github.com/kornia/kornia,Apache-2.0,2018-08-22 10:31:37.000,2024-10-21 17:10:04.000000,2024-10-21 17:10:04,2814.0,50.0,965.0,127.0,1947.0,289.0,660.0,9910.0,Geometric Computer Vision Library for Spatial AI.,271.0,38,True,2024-06-28 15:16:20.000,0.7.3,40.0,kornia,conda-forge/kornia,,,['pytorch'],12445.0,12183.0,https://pypi.org/project/kornia,2024-06-28 15:16:20.000,262.0,1969618.0,1972959.0,https://anaconda.org/conda-forge/kornia,2024-06-28 20:04:02.857,152725.0,,,,,1.0,1512.0,,,,,,,,,,,,,,,,,,, +83,espnet,espnet/espnet,audio,,https://github.com/espnet/espnet,https://github.com/espnet/espnet,Apache-2.0,2017-12-13 00:45:11.000,2024-10-20 13:10:03.000000,2024-10-20 12:46:45,22154.0,419.0,2159.0,180.0,3379.0,347.0,2082.0,8423.0,End-to-End Speech Processing Toolkit.,452.0,38,True,2024-10-01 06:28:01.000,.202409,53.0,espnet,,,,,394.0,382.0,https://pypi.org/project/espnet,2024-02-06 03:28:41.000,12.0,39304.0,39305.0,,,,,,,,1.0,82.0,,,,,,,,,,,,,,,,,,, +84,Flax,google/flax,ml-frameworks,,https://github.com/google/flax,https://github.com/google/flax,Apache-2.0,2020-01-10 09:48:37.000,2024-10-24 04:29:32.688000,2024-10-24 00:32:08,4809.0,207.0,639.0,86.0,2637.0,294.0,740.0,6063.0,Flax is a neural network library for JAX that is designed for flexibility.,244.0,38,True,2024-10-16 23:26:23.000,0.10.0,48.0,flax,conda-forge/flax,,,['jax'],10187.0,9717.0,https://pypi.org/project/flax,2024-10-16 23:26:23.000,470.0,871894.0,873625.0,https://anaconda.org/conda-forge/flax,2024-10-24 04:29:32.688,74396.0,,,,,2.0,55.0,,,,,,,,,,,,,,,,,,, +85,HoloViews,holoviz/holoviews,data-viz,,https://github.com/holoviz/holoviews,https://github.com/holoviz/holoviews,BSD-3-Clause,2014-05-07 16:59:22.000,2024-10-23 17:24:02.000000,2024-10-23 08:19:12,10864.0,46.0,402.0,58.0,3088.0,1097.0,2236.0,2696.0,"With Holoviews, your data visualizes itself.",145.0,38,True,2024-08-01 13:45:47.955,3.0.3,171.0,holoviews,conda-forge/holoviews,,,['jupyter'],12876.0,12472.0,https://pypi.org/project/holoviews,2024-10-23 08:03:48.000,399.0,683417.0,718939.0,https://anaconda.org/conda-forge/holoviews,2024-07-07 07:21:50.008,1832215.0,,,,,2.0,,,,,@pyviz/jupyterlab_pyviz,https://www.npmjs.com/package/@pyviz/jupyterlab_pyviz,2024-08-01 13:45:47.955,5.0,288.0,,,,,,,,,,, +86,PyVista,pyvista/pyvista,data-viz,,https://github.com/pyvista/pyvista,https://github.com/pyvista/pyvista,MIT,2017-05-31 18:01:42.000,2024-10-24 05:29:25.000000,2024-10-21 22:23:58,4752.0,197.0,487.0,37.0,3701.0,602.0,1135.0,2672.0,3D plotting and mesh analysis through a streamlined interface for the Visualization Toolkit (VTK).,164.0,38,True,2024-07-22 04:26:19.000,0.44.1,98.0,pyvista,conda-forge/pyvista,,,['jupyter'],4097.0,3570.0,https://pypi.org/project/pyvista,2024-07-20 05:33:22.000,527.0,346534.0,357447.0,https://anaconda.org/conda-forge/pyvista,2024-07-20 12:44:44.232,566984.0,,,,,2.0,836.0,,,,,,,,,,,,,,,,,,, +87,Rasterio,rasterio/rasterio,geospatial-data,,https://github.com/rasterio/rasterio,https://github.com/rasterio/rasterio,BSD-3-Clause,2013-11-04 16:36:27.000,2024-10-22 14:14:52.000000,2024-10-22 14:14:33,3895.0,36.0,530.0,147.0,1213.0,140.0,1683.0,2247.0,Rasterio reads and writes geospatial raster datasets.,159.0,38,True,2024-10-01 13:34:26.000,1.4.1,164.0,rasterio,conda-forge/rasterio,,,,14889.0,13456.0,https://pypi.org/project/rasterio,2024-10-01 13:28:36.000,1433.0,3739796.0,3821670.0,https://anaconda.org/conda-forge/rasterio,2024-10-01 11:13:22.492,3683986.0,,,,,2.0,969.0,,,,,,,,,,,,,,,,,,, +88,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 10:20:28.000,2024-10-24 14:43:23.000000,2024-10-24 13:43:07,1597.0,103.0,540.0,58.0,1546.0,150.0,827.0,2056.0,The official Python client for the Huggingface Hub.,203.0,38,True,2024-10-21 13:41:41.000,0.26.1,131.0,huggingface_hub,conda-forge/huggingface_hub,,,,1915.0,,https://pypi.org/project/huggingface_hub,2024-10-21 13:35:29.000,1915.0,49079372.0,49130433.0,https://anaconda.org/conda-forge/huggingface_hub,2024-10-21 20:11:59.313,2246694.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +89,imageio,imageio/imageio,image,,https://github.com/imageio/imageio,https://github.com/imageio/imageio,BSD-2-Clause,2013-05-04 22:56:45.000,2024-10-23 08:30:07.000000,2024-10-14 02:48:52,1545.0,8.0,292.0,30.0,497.0,99.0,507.0,1481.0,Python library for reading and writing image data.,118.0,38,True,2024-10-14 02:49:03.000,2.36.0,95.0,imageio,conda-forge/imageio,,,,146918.0,144476.0,https://pypi.org/project/imageio,2024-10-14 02:48:59.000,2442.0,36070858.0,36209201.0,https://anaconda.org/conda-forge/imageio,2024-10-17 18:50:42.350,7054609.0,,,,,1.0,1344.0,,,,,,,,,,,,,,,,,,, +90,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,,6713.0,1278.0,167.0,674.0,227.0,33248.0,Chinese Words Segmentation Utilities.,49.0,37,False,2020-01-20 14:27:23.000,0.42.1,32.0,jieba,conda-forge/jieba,,,,32551.0,31713.0,https://pypi.org/project/jieba,2020-01-20 14:27:23.000,838.0,1160595.0,1162404.0,https://anaconda.org/conda-forge/jieba,2023-06-16 13:21:35.778,162824.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +91,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,,9419.0,371.0,3158.0,1795.0,6719.0,29406.0,OpenMMLab Detection Toolbox and Benchmark.,480.0,37,True,2024-01-05 06:25:30.000,3.3.0,53.0,mmdet,,,,['pytorch'],3172.0,3090.0,https://pypi.org/project/mmdet,2024-01-05 06:25:30.000,82.0,186205.0,186205.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +92,Netron,lutzroeder/netron,interpretability,,https://github.com/lutzroeder/netron,https://github.com/lutzroeder/netron,MIT,2010-12-26 12:53:43.000,2024-10-24 14:18:11.000000,2024-10-24 14:17:31,8568.0,298.0,2766.0,301.0,234.0,21.0,1125.0,27938.0,"Visualizer for neural network, deep learning and machine learning models.",2.0,37,True,2024-10-19 01:50:59.000,7.9.7,673.0,netron,,,,"['pytorch', 'tensorflow']",661.0,578.0,https://pypi.org/project/netron,2024-10-19 01:50:59.000,83.0,26613.0,172475.0,,,,,,,,1.0,145862.0,,,,,,,,,,,,,,,,,,, +93,InsightFace,deepinsight/insightface,image,,https://github.com/deepinsight/insightface,https://github.com/deepinsight/insightface,MIT,2017-09-01 00:36:51.000,2024-10-11 14:13:13.000000,2024-10-11 14:13:13,2338.0,26.0,5381.0,514.0,177.0,1133.0,1375.0,23204.0,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'],2874.0,2844.0,https://pypi.org/project/insightface,2022-12-17 02:14:00.699,30.0,268029.0,551064.0,,,,,,,,2.0,5094641.0,,,,,,,,,,,,,,,,,,, +94,pyecharts,pyecharts/pyecharts,data-viz,,https://github.com/pyecharts/pyecharts,https://github.com/pyecharts/pyecharts,MIT,2017-06-22 02:50:25.000,2024-10-19 10:45:07.000000,2024-06-20 12:51:40,1687.0,,2850.0,378.0,471.0,3.0,1905.0,14866.0,Python Echarts Plotting Library.,44.0,37,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'],4743.0,4534.0,https://pypi.org/project/pyecharts,2024-06-20 15:48:17.000,209.0,155400.0,155403.0,,,,,,,,2.0,70.0,,,,,,,,,,,,,,,,,,, +95,pandas-profiling,ydataai/pandas-profiling,data-viz,,https://github.com/ydataai/ydata-profiling,https://github.com/ydataai/ydata-profiling,MIT,2016-01-09 23:47:55.000,2024-10-16 08:57:35.000000,2024-10-15 18:37:08,1491.0,17.0,1678.0,153.0,816.0,236.0,574.0,12483.0,1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.,132.0,37,True,2024-10-16 08:45:18.000,4.11.0,64.0,pandas-profiling,conda-forge/pandas-profiling,,,"['jupyter', 'pandas']",4618.0,4435.0,https://pypi.org/project/pandas-profiling,2023-02-03 17:59:40.571,183.0,337052.0,341833.0,https://anaconda.org/conda-forge/pandas-profiling,2023-06-16 13:22:30.453,468510.0,,,,,2.0,196.0,,,ydataai/ydata-profiling,,,,,,,,,,,,,,,, +96,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,,2486.0,538.0,4121.0,697.0,2087.0,9898.0,"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,,,,15741.0,15569.0,https://pypi.org/project/theano,2020-07-27 16:13:54.000,172.0,91932.0,116736.0,https://anaconda.org/conda-forge/theano,2023-06-16 13:23:49.668,2455634.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +97,PySyft,OpenMined/PySyft,privacy-ml,,https://github.com/OpenMined/PySyft,https://github.com/OpenMined/PySyft,Apache-2.0,2017-07-18 20:41:16.000,2024-10-15 14:39:13.000000,2024-10-15 14:38:06,33332.0,1784.0,1993.0,199.0,5856.0,39.0,3392.0,9478.0,Perform data science on data that remains in someone elses server.,515.0,37,True,2024-09-04 20:09:29.000,0.9.1,319.0,syft,,,,['pytorch'],5.0,1.0,https://pypi.org/project/syft,2024-10-15 14:38:18.000,4.0,26034.0,26244.0,,,,,,,,1.0,2313.0,,,,,,,,,,,,,,,,,,, +98,Autograd,HIPS/autograd,others,,https://github.com/HIPS/autograd,https://github.com/HIPS/autograd,MIT,2014-11-24 15:50:23.000,2024-10-21 20:04:07.000000,2024-10-21 20:04:05,1445.0,25.0,910.0,211.0,244.0,179.0,243.0,6985.0,Efficiently computes derivatives of NumPy code.,60.0,37,True,2024-08-22 19:07:12.000,1.7.0,30.0,autograd,conda-forge/autograd,,,,10187.0,9904.0,https://pypi.org/project/autograd,2024-08-22 19:07:12.000,283.0,3384352.0,3401619.0,https://anaconda.org/conda-forge/autograd,2024-08-26 07:50:41.522,483495.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +99,PyQtGraph,pyqtgraph/pyqtgraph,data-viz,,https://github.com/pyqtgraph/pyqtgraph,https://github.com/pyqtgraph/pyqtgraph,MIT,2013-09-12 07:18:21.000,2024-10-23 13:57:30.000000,2024-10-13 12:30:48,4188.0,61.0,1102.0,154.0,1731.0,424.0,899.0,3886.0,Fast data visualization and GUI tools for scientific / engineering applications.,291.0,37,True,2024-04-29 02:18:56.000,0.13.7,25.0,pyqtgraph,conda-forge/pyqtgraph,,,,11499.0,10473.0,https://pypi.org/project/pyqtgraph,2024-04-29 02:18:56.000,1026.0,349025.0,360657.0,https://anaconda.org/conda-forge/pyqtgraph,2024-05-02 20:24:38.556,604893.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +100,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 01:09:14.000,2024-10-24 14:21:47.000000,2024-10-17 21:33:51,4927.0,557.0,1102.0,150.0,1367.0,66.0,701.0,1886.0,Documentation and samples for ArcGIS API for Python.,94.0,37,True,2024-09-24 16:57:38.000,2.4.0,50.0,arcgis,,esridocker/arcgis-api-python-notebook,,,879.0,839.0,https://pypi.org/project/arcgis,2024-10-01 15:35:29.000,40.0,81133.0,81262.0,,,,https://hub.docker.com/r/esridocker/arcgis-api-python-notebook,,,,2.0,12578.0,,,,,,,,,,,,,,,,,,, +101,Fiona,Toblerity/Fiona,geospatial-data,,https://github.com/Toblerity/Fiona,https://github.com/Toblerity/Fiona,BSD-3-Clause,2011-12-31 19:47:00.000,2024-10-21 16:46:25.000000,2024-10-21 16:46:22,1564.0,23.0,202.0,47.0,611.0,32.0,774.0,1155.0,Fiona reads and writes geographic data files.,76.0,37,True,2024-09-16 20:20:31.000,1.10.1,117.0,fiona,conda-forge/fiona,,,,23283.0,22980.0,https://pypi.org/project/fiona,2024-09-16 20:14:20.000,303.0,5411647.0,5530952.0,https://anaconda.org/conda-forge/fiona,2024-09-18 13:16:30.929,6084576.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +102,fairseq,facebookresearch/fairseq,nlp,,https://github.com/facebookresearch/fairseq,https://github.com/facebookresearch/fairseq,MIT,2017-08-29 16:26:12.000,2024-10-18 16:40:02.000000,2024-10-18 16:40:02,2327.0,3.0,6393.0,427.0,1348.0,1285.0,3050.0,30371.0,Facebook AI Research Sequence-to-Sequence Toolkit written in Python.,428.0,36,True,2022-06-27 19:32:58.000,0.12.2,16.0,fairseq,conda-forge/fairseq,,,['pytorch'],3757.0,3640.0,https://pypi.org/project/fairseq,2022-06-27 19:32:38.000,117.0,143622.0,145534.0,https://anaconda.org/conda-forge/fairseq,2024-09-22 22:23:30.593,97308.0,,,,,1.0,360.0,,,,,,,,,,,,,,,,,,, +103,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,,2430.0,229.0,342.0,304.0,225.0,14382.0,Image augmentation for machine learning experiments.,36.0,36,False,2020-02-06 06:18:40.000,0.4.0,11.0,imgaug,conda-forge/imgaug,,,,22514.0,22249.0,https://pypi.org/project/imgaug,2020-02-05 20:54:22.000,265.0,553686.0,556526.0,https://anaconda.org/conda-forge/imgaug,2023-06-16 16:15:24.882,181823.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +104,ivy,unifyai/ivy,ml-frameworks,,https://github.com/ivy-llc/ivy,https://github.com/ivy-llc/ivy,Intel-ACPI,2021-01-19 08:37:25.000,2024-10-24 14:35:06.000000,2024-10-24 14:35:02,18767.0,350.0,5757.0,70.0,11743.0,937.0,15950.0,14014.0,Convert Machine Learning Code Between Frameworks.,1479.0,36,False,2023-06-29 19:33:01.167,0.0.0,131.0,ivy,,,,,14.0,,https://pypi.org/project/ivy,2024-10-24 13:22:00.000,14.0,12504.0,12504.0,,,,,,,,2.0,,,,ivy-llc/ivy,,,,,,,,,,,,,,,, +105,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,,5212.0,382.0,720.0,660.0,1367.0,13016.0,"A multi-platform library for OpenGL, OpenGL ES, Vulkan, window and input.",199.0,36,False,2024-02-24 10:01:09.000,2.7.0,58.0,glfw,conda-forge/glfw,,,,1645.0,1452.0,https://pypi.org/project/glfw,2024-02-24 10:01:09.000,193.0,603023.0,643786.0,https://anaconda.org/conda-forge/glfw,2024-02-24 15:41:47.790,264074.0,,,,,2.0,3997699.0,,,,,,,,,,,,,,,,,,, +106,NeMo,NVIDIA/NeMo,nlp,,https://github.com/NVIDIA/NeMo,https://github.com/NVIDIA/NeMo,Apache-2.0,2019-08-05 20:16:42.000,2024-10-24 14:17:54.000000,2024-10-24 11:07:26,7362.0,556.0,2464.0,206.0,8031.0,168.0,2225.0,11937.0,"A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal,..",358.0,36,True,2024-08-15 21:55:14.000,r2.0.0rc1,74.0,nemo-toolkit,,,,['pytorch'],34.0,21.0,https://pypi.org/project/nemo-toolkit,2024-08-15 22:05:43.000,13.0,138935.0,143595.0,,,,,,,,1.0,284277.0,,,,,,,,,,,,,,,,,,, +107,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,,2245.0,280.0,3096.0,91.0,2477.0,11750.0,"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'],4371.0,4246.0,https://pypi.org/project/allennlp,2022-10-18 23:54:05.191,125.0,179311.0,181516.0,https://anaconda.org/conda-forge/allennlp,2023-06-16 16:12:37.768,154387.0,,,,,1.0,69.0,,,,,,,,,,,,,,,,,,, +108,TextBlob,sloria/TextBlob,nlp,,https://github.com/sloria/TextBlob,https://github.com/sloria/TextBlob,MIT,2013-06-30 18:29:18.000,2024-10-21 22:38:56.000000,2024-08-07 18:02:18,598.0,4.0,1148.0,262.0,199.0,112.0,171.0,9135.0,"Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation,..",37.0,36,True,2024-02-15 20:31:28.000,0.18.0,61.0,textblob,conda-forge/textblob,,,,44243.0,43853.0,https://pypi.org/project/textblob,2024-02-15 20:39:47.000,390.0,1347467.0,1350190.0,https://anaconda.org/conda-forge/textblob,2023-06-16 13:22:54.304,266926.0,,,,,1.0,123.0,,,,,,,,,,,,,,,,,,, +109,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 03:34:11,5357.0,36.0,1748.0,134.0,1020.0,371.0,1948.0,8899.0,"An open-source, low-code machine learning library in Python.",141.0,36,True,2024-04-28 18:46:27.000,3.3.2,98.0,pycaret,conda-forge/pycaret,,,,6539.0,6508.0,https://pypi.org/project/pycaret,2024-04-28 18:46:21.000,31.0,288643.0,289790.0,https://anaconda.org/conda-forge/pycaret,2024-04-25 15:07:46.052,56653.0,,,,,2.0,715.0,,,,,,,,,,,,,,,,,,, +110,FiftyOne,voxel51/fiftyone,data-viz,,https://github.com/voxel51/fiftyone,https://github.com/voxel51/fiftyone,Apache-2.0,2020-04-22 13:43:28.000,2024-10-24 14:28:36.000000,2024-10-24 05:48:03,21493.0,802.0,552.0,59.0,3447.0,488.0,1064.0,8803.0,"Visualize, create, and debug image and video datasets and model predictions.",135.0,36,True,2024-10-14 14:23:30.000,1.0.1,149.0,fiftyone,,,,"['tensorflow', 'pytorch', 'jupyter']",736.0,714.0,https://pypi.org/project/fiftyone,2024-10-14 14:02:54.000,22.0,117007.0,117007.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +111,einops,arogozhnikov/einops,ml-frameworks,,https://github.com/arogozhnikov/einops,https://github.com/arogozhnikov/einops,MIT,2018-09-22 00:45:08.000,2024-10-13 22:42:35.000000,2024-10-13 22:41:32,698.0,21.0,344.0,67.0,126.0,35.0,149.0,8461.0,"Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others).",30.0,36,True,2024-04-28 04:07:49.000,0.8.0,15.0,einops,conda-forge/einops,,,,50600.0,48560.0,https://pypi.org/project/einops,2024-04-28 04:07:49.000,2040.0,5522178.0,5528079.0,https://anaconda.org/conda-forge/einops,2024-04-28 06:22:09.150,283294.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +112,MONAI,Project-MONAI/MONAI,medical-data,,https://github.com/Project-MONAI/MONAI,https://github.com/Project-MONAI/MONAI,Apache-2.0,2019-10-11 16:41:38.000,2024-10-23 15:47:01.000000,2024-10-23 15:47:01,3154.0,71.0,1065.0,89.0,3506.0,373.0,2767.0,5792.0,AI Toolkit for Healthcare Imaging.,207.0,36,True,2024-10-17 00:54:28.000,1.4.0,102.0,monai,conda-forge/monai,,,['pytorch'],3114.0,2993.0,https://pypi.org/project/monai,2024-10-16 17:29:29.000,121.0,161604.0,162527.0,https://anaconda.org/conda-forge/monai,2024-10-17 00:39:44.050,31389.0,,,,,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,,844.0,91.0,218.0,132.0,686.0,4511.0,"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,,,,,465997.0,455641.0,https://pypi.org/project/opencv-python,2024-06-17 18:28:13.000,10356.0,15903108.0,15903108.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +114,Core ML Tools,apple/coremltools,model-serialisation,,https://github.com/apple/coremltools,https://github.com/apple/coremltools,BSD-3-Clause,2017-06-30 07:39:02.000,2024-10-23 21:06:38.000000,2024-10-21 16:41:44,1189.0,28.0,627.0,126.0,939.0,350.0,1097.0,4399.0,"Core ML tools contain supporting tools for Core ML model conversion, editing, and validation.",178.0,36,True,2024-09-16 20:50:54.000,8.0,50.0,coremltools,conda-forge/coremltools,,,,4287.0,4206.0,https://pypi.org/project/coremltools,2024-09-16 21:06:12.000,81.0,623845.0,625489.0,https://anaconda.org/conda-forge/coremltools,2023-06-16 19:23:14.592,72317.0,,,,,2.0,11786.0,2.0,,,,,,,,,,,,,,,,,, +115,tensorflow-probability,tensorflow/probability,probabilistics,,https://github.com/tensorflow/probability,https://github.com/tensorflow/probability,Apache-2.0,2017-10-23 23:50:54.000,2024-10-23 14:12:46.000000,2024-10-23 14:12:44,12175.0,21.0,1098.0,163.0,466.0,691.0,754.0,4262.0,Probabilistic reasoning and statistical analysis in TensorFlow.,496.0,36,True,2024-03-12 19:43:46.000,0.24.0,52.0,tensorflow-probability,conda-forge/tensorflow-probability,,,['tensorflow'],615.0,2.0,https://pypi.org/project/tensorflow-probability,2024-03-12 19:43:39.000,613.0,1494162.0,1497534.0,https://anaconda.org/conda-forge/tensorflow-probability,2024-05-27 12:58:13.692,148388.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +116,Thinc,explosion/thinc,ml-frameworks,,https://github.com/explosion/thinc,https://github.com/explosion/thinc,MIT,2014-10-16 16:34:59.000,2024-10-01 10:35:24.000000,2024-09-30 12:55:05,5344.0,19.0,275.0,78.0,797.0,18.0,128.0,2820.0,"A refreshing functional take on deep learning, compatible with your favorite libraries.",64.0,36,True,2024-10-01 10:35:24.000,8.3.2,241.0,thinc,conda-forge/thinc,,,,54844.0,54703.0,https://pypi.org/project/thinc,2024-10-01 10:35:24.000,141.0,12724740.0,12783728.0,https://anaconda.org/conda-forge/thinc,2024-07-14 15:52:37.957,3126201.0,,,,,2.0,389.0,,,,,,,,,,,,,,,,,,, +117,optimum,huggingface/optimum,gpu-utilities,,https://github.com/huggingface/optimum,https://github.com/huggingface/optimum,Apache-2.0,2021-07-20 12:36:40.000,2024-10-24 14:07:17.000000,2024-10-22 14:48:29,1120.0,47.0,454.0,57.0,1313.0,418.0,430.0,2539.0,Accelerate training and inference of Transformers and Diffusers with easy to use hardware optimization tools.,126.0,36,True,2024-10-22 15:04:30.000,1.23.2,73.0,optimum,conda-forge/optimum,,,,3846.0,3675.0,https://pypi.org/project/optimum,2024-10-22 14:59:14.000,171.0,989115.0,989955.0,https://anaconda.org/conda-forge/optimum,2024-05-29 19:43:21.254,25203.0,,,,,1.0,,2.0,,,,,,,,,,,,,,,,,, +118,Ax,facebook/Ax,hyperopt,,https://github.com/facebook/Ax,https://github.com/facebook/Ax,MIT,2019-02-09 15:23:44.000,2024-10-24 14:08:26.000000,2024-10-24 14:03:20,3426.0,302.0,306.0,69.0,2185.0,59.0,719.0,2369.0,Adaptive Experimentation Platform.,176.0,36,True,2024-09-23 20:22:26.000,0.4.3,43.0,ax-platform,conda-forge/ax-platform,,,['pytorch'],876.0,822.0,https://pypi.org/project/ax-platform,2024-09-23 20:22:26.000,54.0,121400.0,122106.0,https://anaconda.org/conda-forge/ax-platform,2024-09-24 20:13:10.358,28241.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +119,PennyLane,PennyLaneAI/PennyLane,others,,https://github.com/PennyLaneAI/pennylane,https://github.com/PennyLaneAI/pennylane,Apache-2.0,2018-04-17 16:45:42.000,2024-10-24 14:51:53.000000,2024-10-24 09:51:44,4650.0,290.0,595.0,46.0,5091.0,324.0,1091.0,2326.0,"PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry...",185.0,36,True,2024-09-12 16:21:00.000,0.38.1,59.0,pennylane,conda-forge/pennylane,,,,1219.0,1103.0,https://pypi.org/project/pennylane,2024-09-12 16:21:00.000,116.0,74820.0,79257.0,https://anaconda.org/conda-forge/pennylane,2024-07-09 13:59:12.283,155270.0,,,,,1.0,96.0,,,,,,,,,,,,,,,,,,, +120,metrics,Lightning-AI/metrics,distributed-ml,,https://github.com/Lightning-AI/torchmetrics,https://github.com/Lightning-AI/torchmetrics,Apache-2.0,2020-12-22 20:02:42.000,2024-10-24 14:02:05.000000,2024-10-24 09:16:11,1964.0,105.0,397.0,32.0,1696.0,71.0,804.0,2119.0,"Machine learning metrics for distributed, scalable PyTorch applications.",254.0,36,True,2024-10-23 07:05:32.000,1.5.1,51.0,metrics,conda-forge/torchmetrics,,,['pytorch'],31556.0,31554.0,https://pypi.org/project/metrics,2018-04-28 10:58:56.000,2.0,6069.0,43874.0,https://anaconda.org/conda-forge/torchmetrics,2024-10-24 12:57:19.442,1619953.0,,,,,2.0,5716.0,,,Lightning-AI/torchmetrics,,,,,,,,,,,,,,,, +121,arviz,arviz-devs/arviz,interpretability,,https://github.com/arviz-devs/arviz,https://github.com/arviz-devs/arviz,Apache-2.0,2015-07-29 11:51:10.000,2024-10-08 21:42:17.000000,2024-10-08 21:42:17,1568.0,13.0,397.0,48.0,1518.0,179.0,687.0,1600.0,Exploratory analysis of Bayesian models with Python.,163.0,36,True,2024-09-28 20:50:27.000,0.20.0,39.0,arviz,conda-forge/arviz,,,,8190.0,7877.0,https://pypi.org/project/arviz,2024-09-28 20:50:27.000,313.0,1455723.0,1497787.0,https://anaconda.org/conda-forge/arviz,2024-09-29 12:11:02.561,2229333.0,,,,,1.0,161.0,,,,,,,,,,,,,,,,,,, +122,cartopy,SciTools/cartopy,data-viz,,https://github.com/SciTools/cartopy,https://github.com/SciTools/cartopy,BSD-3-Clause,2012-08-03 07:43:59.000,2024-10-23 19:36:25.000000,2024-10-23 19:36:24,3104.0,44.0,362.0,55.0,1204.0,316.0,975.0,1425.0,Cartopy - a cartographic python library with matplotlib support.,128.0,36,True,2024-10-08 23:24:50.000,0.24.1,32.0,cartopy,conda-forge/cartopy,,,,6565.0,5847.0,https://pypi.org/project/cartopy,2024-10-08 23:24:50.000,718.0,413508.0,491649.0,https://anaconda.org/conda-forge/cartopy,2024-10-07 23:20:51.384,4141479.0,,,,,2.0,,2.0,,,,,,,,,,,,,,,,,, +123,Nilearn,nilearn/nilearn,medical-data,,https://github.com/nilearn/nilearn,https://github.com/nilearn/nilearn,BSD-3-Clause,2011-01-09 19:02:23.000,2024-10-24 13:45:08.000000,2024-10-24 13:45:08,10445.0,116.0,595.0,70.0,2583.0,298.0,1843.0,1178.0,Machine learning for NeuroImaging in Python.,249.0,36,True,2024-04-09 09:15:50.000,0.10.4,47.0,nilearn,conda-forge/nilearn,,,['sklearn'],3805.0,3509.0,https://pypi.org/project/nilearn,2024-04-09 09:09:58.000,296.0,65009.0,71345.0,https://anaconda.org/conda-forge/nilearn,2024-04-09 13:18:52.622,297532.0,,,,,1.0,241.0,,,,,,,,,,,,,,,,,,, +124,pyproj,pyproj4/pyproj,geospatial-data,,https://github.com/pyproj4/pyproj,https://github.com/pyproj4/pyproj,MIT,2014-12-29 21:38:25.000,2024-10-22 12:04:54.000000,2024-10-22 12:03:37,1585.0,32.0,211.0,34.0,715.0,32.0,590.0,1053.0,Python interface to PROJ (cartographic projections and coordinate transformations library).,67.0,36,True,2024-10-01 05:02:59.000,3.7.0,63.0,pyproj,conda-forge/pyproj,,,,36582.0,34842.0,https://pypi.org/project/pyproj,2024-10-01 05:02:59.000,1740.0,9942201.0,10114976.0,https://anaconda.org/conda-forge/pyproj,2024-10-01 16:10:00.706,8811535.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +125,NiBabel,nipy/nibabel,medical-data,,https://github.com/nipy/nibabel,https://github.com/nipy/nibabel,MIT,2010-07-22 16:28:30.000,2024-10-23 17:14:10.689000,2024-10-23 13:35:18,6042.0,136.0,259.0,37.0,852.0,130.0,410.0,652.0,Python package to access a cacophony of neuro-imaging file formats.,104.0,36,True,2024-10-23 14:19:52.000,5.3.2,45.0,nibabel,conda-forge/nibabel,,,,23415.0,22234.0,https://pypi.org/project/nibabel,2024-10-23 14:19:52.000,1181.0,1410213.0,1425305.0,https://anaconda.org/conda-forge/nibabel,2024-10-23 17:14:10.689,784832.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +126,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,,13466.0,1566.0,232.0,792.0,588.0,53207.0,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'],3515.0,3399.0,https://pypi.org/project/face_recognition,2020-02-20 14:26:01.000,116.0,138588.0,139182.0,https://anaconda.org/conda-forge/face_recognition,2023-06-16 19:21:40.721,28414.0,,,,,2.0,1390.0,,,,,,,,,,,,,,,,,,, +127,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,,4195.0,288.0,749.0,87.0,1028.0,34893.0,"- a deep learning toolkit for Text-to-Speech, battle-tested in research and production.",166.0,35,True,2023-12-12 15:27:06.000,0.22.0,98.0,tts,conda-forge/tts,,,"['pytorch', 'tensorflow']",1876.0,1823.0,https://pypi.org/project/tts,2023-12-12 15:27:06.000,53.0,133740.0,215023.0,https://anaconda.org/conda-forge/tts,2023-06-16 19:27:41.222,18040.0,,,,,1.0,3473661.0,,,,,,,,,,,,,,,,,,, +128,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,,4709.0,846.0,268.0,556.0,611.0,25898.0,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,,,,6978.0,6731.0,https://pypi.org/project/fasttext,2024-06-12 09:44:40.000,247.0,1622317.0,1624463.0,https://anaconda.org/conda-forge/fasttext,2024-05-19 03:10:51.802,105156.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +129,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,,3947.0,670.0,1677.0,151.0,1987.0,25259.0,"DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices..",163.0,35,False,2020-12-10 17:22:09.000,0.9.3,100.0,deepspeech,conda-forge/deepspeech,,,['tensorflow'],485.0,461.0,https://pypi.org/project/deepspeech,2020-12-19 10:05:12.000,24.0,54481.0,70991.0,https://anaconda.org/conda-forge/deepspeech,2023-06-16 19:27:01.157,3222.0,,,,,1.0,1199255.0,,,,,,,,,,,,,,,,,,, +130,EasyOCR,JaidedAI/EasyOCR,ocr,,https://github.com/JaidedAI/EasyOCR,https://github.com/JaidedAI/EasyOCR,Apache-2.0,2020-03-14 11:46:39.000,2024-09-24 11:34:43.000000,2024-09-24 11:18:06,618.0,1.0,3133.0,315.0,259.0,430.0,596.0,24214.0,"Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic,..",129.0,35,True,2024-09-24 11:34:43.000,1.7.2,33.0,easyocr,,,,,9141.0,8928.0,https://pypi.org/project/easyocr,2024-09-24 11:34:43.000,213.0,485447.0,781978.0,,,,,,,,1.0,15419644.0,-1.0,,,,,,,,,,,,,,,,,, +131,Recommenders,microsoft/recommenders,recommender-systems,,https://github.com/recommenders-team/recommenders,https://github.com/recommenders-team/recommenders,MIT,2018-09-19 10:06:07.000,2024-10-21 14:38:38.000000,2024-09-11 08:45:28,9010.0,43.0,3078.0,274.0,1294.0,163.0,703.0,19070.0,Best Practices on Recommendation Systems.,136.0,35,True,2024-05-01 18:45:29.000,1.2.0,13.0,recommenders,,,,,128.0,124.0,https://pypi.org/project/recommenders,2024-05-01 18:45:29.000,4.0,32554.0,32562.0,,,,,,,,1.0,594.0,,,recommenders-team/recommenders,,,,,,,,,,,,,,,, +132,Prophet,facebook/prophet,time-series-data,,https://github.com/facebook/prophet,https://github.com/facebook/prophet,MIT,2016-11-16 01:50:08.000,2024-10-20 08:37:57.000000,2024-10-20 08:37:57,818.0,16.0,4522.0,451.0,464.0,421.0,1733.0,18401.0,Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear..,183.0,35,True,2024-10-02 23:56:39.000,1.1.6-patched-pypi,18.0,fbprophet,conda-forge/prophet,,,,112.0,21.0,https://pypi.org/project/fbprophet,2020-09-05 16:12:50.000,91.0,229970.0,260385.0,https://anaconda.org/conda-forge/prophet,2024-10-04 13:02:12.277,1276134.0,,,,,1.0,2831.0,,,,,,,,,,,,,,,,,,, +133,haystack,deepset-ai/haystack,nlp,,https://github.com/deepset-ai/haystack,https://github.com/deepset-ai/haystack,Apache-2.0,2019-11-14 09:05:28.000,2024-10-24 14:21:17.000000,2024-10-24 14:21:15,3705.0,161.0,1881.0,141.0,4051.0,118.0,3439.0,17292.0,"AI orchestration framework to build customizable, production-ready LLM applications. Connect components (models,..",266.0,35,True,2024-10-10 08:53:02.000,2.6.1,100.0,haystack,,,,,588.0,583.0,https://pypi.org/project/haystack,2021-12-15 14:01:39.322,5.0,7264.0,7264.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +134,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 11:55:45,1340.0,1.0,2230.0,335.0,1602.0,405.0,1860.0,14234.0,"Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.",173.0,35,True,2023-06-12 09:28:02.604,0.28.1,77.0,horovod,,,,,1276.0,1243.0,https://pypi.org/project/horovod,2023-06-12 09:28:02.604,33.0,111735.0,111735.0,,,,,,,,2.0,,,stable/horovod,,,,,,,,,,,,,,,,, +135,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,,4439.0,545.0,717.0,412.0,1283.0,14068.0,"ChatterBot is a machine learning, conversational dialog engine for creating chat bots.",103.0,35,False,2020-08-22 18:42:43.000,1.0.8,86.0,chatterbot,,,,,5974.0,5956.0,https://pypi.org/project/chatterbot,2020-08-22 18:40:36.000,18.0,93324.0,93324.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +136,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 00:37:39,894.0,4.0,1151.0,318.0,268.0,56.0,343.0,13196.0,Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk.,88.0,35,True,2023-06-14 16:39:02.504,1.17.3,47.0,annoy,conda-forge/python-annoy,,,,4550.0,4349.0,https://pypi.org/project/annoy,2023-06-14 16:39:02.504,201.0,1107307.0,1118356.0,https://anaconda.org/conda-forge/python-annoy,2024-09-05 05:37:11.713,541410.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +137,Datasette,simonw/datasette,others,,https://github.com/simonw/datasette,https://github.com/simonw/datasette,Apache-2.0,2017-10-23 00:39:03.000,2024-10-24 13:13:57.000000,2024-10-07 17:40:57,2659.0,47.0,676.0,101.0,496.0,605.0,1263.0,9481.0,An open source multi-tool for exploring and publishing data.,80.0,35,True,2024-10-07 17:38:03.000,0.65,153.0,datasette,conda-forge/datasette,,,,1749.0,1336.0,https://pypi.org/project/datasette,2024-10-07 17:41:27.000,413.0,76208.0,77304.0,https://anaconda.org/conda-forge/datasette,2024-10-08 05:31:37.168,46028.0,,,,,1.0,68.0,,,,,,,,,datasette,,,,,,,,,, +138,SpeechRecognition,Uberi/speech_recognition,audio,,https://github.com/Uberi/speech_recognition,https://github.com/Uberi/speech_recognition,BSD-3-Clause,2014-04-23 04:53:54.000,2024-10-21 14:22:54.000000,2024-10-21 14:22:54,560.0,17.0,2394.0,283.0,165.0,331.0,324.0,8395.0,"Speech recognition module for Python, supporting several engines and APIs, online and offline.",51.0,35,True,2024-10-20 09:28:59.000,3.11.0,60.0,SpeechRecognition,conda-forge/speechrecognition,,,,602.0,21.0,https://pypi.org/project/SpeechRecognition,2024-10-20 09:22:41.000,581.0,1054966.0,1059087.0,https://anaconda.org/conda-forge/speechrecognition,2024-05-06 02:00:59.322,206090.0,,,,,1.0,,2.0,,,,,,,,,,,,,,,,,, +139,cuDF,rapidsai/cudf,gpu-utilities,,https://github.com/rapidsai/cudf,https://github.com/rapidsai/cudf,Apache-2.0,2017-05-07 03:43:37.000,2024-10-24 13:10:36.000000,2024-10-24 13:10:33,39679.0,467.0,889.0,153.0,10650.0,1058.0,5523.0,8377.0,cuDF - GPU DataFrame Library.,295.0,35,True,2024-10-09 15:25:13.000,24.10.00,56.0,cudf,,,,,79.0,57.0,https://pypi.org/project/cudf,2020-06-01 20:07:47.000,22.0,3483.0,3483.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +140,Metaflow,Netflix/metaflow,ml-experiments,,https://github.com/Netflix/metaflow,https://github.com/Netflix/metaflow,Apache-2.0,2019-09-17 17:48:25.000,2024-10-24 07:40:50.000000,2024-10-24 07:37:46,1086.0,109.0,765.0,289.0,1447.0,338.0,418.0,8131.0,"Open Source Platform for developing, scaling and deploying serious ML, AI, and data science systems.",96.0,35,True,2024-10-23 21:00:32.000,2.12.26,150.0,metaflow,conda-forge/metaflow,,,,786.0,739.0,https://pypi.org/project/metaflow,2024-10-23 21:00:32.000,47.0,876076.0,880415.0,https://anaconda.org/conda-forge/metaflow,2024-10-08 15:30:55.152,221313.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +141,AutoGluon,autogluon/autogluon,hyperopt,,https://github.com/autogluon/autogluon,https://github.com/autogluon/autogluon,Apache-2.0,2019-07-29 18:51:24.000,2024-10-24 09:04:46.000000,2024-10-23 16:04:35,2341.0,77.0,917.0,99.0,2641.0,376.0,1090.0,7853.0,Fast and Accurate ML in 3 Lines of Code.,125.0,35,True,2024-06-14 20:30:21.000,1.1.1,1645.0,autogluon,conda-forge/autogluon,autogluon/autogluon,https://auto.gluon.ai,"['pytorch', 'sklearn']",872.0,845.0,https://pypi.org/project/autogluon,2024-10-24 09:04:46.000,27.0,493043.0,494191.0,https://anaconda.org/conda-forge/autogluon,2024-10-18 16:39:52.687,20575.0,https://hub.docker.com/r/autogluon/autogluon,2024-03-07 07:21:23.461952,17.0,10701.0,1.0,,,,,,,,,,,,,,,,,,,, +142,BentoML,bentoml/BentoML,model-serialisation,,https://github.com/bentoml/BentoML,https://github.com/bentoml/BentoML,Apache-2.0,2019-04-02 01:39:27.000,2024-10-24 06:19:46.000000,2024-10-24 06:19:46,3326.0,143.0,784.0,78.0,3703.0,169.0,917.0,7085.0,"The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines,..",209.0,35,True,2024-10-16 05:35:45.000,1.3.9,164.0,bentoml,,,,,2158.0,2130.0,https://pypi.org/project/bentoml,2024-10-16 05:35:45.000,28.0,121631.0,121652.0,,,,,,,,2.0,1109.0,,,,,,,,,,,,,,,,,,, +143,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 16:08:07.000,2024-10-24 14:45:38.000000,2024-10-23 21:44:05,32532.0,56.0,1994.0,386.0,6888.0,2838.0,6668.0,6899.0,"H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM)..",268.0,35,True,,,155.0,h2o,,,,,69.0,21.0,https://pypi.org/project/h2o,2024-08-29 13:55:23.000,48.0,293081.0,293081.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +144,DeepChem,deepchem/deepchem,others,,https://github.com/deepchem/deepchem,https://github.com/deepchem/deepchem,MIT,2015-09-24 23:20:28.000,2024-10-21 16:58:55.000000,2024-10-21 16:38:41,10544.0,37.0,1676.0,143.0,2446.0,638.0,1238.0,5461.0,"Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology.",250.0,35,True,2024-04-03 16:21:23.000,2.8.0,932.0,deepchem,conda-forge/deepchem,,,['tensorflow'],456.0,443.0,https://pypi.org/project/deepchem,2024-10-21 16:58:55.000,13.0,99142.0,101266.0,https://anaconda.org/conda-forge/deepchem,2024-04-05 16:46:45.105,110494.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +145,mlpack,mlpack/mlpack,ml-frameworks,,https://github.com/mlpack/mlpack,https://github.com/mlpack/mlpack,BSD-3-Clause,2014-12-17 18:16:59.000,2024-10-22 21:37:41.000000,2024-10-22 21:37:41,30454.0,233.0,1593.0,183.0,2193.0,19.0,1612.0,5074.0,"mlpack: a fast, header-only C++ machine learning library.",324.0,35,True,2024-09-20 14:12:49.000,4.5.0,48.0,mlpack,conda-forge/mlpack,,,,4.0,,https://pypi.org/project/mlpack,2024-09-20 14:12:49.000,4.0,15287.0,20234.0,https://anaconda.org/conda-forge/mlpack,2024-09-22 00:54:14.076,257274.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +146,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 14:40:43.000,2024-10-23 08:54:39.000000,2024-10-22 15:01:37,12408.0,63.0,1159.0,98.0,1388.0,141.0,759.0,4820.0,"Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction,..",138.0,35,True,2024-10-02 21:30:21.000,1.18.2,61.0,adversarial-robustness-toolbox,conda-forge/adversarial-robustness-toolbox,,,,620.0,600.0,https://pypi.org/project/adversarial-robustness-toolbox,2024-10-02 21:24:21.000,20.0,77576.0,78574.0,https://anaconda.org/conda-forge/adversarial-robustness-toolbox,2024-10-03 01:54:09.200,50902.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +147,Ignite,pytorch/ignite,ml-frameworks,,https://github.com/pytorch/ignite,https://github.com/pytorch/ignite,BSD-3-Clause,2017-11-23 17:31:21.000,2024-10-24 00:18:47.000000,2024-10-21 09:36:30,1733.0,24.0,615.0,59.0,1881.0,156.0,1266.0,4521.0,High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.,669.0,35,True,2024-08-13 12:47:02.000,0.5.1,1778.0,pytorch-ignite,pytorch/ignite,,,['pytorch'],3393.0,3295.0,https://pypi.org/project/pytorch-ignite,2024-10-24 00:18:47.000,98.0,250502.0,253149.0,https://anaconda.org/pytorch/ignite,2024-08-13 12:46:51.642,201210.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +148,plotnine,has2k1/plotnine,data-viz,,https://github.com/has2k1/plotnine,https://github.com/has2k1/plotnine,MIT,2017-04-24 19:00:44.000,2024-10-24 12:37:54.000000,2024-10-24 12:26:57,2411.0,39.0,213.0,64.0,145.0,90.0,595.0,4009.0,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,,,,9363.0,9056.0,https://pypi.org/project/plotnine,2024-05-09 20:44:49.000,307.0,2975192.0,2983097.0,https://anaconda.org/conda-forge/plotnine,2024-09-20 10:25:14.080,411082.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +149,spark-nlp,JohnSnowLabs/spark-nlp,nlp,,https://github.com/JohnSnowLabs/spark-nlp,https://github.com/JohnSnowLabs/spark-nlp,Apache-2.0,2017-09-24 19:36:44.000,2024-10-24 12:50:47.000000,2024-10-18 16:16:34,8604.0,39.0,710.0,100.0,13348.0,36.0,858.0,3856.0,State of the Art Natural Language Processing.,113.0,35,True,2024-09-25 20:20:27.000,5.5.0,148.0,spark-nlp,,,,['spark'],550.0,513.0,https://pypi.org/project/spark-nlp,2024-09-25 14:58:28.000,37.0,3680271.0,3680271.0,,,,,,,,2.0,,-1.0,,,,,,,,,,,,,,,,,, +150,torchaudio,pytorch/audio,audio,,https://github.com/pytorch/audio,https://github.com/pytorch/audio,BSD-2-Clause,2017-05-05 00:38:05.000,2024-10-24 11:34:47.000000,2024-10-23 20:30:53,2319.0,8.0,648.0,72.0,2906.0,259.0,726.0,2518.0,"Data manipulation and transformation for audio signal processing, powered by PyTorch.",228.0,35,True,2024-10-17 16:24:06.000,2.5.0,38.0,torchaudio,,,,['pytorch'],1375.0,,https://pypi.org/project/torchaudio,2024-10-17 14:49:06.000,1375.0,6642467.0,6642467.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,, +151,TFX,tensorflow/tfx,tensorflow-utils,,https://github.com/tensorflow/tfx,https://github.com/tensorflow/tfx,Apache-2.0,2019-02-04 17:14:36.000,2024-10-23 20:11:44.000000,2024-10-23 20:09:49,5913.0,233.0,701.0,88.0,6014.0,245.0,861.0,2114.0,TFX is an end-to-end platform for deploying production ML pipelines.,191.0,35,True,2024-05-13 23:20:24.000,1.15.1,98.0,tfx,,,,['tensorflow'],1599.0,1582.0,https://pypi.org/project/tfx,2024-05-13 23:20:24.000,17.0,40630.0,40630.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,, +152,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,,209.0,32.0,47.0,13.0,169.0,1634.0,Simple Python interface for Graphviz.,23.0,35,True,2024-03-21 07:50:43.000,0.20.3,58.0,graphviz,anaconda/python-graphviz,,,,77509.0,74890.0,https://pypi.org/project/graphviz,2024-03-21 07:50:43.000,2619.0,16309122.0,16309673.0,https://anaconda.org/anaconda/python-graphviz,2024-04-08 21:04:04.101,49672.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +153,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 06:45:41.000,2024-10-24 12:44:15.000000,2024-10-24 12:36:11,1888.0,132.0,173.0,29.0,1844.0,91.0,194.0,1214.0,Intel(R) Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application.,82.0,35,True,2024-09-18 12:49:48.000,2024.7.0,30.0,scikit-learn-intelex,conda-forge/scikit-learn-intelex,,,['sklearn'],12331.0,12276.0,https://pypi.org/project/scikit-learn-intelex,2024-09-17 16:36:34.000,55.0,98828.0,107321.0,https://anaconda.org/conda-forge/scikit-learn-intelex,2024-08-20 09:58:15.356,356741.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +154,NIPYPE,nipy/nipype,medical-data,,https://github.com/nipy/nipype,https://github.com/nipy/nipype,Apache-2.0,2010-07-22 17:06:49.000,2024-10-16 17:56:47.000000,2024-10-16 17:56:47,14987.0,105.0,506.0,50.0,2321.0,403.0,965.0,747.0,Workflows and interfaces for neuroimaging packages.,258.0,35,True,2023-04-06 12:55:55.544,1.8.6,64.0,nipype,conda-forge/nipype,,,,5226.0,5078.0,https://pypi.org/project/nipype,2023-04-06 12:55:55.544,148.0,189968.0,203954.0,https://anaconda.org/conda-forge/nipype,2023-09-22 18:28:24.915,699332.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +155,ColossalAI,hpcaitech/colossalai,distributed-ml,,https://github.com/hpcaitech/ColossalAI,https://github.com/hpcaitech/ColossalAI,Apache-2.0,2021-10-28 16:19:44.000,2024-10-24 09:51:19.000000,2024-10-24 09:51:19,3745.0,217.0,4342.0,383.0,4200.0,432.0,1263.0,38744.0,"Making large AI models cheaper, faster and more accessible.",192.0,34,True,2024-10-21 02:21:19.000,0.4.5,45.0,,,,,,426.0,426.0,,,,,,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +156,detectron2,facebookresearch/detectron2,image,,https://github.com/facebookresearch/detectron2,https://github.com/facebookresearch/detectron2,Apache-2.0,2019-09-05 21:30:20.000,2024-10-14 23:20:09.000000,2024-10-14 23:16:51,1533.0,7.0,7449.0,387.0,687.0,531.0,3073.0,30330.0,"Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.",273.0,34,True,2021-11-15 22:08:26.000,0.6,10.0,detectron2,conda-forge/detectron2,,,['pytorch'],2079.0,2066.0,https://pypi.org/project/detectron2,2020-02-06 00:35:57.000,13.0,,8759.0,https://anaconda.org/conda-forge/detectron2,2024-08-26 11:04:11.128,446752.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +157,OCRmyPDF,ocrmypdf/OCRmyPDF,ocr,,https://github.com/ocrmypdf/OCRmyPDF,https://github.com/ocrmypdf/OCRmyPDF,MPL-2.0,2013-12-20 08:26:28.000,2024-09-15 23:43:40.000000,2024-09-15 23:43:35,3868.0,18.0,1007.0,136.0,181.0,116.0,1065.0,13940.0,"OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them to be searched.",100.0,34,True,2024-08-31 09:35:44.000,16.5.0,244.0,ocrmypdf,conda-forge/ocrmypdf,,,,1054.0,1020.0,https://pypi.org/project/ocrmypdf,2024-08-31 09:35:10.000,34.0,131767.0,133979.0,https://anaconda.org/conda-forge/ocrmypdf,2023-06-16 19:24:58.228,80306.0,,,,,2.0,5425.0,,,,,,,,,ocrmypdf,ocrmypdf,,,,,,,,, +158,carla,carla-simulator/carla,others,,https://github.com/carla-simulator/carla,https://github.com/carla-simulator/carla,MIT,2017-10-24 09:06:23.000,2024-10-24 14:49:07.000000,2024-10-18 15:47:49,6263.0,9.0,3631.0,247.0,1728.0,1106.0,4493.0,11275.0,Open-source simulator for autonomous driving research.,190.0,34,True,2023-11-14 22:51:02.000,0.9.15,26.0,carla,,,,,840.0,829.0,https://pypi.org/project/carla,2023-11-14 22:51:02.000,11.0,15871.0,15871.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +159,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,,1031.0,133.0,234.0,360.0,274.0,8885.0,Manipulate audio with a simple and easy high level interface.,95.0,34,False,2021-03-10 02:10:41.000,0.25.1,68.0,pydub,conda-forge/pydub,,,,72326.0,70957.0,https://pypi.org/project/pydub,2021-03-10 02:09:53.000,1369.0,6870423.0,6872152.0,https://anaconda.org/conda-forge/pydub,2023-06-16 16:12:25.533,121099.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +160,Pyro,pyro-ppl/pyro,probabilistics,,https://github.com/pyro-ppl/pyro,https://github.com/pyro-ppl/pyro,Apache-2.0,2017-06-16 05:03:47.000,2024-10-24 12:11:43.000000,2024-10-24 12:11:43,2495.0,16.0,983.0,199.0,2327.0,258.0,847.0,8533.0,Deep universal probabilistic programming with Python and PyTorch.,157.0,34,True,2024-06-02 00:37:37.000,1.9.1,36.0,pyro-ppl,conda-forge/pyro-ppl,,,['pytorch'],186.0,,https://pypi.org/project/pyro-ppl,2024-06-02 00:37:37.000,186.0,377652.0,382292.0,https://anaconda.org/conda-forge/pyro-ppl,2024-06-03 00:37:06.159,199561.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +161,PyOD,yzhao062/pyod,others,,https://github.com/yzhao062/pyod,https://github.com/yzhao062/pyod,BSD-2-Clause,2017-10-03 20:29:04.000,2024-09-06 16:48:34.000000,2024-09-05 19:08:20,1865.0,2.0,1356.0,145.0,248.0,221.0,146.0,8528.0,"A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques.",60.0,34,True,2024-09-06 03:26:33.000,2.0.2,94.0,pyod,conda-forge/pyod,,,,4430.0,4317.0,https://pypi.org/project/pyod,2024-09-06 03:24:51.000,113.0,662802.0,665155.0,https://anaconda.org/conda-forge/pyod,2024-09-06 15:18:34.744,124713.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +162,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 19:36:58.000,2024-10-17 16:32:55.000000,2024-08-01 18:55:53,10421.0,2.0,1926.0,352.0,3429.0,130.0,1140.0,8478.0,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,,,,40.0,,https://pypi.org/project/vowpalwabbit,2024-08-08 17:57:21.000,40.0,59441.0,64289.0,https://anaconda.org/conda-forge/vowpalwabbit,2024-09-05 15:50:55.744,232712.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +163,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,,865.0,84.0,276.0,81.0,376.0,7869.0,"tensorboard for pytorch (and chainer, mxnet, numpy, ...).",82.0,34,True,2023-07-30 14:05:26.000,2.6.2,24.0,tensorboardX,conda-forge/tensorboardx,,,,50037.0,49412.0,https://pypi.org/project/tensorboardX,2023-08-20 13:38:18.000,625.0,3475302.0,3499295.0,https://anaconda.org/conda-forge/tensorboardx,2023-08-20 16:29:43.490,1223399.0,,,,,2.0,447.0,,,,,,,,,,,,,,,,,,, +164,UMAP,lmcinnes/umap,data-viz,,https://github.com/lmcinnes/umap,https://github.com/lmcinnes/umap,BSD-3-Clause,2017-07-02 01:11:17.000,2024-10-19 13:52:50.000000,2024-10-19 13:52:50,1847.0,43.0,796.0,127.0,287.0,473.0,338.0,7415.0,Uniform Manifold Approximation and Projection.,137.0,34,True,2024-04-03 16:53:16.000,0.5.6,40.0,umap-learn,conda-forge/umap-learn,,,,959.0,1.0,https://pypi.org/project/umap-learn,2024-04-03 16:53:16.000,958.0,1613593.0,1664767.0,https://anaconda.org/conda-forge/umap-learn,2024-08-14 17:32:09.484,2661056.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +165,stanza,stanfordnlp/stanza,nlp,,https://github.com/stanfordnlp/stanza,https://github.com/stanfordnlp/stanza,Apache-2.0,2017-09-26 08:00:56.000,2024-10-24 06:56:01.000000,2024-09-12 23:27:08,4682.0,87.0,889.0,141.0,498.0,95.0,804.0,7272.0,"Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages.",68.0,34,True,2024-09-12 23:17:21.000,1.9.2,28.0,stanza,stanfordnlp/stanza,,,,3338.0,3163.0,https://pypi.org/project/stanza,2024-09-12 23:16:02.000,175.0,259975.0,260122.0,https://anaconda.org/stanfordnlp/stanza,2023-06-16 19:18:21.932,8101.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +166,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 07:59:50.000,2024-10-24 10:06:45.000000,2024-10-24 10:06:45,3560.0,368.0,1256.0,252.0,9667.0,989.0,1600.0,6623.0,"Accelerate local LLM inference and finetuning (LLaMA, Mistral, ChatGLM, Qwen, Baichuan, Mixtral, Gemma, Phi, MiniCPM,..",109.0,34,True,2024-08-22 09:06:57.000,2.1.0,869.0,bigdl,,,,,7.0,,https://pypi.org/project/bigdl,2024-03-24 14:04:20.000,2.0,115415.0,115422.0,,,,,,,,2.0,642.0,,,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,,, +167,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,,1368.0,284.0,6588.0,12.0,2032.0,5889.0,A flexible framework of neural networks for deep learning.,326.0,34,False,2022-06-29 08:19:03.000,7.8.1.post1,111.0,chainer,conda-forge/chainer,,,,3382.0,3324.0,https://pypi.org/project/chainer,2022-01-05 05:33:36.000,58.0,162546.0,162900.0,https://anaconda.org/conda-forge/chainer,2023-06-16 19:17:58.452,19857.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +168,Captum,pytorch/captum,interpretability,,https://github.com/pytorch/captum,https://github.com/pytorch/captum,BSD-3-Clause,2019-08-27 15:34:41.000,2024-10-24 07:59:09.000000,2024-10-24 07:51:06,1180.0,76.0,486.0,266.0,866.0,230.0,338.0,4891.0,Model interpretability and understanding for PyTorch.,120.0,34,True,2023-12-05 09:21:02.000,0.7.0,10.0,captum,conda-forge/captum,,,['pytorch'],2596.0,2470.0,https://pypi.org/project/captum,2023-12-05 08:32:04.000,126.0,218281.0,220530.0,https://anaconda.org/conda-forge/captum,2023-06-16 19:28:19.191,76472.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +169,TorchServe,pytorch/serve,model-serialisation,,https://github.com/pytorch/serve,https://github.com/pytorch/serve,Apache-2.0,2019-10-03 03:17:43.000,2024-10-23 20:13:30.000000,2024-10-23 19:37:04,3880.0,41.0,858.0,57.0,1710.0,411.0,1270.0,4219.0,"Serve, optimize and scale PyTorch models in production.",216.0,34,True,2024-09-30 22:46:39.000,0.12.0,26.0,torchserve,pytorch/torchserve,pytorch/torchserve,,['pytorch'],759.0,737.0,https://pypi.org/project/torchserve,2024-09-30 18:57:42.000,22.0,55062.0,83731.0,https://anaconda.org/pytorch/torchserve,2024-09-30 18:57:10.837,325700.0,https://hub.docker.com/r/pytorch/torchserve,2024-09-30 22:07:15.226668,29.0,1350565.0,2.0,6982.0,,,,,,,,,,,,,,,,,,, +170,StatsForecast,Nixtla/statsforecast,time-series-data,,https://github.com/Nixtla/statsforecast,https://github.com/Nixtla/statsforecast,Apache-2.0,2021-11-24 02:19:14.000,2024-10-21 21:58:22.000000,2024-10-21 21:55:51,1333.0,31.0,277.0,41.0,483.0,100.0,239.0,3932.0,Lightning fast forecasting with statistical and econometric models.,46.0,34,True,2024-09-19 21:41:21.000,1.7.8,37.0,statsforecast,conda-forge/statsforecast,,,,1232.0,1175.0,https://pypi.org/project/statsforecast,2024-09-19 21:39:13.000,57.0,707037.0,710287.0,https://anaconda.org/conda-forge/statsforecast,2024-09-23 21:39:04.210,100754.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +171,rubrix,recognai/rubrix,nlp,,https://github.com/argilla-io/argilla,https://github.com/argilla-io/argilla,Apache-2.0,2021-04-28 14:37:42.000,2024-10-24 14:58:48.000000,2024-10-23 17:25:14,3457.0,207.0,364.0,30.0,3306.0,125.0,2021.0,3905.0,Argilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets.,97.0,34,True,2024-10-08 09:45:50.000,2.3.1,100.0,rubrix,conda-forge/rubrix,,,,2764.0,2764.0,https://pypi.org/project/rubrix,2022-10-24 18:22:00.951,,3695.0,4789.0,https://anaconda.org/conda-forge/rubrix,2023-06-16 19:28:09.653,37220.0,,,,,2.0,,,,argilla-io/argilla,,,,,,,,,,,,,,,, +172,VisPy,vispy/vispy,data-viz,,https://github.com/vispy/vispy,https://github.com/vispy/vispy,BSD-3-Clause,2013-03-21 18:43:22.000,2024-10-14 12:43:50.000000,2024-10-07 18:43:00,7401.0,9.0,618.0,115.0,1188.0,353.0,1115.0,3312.0,High-performance interactive 2D/3D data visualization library.,198.0,34,True,2024-06-17 12:39:47.000,0.14.3,39.0,vispy,conda-forge/vispy,,,['jupyter'],1887.0,1711.0,https://pypi.org/project/vispy,2024-06-17 12:32:22.000,173.0,401191.0,413870.0,https://anaconda.org/conda-forge/vispy,2024-09-04 12:47:04.775,620846.0,,,,,2.0,,-2.0,,,vispy,https://www.npmjs.com/package/vispy,2020-03-15 14:39:41.516,3.0,9.0,,,,,,,,,,, +173,BoTorch,pytorch/botorch,hyperopt,,https://github.com/pytorch/botorch,https://github.com/pytorch/botorch,MIT,2018-07-30 23:59:57.000,2024-10-23 23:28:20.000000,2024-10-23 23:25:05,2031.0,101.0,391.0,52.0,1777.0,65.0,470.0,3085.0,Bayesian optimization in PyTorch.,133.0,34,True,2024-09-17 16:43:01.000,0.12.0,47.0,botorch,conda-forge/botorch,,,['pytorch'],1277.0,1193.0,https://pypi.org/project/botorch,2024-09-17 16:43:01.000,84.0,215010.0,217553.0,https://anaconda.org/conda-forge/botorch,2024-09-20 23:53:13.019,127169.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +174,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 13:32:37.000,2024-10-23 22:06:54.000000,2024-10-23 22:06:53,1037.0,18.0,499.0,56.0,147.0,360.0,171.0,2792.0,A high performance implementation of HDBSCAN clustering.,94.0,34,True,2024-10-12 02:04:35.000,0.8.39,56.0,hdbscan,conda-forge/hdbscan,,,['sklearn'],4505.0,4166.0,https://pypi.org/project/hdbscan,2024-10-12 02:04:35.000,339.0,661780.0,707253.0,https://anaconda.org/conda-forge/hdbscan,2024-10-12 13:49:18.321,2182751.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +175,pgmpy,pgmpy/pgmpy,probabilistics,,https://github.com/pgmpy/pgmpy,https://github.com/pgmpy/pgmpy,MIT,2013-09-20 08:18:58.000,2024-10-24 06:22:15.000000,2024-10-24 06:22:15,3022.0,47.0,698.0,74.0,921.0,293.0,641.0,2724.0,"Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in..",132.0,34,True,2024-08-09 17:03:45.000,0.1.26,26.0,pgmpy,,,,,1260.0,1207.0,https://pypi.org/project/pgmpy,2024-08-09 16:48:04.000,53.0,125918.0,125928.0,,,,,,,,1.0,545.0,,,,,,,,,,,,,,,,,,, +176,snakemake,snakemake/snakemake,ml-experiments,,https://github.com/snakemake/snakemake,https://github.com/snakemake/snakemake,MIT,2015-10-17 15:43:54.867,2024-10-24 10:50:19.000000,2024-10-24 10:49:17,5328.0,109.0,551.0,19.0,1433.0,1138.0,691.0,2261.0,"This is the development home of the workflow management system Snakemake. For general information, see.",342.0,34,True,2024-10-23 08:32:33.000,8.24.1,367.0,snakemake,bioconda/snakemake,,,,2343.0,2111.0,https://pypi.org/project/snakemake,2024-10-23 08:32:33.000,232.0,125328.0,136420.0,https://anaconda.org/bioconda/snakemake,2024-10-24 00:32:48.345,1198033.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +177,jellyfish,jamesturk/jellyfish,nlp,,https://github.com/jamesturk/jellyfish,https://github.com/jamesturk/jellyfish,MIT,2010-07-09 20:41:11.000,2024-10-19 19:53:00.000000,2024-10-19 19:53:00,566.0,12.0,159.0,42.0,81.0,7.0,132.0,2056.0,a python library for doing approximate and phonetic matching of strings.,33.0,34,True,2024-07-28 08:19:05.000,1.1.0,44.0,jellyfish,conda-forge/jellyfish,,,,11191.0,10922.0,https://pypi.org/project/jellyfish,2024-07-28 08:19:05.000,269.0,6097888.0,6118087.0,https://anaconda.org/conda-forge/jellyfish,2024-09-06 22:00:00.405,1050387.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +178,Wand,emcconville/wand,image,,https://github.com/emcconville/wand,https://github.com/emcconville/wand,MIT,2011-09-30 21:36:38.000,2024-10-01 11:37:22.000000,2024-10-01 11:37:17,1873.0,7.0,200.0,33.0,214.0,26.0,403.0,1404.0,The ctypes-based simple ImageMagick binding for Python.,106.0,34,True,2023-11-04 01:41:17.000,0.6.13,56.0,wand,conda-forge/wand,,,,20061.0,19804.0,https://pypi.org/project/wand,2023-11-03 23:18:50.000,257.0,960778.0,962782.0,https://anaconda.org/conda-forge/wand,2023-06-16 16:16:46.218,80079.0,,,,,2.0,50693.0,,,,,,,,,,,,,,,,,,, +179,igraph,igraph/python-igraph,graph,,https://github.com/igraph/python-igraph,https://github.com/igraph/python-igraph,GPL-2.0,2015-01-08 23:55:16.000,2024-10-24 09:16:00.000000,2024-10-24 09:15:57,2914.0,39.0,248.0,35.0,228.0,49.0,510.0,1301.0,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,,,,4556.0,4159.0,https://pypi.org/project/python-igraph,2024-07-08 23:38:30.000,397.0,668059.0,686456.0,https://anaconda.org/conda-forge/igraph,2024-06-28 12:12:37.634,619395.0,,,,,1.0,564988.0,,,,,,,,,,,,,,,,,,, +180,TensorFlow Text,tensorflow/text,nlp,,https://github.com/tensorflow/text,https://github.com/tensorflow/text,Apache-2.0,2019-05-29 22:10:03.000,2024-09-30 23:37:10.000000,2024-09-05 06:54:23,889.0,6.0,341.0,42.0,1054.0,190.0,170.0,1227.0,Making text a first-class citizen in TensorFlow.,126.0,34,True,2024-07-15 22:42:38.000,2.17.0,72.0,tensorflow-text,,,,['tensorflow'],7684.0,7468.0,https://pypi.org/project/tensorflow-text,2024-09-30 23:25:49.000,216.0,8280366.0,8280366.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +181,MindsDB,mindsdb/mindsdb,ml-frameworks,,https://github.com/mindsdb/mindsdb,https://github.com/mindsdb/mindsdb,libpng-2.0,2018-08-02 17:56:45.000,2024-10-24 12:22:20.000000,2024-10-24 12:22:18,18749.0,219.0,4852.0,401.0,5500.0,233.0,3868.0,26658.0,The platform for building AI from enterprise data.,852.0,33,False,2024-10-22 12:42:27.000,24.10.4.0,493.0,mindsdb,,,,['pytorch'],,,https://pypi.org/project/mindsdb,2024-10-22 12:43:29.000,,24845.0,24845.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +182,tinygrad,geohot/tinygrad,pytorch-utils,,https://github.com/tinygrad/tinygrad,https://github.com/tinygrad/tinygrad,MIT,2020-10-18 16:23:12.000,2024-10-24 14:30:29.000000,2024-10-24 14:29:05,6480.0,1173.0,2909.0,269.0,6405.0,122.0,653.0,26653.0,You like pytorch? You like micrograd? You love tinygrad!.,347.0,33,True,2024-08-13 23:19:48.000,0.9.2,8.0,,,,,['pytorch'],117.0,117.0,,,,,,,,,,,,,1.0,,,,tinygrad/tinygrad,,,,,,,,,,,,,,,, +183,qdrant,qdrant/qdrant,nlp,,https://github.com/qdrant/qdrant,https://github.com/qdrant/qdrant,Apache-2.0,2020-05-30 21:37:01.000,2024-10-24 14:40:59.000000,2024-10-11 18:15:45,3375.0,358.0,1371.0,123.0,3759.0,307.0,1010.0,20283.0,"Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud..",122.0,33,True,2024-10-11 19:38:48.000,1.12.1,85.0,,,,,,115.0,115.0,,,,,5755.0,,,,,,,,2.0,241720.0,,,,,,,,,,,,,,,,,,, +184,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,,3484.0,465.0,671.0,590.0,672.0,15458.0,Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.,244.0,33,False,2020-06-17 16:31:34.798,1.15.7,79.0,tensor2tensor,,,,['tensorflow'],1525.0,1511.0,https://pypi.org/project/tensor2tensor,2020-06-17 16:31:34.798,14.0,10924.0,10924.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +185,Ludwig,ludwig-ai/ludwig,ml-frameworks,,https://github.com/ludwig-ai/ludwig,https://github.com/ludwig-ai/ludwig,Apache-2.0,2018-12-27 23:58:12.000,2024-10-17 22:52:48.000000,2024-10-17 22:52:09,3861.0,7.0,1185.0,194.0,2866.0,361.0,1037.0,11149.0,"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'],282.0,276.0,https://pypi.org/project/ludwig,2024-07-30 00:29:49.000,6.0,4712.0,4712.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +186,PyTorch3D,facebookresearch/pytorch3d,image,,https://github.com/facebookresearch/pytorch3d,https://github.com/facebookresearch/pytorch3d,,2019-10-25 02:23:45.000,2024-10-23 14:58:04.000000,2024-10-17 02:22:01,1180.0,13.0,1274.0,147.0,180.0,265.0,1349.0,8749.0,PyTorch3D is FAIRs library of reusable components for deep learning with 3D data.,150.0,33,False,2024-09-13 14:37:23.000,V0.7.8,19.0,pytorch3d,pytorch3d/pytorch3d,,,['pytorch'],1013.0,999.0,https://pypi.org/project/pytorch3d,2022-04-28 15:53:26.000,14.0,8145.0,12511.0,https://anaconda.org/pytorch3d/pytorch3d,2024-09-13 14:58:15.228,257617.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +187,PaddleSeg,PaddlePaddle/PaddleSeg,image,,https://github.com/PaddlePaddle/PaddleSeg,https://github.com/PaddlePaddle/PaddleSeg,Apache-2.0,2019-08-26 02:32:22.000,2024-10-18 09:05:07.000000,2024-10-18 09:05:06,2939.0,18.0,1681.0,92.0,1692.0,236.0,1906.0,8649.0,"Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in..",131.0,33,True,2023-10-18 03:54:18.000,2.9.0,19.0,paddleseg,,,,['paddle'],1300.0,1293.0,https://pypi.org/project/paddleseg,2022-11-30 11:24:02.578,7.0,1548.0,1548.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +188,Perspective,finos/perspective,data-viz,,https://github.com/finos/perspective,https://github.com/finos/perspective,Apache-2.0,2017-11-02 16:27:54.000,2024-10-22 20:55:46.000000,2024-10-22 18:43:50,6121.0,103.0,1175.0,122.0,1726.0,104.0,710.0,8425.0,"A data visualization and analytics component, especially well-suited for large and/or streaming datasets.",96.0,33,True,2024-10-22 20:09:24.000,3.1.2,133.0,perspective-python,conda-forge/perspective,,,['jupyter'],180.0,148.0,https://pypi.org/project/perspective-python,2024-10-22 20:06:47.000,26.0,27045.0,55384.0,https://anaconda.org/conda-forge/perspective,2024-09-21 14:46:30.468,1253753.0,,,,,2.0,5509.0,,,,@finos/perspective-jupyterlab,https://www.npmjs.com/package/@finos/perspective-jupyterlab,2024-10-22 20:08:03.773,6.0,3862.0,,,,,,,,,,, +189,Bayesian Optimization,fmfn/BayesianOptimization,hyperopt,,https://github.com/bayesian-optimization/BayesianOptimization,https://github.com/bayesian-optimization/BayesianOptimization,MIT,2014-06-06 08:18:56.000,2024-10-21 14:28:23.000000,2024-10-21 14:24:34,386.0,13.0,1540.0,129.0,164.0,9.0,356.0,7862.0,A Python implementation of global optimization with gaussian processes.,47.0,33,True,2024-10-21 14:26:57.000,2.0.0,17.0,bayesian-optimization,,,,,3165.0,3015.0,https://pypi.org/project/bayesian-optimization,2024-10-21 14:26:57.000,150.0,436202.0,436203.0,,,,,,,,1.0,161.0,,,bayesian-optimization/BayesianOptimization,,,,,,,,,,,,,,,, +190,featuretools,alteryx/featuretools,hyperopt,,https://github.com/alteryx/featuretools,https://github.com/alteryx/featuretools,BSD-3-Clause,2017-09-08 22:15:17.000,2024-10-21 18:05:21.000000,2024-06-21 13:43:40,1379.0,,874.0,158.0,1731.0,150.0,865.0,7243.0,An open source python library for automated feature engineering.,73.0,33,True,2024-05-14 18:59:58.000,1.31.0,106.0,featuretools,conda-forge/featuretools,,,,1872.0,1798.0,https://pypi.org/project/featuretools,2024-05-14 18:59:58.000,74.0,107702.0,111767.0,https://anaconda.org/conda-forge/featuretools,2024-05-15 15:26:44.535,211426.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +191,Hyperopt,hyperopt/hyperopt,hyperopt,,https://github.com/hyperopt/hyperopt,https://github.com/hyperopt/hyperopt,BSD-3-Clause,2011-09-06 22:24:59.000,2024-10-14 23:04:19.000000,2024-09-25 17:28:01,1221.0,1.0,1051.0,121.0,278.0,143.0,520.0,7241.0,Distributed Asynchronous Hyperparameter Optimization in Python.,104.0,33,True,2021-11-17 10:07:00.808,0.2.7,13.0,hyperopt,conda-forge/hyperopt,,,,17822.0,17369.0,https://pypi.org/project/hyperopt,2021-11-17 10:07:00.808,453.0,2350862.0,2361751.0,https://anaconda.org/conda-forge/hyperopt,2023-06-16 16:14:11.076,794957.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +192,librosa,librosa/librosa,audio,,https://github.com/librosa/librosa,https://github.com/librosa/librosa,ISC,2012-10-20 14:21:01.000,2024-10-08 01:00:43.000000,2024-10-08 01:00:39,3284.0,7.0,959.0,136.0,666.0,54.0,1161.0,7112.0,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,,,,1358.0,,https://pypi.org/project/librosa,2024-05-14 15:49:38.000,1358.0,3060878.0,3077006.0,https://anaconda.org/conda-forge/librosa,2024-05-15 16:59:32.016,822530.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +193,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 05:08:26.000,2024-10-06 21:08:11.000000,2024-10-06 21:08:11,869.0,4.0,1277.0,141.0,504.0,47.0,566.0,6825.0,A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning.,85.0,33,True,2024-10-04 17:52:31.000,0.12.4,38.0,imbalanced-learn,conda-forge/imbalanced-learn,,,['sklearn'],452.0,,https://pypi.org/project/imbalanced-learn,2024-10-04 17:00:52.000,452.0,19659890.0,19671910.0,https://anaconda.org/conda-forge/imbalanced-learn,2024-10-04 17:49:36.866,625040.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +194,InterpretML,interpretml/interpret,interpretability,,https://github.com/interpretml/interpret,https://github.com/interpretml/interpret,MIT,2019-05-03 05:47:52.000,2024-10-24 09:52:24.000000,2024-10-24 08:46:24,3432.0,171.0,728.0,144.0,128.0,108.0,343.0,6265.0,Fit interpretable models. Explain blackbox machine learning.,48.0,33,True,2024-10-24 09:52:24.000,0.6.5,53.0,interpret,,,,['jupyter'],816.0,767.0,https://pypi.org/project/interpret,2024-10-24 09:52:24.000,49.0,105197.0,105197.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,, +195,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,,1123.0,191.0,238.0,279.0,285.0,5832.0,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,,,,5603.0,5351.0,https://pypi.org/project/deap,2023-07-21 10:51:54.000,252.0,294044.0,303387.0,https://anaconda.org/conda-forge/deap,2024-09-03 13:46:04.210,448480.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +196,ClearML,allegroai/clearml,ml-experiments,,https://github.com/allegroai/clearml,https://github.com/allegroai/clearml,Apache-2.0,2019-06-10 08:18:32.000,2024-10-23 21:27:58.000000,2024-10-23 21:27:38,2435.0,41.0,649.0,95.0,273.0,491.0,566.0,5642.0,"ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline,..",101.0,33,True,2024-08-27 19:48:22.000,1.16.4,172.0,clearml,,allegroai/trains,,,1388.0,1348.0,https://pypi.org/project/clearml,2024-10-01 07:26:30.000,40.0,333322.0,333840.0,,,,https://hub.docker.com/r/allegroai/trains,2020-10-05 10:16:46.865671,,30296.0,2.0,2911.0,,,,,,,,,,,,,,,,,,, +197,aim,aimhubio/aim,ml-experiments,,https://github.com/aimhubio/aim,https://github.com/aimhubio/aim,Apache-2.0,2019-05-31 18:25:07.000,2024-10-23 20:20:21.000000,2024-10-02 16:35:21,2213.0,10.0,318.0,46.0,2189.0,387.0,664.0,5193.0,Aim An easy-to-use & supercharged open-source experiment tracker.,76.0,33,True,2024-10-02 17:28:03.000,3.25.0,1134.0,aim,conda-forge/aim,,,,747.0,709.0,https://pypi.org/project/aim,2024-10-23 20:20:21.000,38.0,887305.0,889403.0,https://anaconda.org/conda-forge/aim,2024-06-14 16:22:37.168,81840.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +198,River,online-ml/river,others,,https://github.com/online-ml/river,https://github.com/online-ml/river,BSD-3-Clause,2019-01-24 15:18:26.000,2024-10-17 15:24:00.000000,2024-10-03 19:24:18,3913.0,21.0,537.0,82.0,604.0,114.0,495.0,5057.0,Online machine learning in Python.,121.0,33,True,2024-07-09 19:24:30.000,0.21.2,22.0,river,conda-forge/river,,,,637.0,581.0,https://pypi.org/project/river,2024-07-09 19:24:30.000,56.0,737418.0,739394.0,https://anaconda.org/conda-forge/river,2023-10-06 14:40:00.791,83013.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +199,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,,644.0,89.0,272.0,41.0,253.0,4460.0,Geocoding library for Python.,133.0,33,True,2023-11-23 21:50:14.000,2.4.1,61.0,geopy,conda-forge/geopy,,,,901.0,,https://pypi.org/project/geopy,2023-11-23 21:49:30.000,901.0,6028477.0,6056876.0,https://anaconda.org/conda-forge/geopy,2024-02-28 17:12:19.096,1476790.0,,,,,2.0,87.0,,,,,,,,,,,,,,,,,,, +200,datashader,holoviz/datashader,data-viz,,https://github.com/holoviz/datashader,https://github.com/holoviz/datashader,BSD-3-Clause,2015-12-23 18:02:20.000,2024-10-11 13:48:14.000000,2024-10-10 06:47:04,1526.0,9.0,363.0,90.0,771.0,136.0,449.0,3314.0,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,,,,5123.0,4927.0,https://pypi.org/project/datashader,2024-07-04 12:26:22.000,196.0,137867.0,160135.0,https://anaconda.org/conda-forge/datashader,2024-07-08 10:48:31.985,1180225.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +201,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,,545.0,63.0,546.0,322.0,393.0,2741.0,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,,,,7085.0,6717.0,https://pypi.org/project/scikit-optimize,2024-06-04 19:12:54.000,368.0,1029623.0,1044576.0,https://anaconda.org/conda-forge/scikit-optimize,2024-06-05 12:17:25.116,747688.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +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 08:02:14.000,2024-10-18 09:06:10.000000,2024-10-18 06:45:47,3758.0,38.0,193.0,50.0,1390.0,132.0,734.0,1996.0,Ahead of Time compiler for numeric kernels.,73.0,33,True,2024-05-28 05:22:14.000,0.16.1,61.0,pythran,conda-forge/pythran,,,,2742.0,2723.0,https://pypi.org/project/pythran,2024-05-28 05:22:14.000,19.0,249954.0,264969.0,https://anaconda.org/conda-forge/pythran,2024-09-03 03:38:51.615,735783.0,,,,,2.0,,,,,,,,,,,,,,,,,,pythran,python-pythran, +203,tensorly,tensorly/tensorly,others,,https://github.com/tensorly/tensorly,https://github.com/tensorly/tensorly,BSD-2-Clause,2016-10-21 23:14:52.000,2024-10-22 17:44:47.000000,2024-10-22 17:44:47,1954.0,18.0,288.0,45.0,287.0,58.0,213.0,1552.0,TensorLy: Tensor Learning in Python.,69.0,33,True,2024-06-09 17:29:20.000,0.8.2,20.0,tensorly,conda-forge/tensorly,,,,877.0,785.0,https://pypi.org/project/tensorly,2023-03-08 01:09:02.237,92.0,93209.0,100895.0,https://anaconda.org/conda-forge/tensorly,2024-06-10 02:35:16.323,368930.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +204,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 00:56:56,1557.0,2.0,155.0,40.0,133.0,4.0,644.0,1172.0,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,,,,3980.0,3931.0,https://pypi.org/project/agate,2024-07-30 00:58:25.000,49.0,11228940.0,11234888.0,https://anaconda.org/conda-forge/agate,2024-07-30 07:34:33.171,243891.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +205,vit-pytorch,lucidrains/vit-pytorch,image,,https://github.com/lucidrains/vit-pytorch,https://github.com/lucidrains/vit-pytorch,MIT,2020-10-03 22:47:24.000,2024-10-11 02:15:57.000000,2024-10-11 02:15:17,327.0,14.0,3007.0,153.0,54.0,134.0,141.0,20247.0,"Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single..",21.0,32,True,2024-10-11 02:15:57.000,1.8.5,208.0,vit-pytorch,,,,['pytorch'],556.0,543.0,https://pypi.org/project/vit-pytorch,2024-10-11 02:15:57.000,13.0,27984.0,27984.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +206,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,,4706.0,1013.0,1869.0,363.0,658.0,17629.0,"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,,,,1024.0,1014.0,https://pypi.org/project/zipline,2020-10-05 15:46:20.429,10.0,3882.0,4063.0,https://anaconda.org/conda-forge/zipline,2023-06-16 19:21:35.991,8872.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +207,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,,1795.0,261.0,117.0,120.0,535.0,11579.0,Lime: Explaining the predictions of any machine learning classifier.,62.0,32,False,2020-04-03 22:05:03.000,0.2.0.0,39.0,lime,conda-forge/lime,,,,6740.0,6537.0,https://pypi.org/project/lime,2020-06-26 21:38:15.000,203.0,381117.0,383592.0,https://anaconda.org/conda-forge/lime,2023-06-16 13:18:57.655,232699.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +208,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,,1135.0,339.0,1683.0,523.0,1294.0,11197.0,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,,,,,382.0,377.0,https://pypi.org/project/turicreate,2020-09-30 22:51:40.000,5.0,19193.0,19324.0,,,,,,,,3.0,10758.0,,,,,,,,,,,,,,,,,,, +209,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,,2091.0,283.0,3401.0,51.0,1494.0,10481.0,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'],262.0,257.0,https://pypi.org/project/parlai,2022-09-20 02:56:01.305,5.0,4327.0,4327.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +210,wordcloud,amueller/word_cloud,data-viz,,https://github.com/amueller/word_cloud,https://github.com/amueller/word_cloud,MIT,2012-11-04 22:57:59.000,2024-09-16 13:29:20.331000,2024-09-15 17:01:45,578.0,2.0,2312.0,217.0,251.0,129.0,418.0,10131.0,A little word cloud generator in Python.,72.0,32,True,2023-12-09 14:04:35.000,1.9.3,20.0,wordcloud,conda-forge/wordcloud,,,,552.0,21.0,https://pypi.org/project/wordcloud,2023-12-09 14:04:35.000,531.0,1691169.0,1701966.0,https://anaconda.org/conda-forge/wordcloud,2024-09-16 13:29:20.331,550697.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +211,Sonnet,deepmind/sonnet,ml-frameworks,,https://github.com/google-deepmind/sonnet,https://github.com/google-deepmind/sonnet,Apache-2.0,2017-04-03 11:34:35.000,2024-10-01 18:34:33.000000,2024-04-08 20:21:10,864.0,,1290.0,422.0,89.0,32.0,161.0,9767.0,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'],1366.0,1347.0,https://pypi.org/project/dm-sonnet,2024-01-02 11:15:06.000,19.0,24739.0,25329.0,https://anaconda.org/conda-forge/sonnet,2023-06-16 16:19:12.602,34818.0,,,,,3.0,,,,google-deepmind/sonnet,,,,,,,,,,,,,,,, +212,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,,2243.0,178.0,1152.0,27.0,1429.0,6750.0,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'],315.0,292.0,https://pypi.org/project/OpenNMT-py,2024-03-18 14:02:12.000,23.0,10932.0,10932.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +213,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,,1813.0,196.0,206.0,13.0,1343.0,6300.0,"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'],1632.0,1614.0,https://pypi.org/project/tensorpack,2021-01-22 19:59:12.425,18.0,15379.0,15702.0,https://anaconda.org/conda-forge/tensorpack,2023-06-16 19:27:42.012,11590.0,,,,,3.0,184.0,,,,,,,,,,,,,,,,,,, +214,kaggle,Kaggle/kaggle-api,ml-experiments,,https://github.com/Kaggle/kaggle-api,https://github.com/Kaggle/kaggle-api,Apache-2.0,2018-01-25 03:02:39.000,2024-10-18 22:29:38.000000,2024-10-07 16:58:46,205.0,16.0,1089.0,200.0,149.0,146.0,339.0,6214.0,Official Kaggle API.,47.0,32,True,2024-07-24 19:08:19.000,1.6.17,74.0,kaggle,conda-forge/kaggle,,,,230.0,21.0,https://pypi.org/project/kaggle,2024-07-24 19:08:19.000,209.0,215863.0,219666.0,https://anaconda.org/conda-forge/kaggle,2024-07-27 21:52:01.276,186348.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +215,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 17:20:35.000,2024-09-11 20:27:12.000000,2024-09-11 20:27:12,1230.0,2.0,657.0,62.0,140.0,61.0,446.0,5993.0,"The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.",42.0,32,True,2024-07-25 01:34:14.000,2.6.1,212.0,pytorch-metric-learning,metric-learning/pytorch-metric-learning,,,['pytorch'],1995.0,1945.0,https://pypi.org/project/pytorch-metric-learning,2024-07-25 01:34:14.000,50.0,805533.0,805743.0,https://anaconda.org/metric-learning/pytorch-metric-learning,2023-06-16 19:17:36.446,11986.0,,,,,1.0,,-2.0,,,,,,,,,,,,,,,,,, +216,Tesseract,madmaze/pytesseract,ocr,,https://github.com/madmaze/pytesseract,https://github.com/madmaze/pytesseract,Apache-2.0,2010-10-27 23:02:49.000,2024-10-15 22:29:30.000000,2024-10-15 22:29:26,624.0,6.0,714.0,110.0,194.0,18.0,350.0,5816.0,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,,,,971.0,,https://pypi.org/project/pytesseract,2024-08-16 02:36:10.000,971.0,2352394.0,2364735.0,https://anaconda.org/conda-forge/pytesseract,2023-10-15 19:50:43.241,629402.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +217,MLxtend,rasbt/mlxtend,sklearn-utils,,https://github.com/rasbt/mlxtend,https://github.com/rasbt/mlxtend,BSD-3-Clause,2014-08-14 01:56:16.000,2024-10-23 18:26:01.000000,2024-10-23 18:26:01,1647.0,1.0,858.0,116.0,530.0,149.0,342.0,4886.0,A library of extension and helper modules for Pythons data analysis and machine learning libraries.,108.0,32,True,2024-01-05 09:13:47.000,0.23.1,52.0,mlxtend,conda-forge/mlxtend,,,['sklearn'],15786.0,15605.0,https://pypi.org/project/mlxtend,2024-01-05 09:13:47.000,181.0,601106.0,607501.0,https://anaconda.org/conda-forge/mlxtend,2024-01-05 18:58:45.309,326195.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +218,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,,619.0,65.0,224.0,223.0,162.0,4336.0,Header-only C++/python library for fast approximate nearest neighbors.,72.0,32,True,2023-12-03 04:16:17.000,0.8.0,11.0,hnswlib,conda-forge/hnswlib,,,,7217.0,7083.0,https://pypi.org/project/hnswlib,2023-12-03 04:16:17.000,134.0,975288.0,980606.0,https://anaconda.org/conda-forge/hnswlib,2023-09-27 14:20:16.958,244671.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +219,sacred,IDSIA/sacred,ml-experiments,,https://github.com/IDSIA/sacred,https://github.com/IDSIA/sacred,MIT,2014-03-31 18:05:29.000,2024-10-22 09:21:38.000000,2024-10-22 09:21:38,1351.0,7.0,380.0,70.0,375.0,102.0,460.0,4235.0,"Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.",106.0,32,True,2024-08-26 09:23:15.000,0.8.6,30.0,sacred,conda-forge/sacred,,,,3288.0,3228.0,https://pypi.org/project/sacred,2024-08-26 09:23:15.000,60.0,99373.0,99566.0,https://anaconda.org/conda-forge/sacred,2023-11-28 14:54:27.704,6771.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +220,Dedupe,dedupeio/dedupe,nlp,,https://github.com/dedupeio/dedupe,https://github.com/dedupeio/dedupe,MIT,2012-04-20 14:57:36.000,2024-10-14 02:32:51.000000,2024-08-15 14:20:30,3331.0,10.0,548.0,120.0,383.0,72.0,743.0,4128.0,"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,,,,359.0,340.0,https://pypi.org/project/dedupe,2024-08-15 14:31:34.000,19.0,175450.0,177731.0,https://anaconda.org/conda-forge/dedupe,2023-06-16 19:28:08.623,77563.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +221,AzureML SDK,Azure/MachineLearningNotebooks,ml-experiments,,https://github.com/Azure/MachineLearningNotebooks,https://github.com/Azure/MachineLearningNotebooks,MIT,2018-08-17 17:29:14.000,2024-10-21 16:03:36.000000,2024-10-21 16:03:36,1299.0,4.0,2506.0,1947.0,536.0,390.0,1078.0,4086.0,Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft.,64.0,32,True,2024-08-05 21:53:53.000,1.57.0,105.0,azureml-sdk,,,,,31.0,,https://pypi.org/project/azureml-sdk,2024-10-16 17:44:34.000,31.0,429158.0,429167.0,,,,,,,,2.0,656.0,,,,,,,,,,,,,,,,,,, +222,pytorch-forecasting,jdb78/pytorch-forecasting,time-series-data,,https://github.com/sktime/pytorch-forecasting,https://github.com/sktime/pytorch-forecasting,MIT,2020-07-03 13:05:24.000,2024-10-22 14:18:08.000000,2024-10-22 14:14:30,1908.0,117.0,620.0,42.0,908.0,477.0,307.0,3959.0,Time series forecasting with PyTorch.,54.0,32,True,2024-09-09 09:36:07.000,1.1.1,36.0,pytorch-forecasting,conda-forge/pytorch-forecasting,,,,466.0,444.0,https://pypi.org/project/pytorch-forecasting,2024-09-09 09:36:07.000,22.0,55505.0,56842.0,https://anaconda.org/conda-forge/pytorch-forecasting,2023-06-16 19:21:40.268,65539.0,,,,,2.0,,,,sktime/pytorch-forecasting,,,,,,,,,,,,,,,, +223,nevergrad,facebookresearch/nevergrad,hyperopt,,https://github.com/facebookresearch/nevergrad,https://github.com/facebookresearch/nevergrad,MIT,2018-11-21 00:33:17.000,2024-10-12 16:14:34.000000,2024-10-12 16:14:31,1115.0,18.0,352.0,58.0,1380.0,121.0,184.0,3953.0,A Python toolbox for performing gradient-free optimization.,57.0,32,True,2024-09-25 16:43:58.000,1.0.5,50.0,nevergrad,conda-forge/nevergrad,,,,821.0,763.0,https://pypi.org/project/nevergrad,2024-09-25 16:43:58.000,58.0,81313.0,82347.0,https://anaconda.org/conda-forge/nevergrad,2024-01-09 16:02:07.312,54837.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +224,ftfy,rspeer/python-ftfy,nlp,,https://github.com/rspeer/python-ftfy,https://github.com/rspeer/python-ftfy,,2012-08-24 16:14:59.000,2024-10-11 14:58:53.415000,2024-10-11 04:47:47,664.0,43.0,121.0,75.0,75.0,10.0,135.0,3796.0,"Fixes mojibake and other glitches in Unicode text, after the fact.",20.0,32,False,2024-10-11 04:54:40.000,6.3.0,54.0,ftfy,conda-forge/ftfy,,,,24214.0,23649.0,https://pypi.org/project/ftfy,2024-10-10 21:49:15.000,565.0,5383003.0,5389748.0,https://anaconda.org/conda-forge/ftfy,2024-10-11 14:58:53.415,303554.0,,,,,2.0,19.0,,,,,,,,,,,,,,,,,,, +225,STUMPY,TDAmeritrade/stumpy,time-series-data,,https://github.com/TDAmeritrade/stumpy,https://github.com/TDAmeritrade/stumpy,BSD-3-Clause,2019-05-03 19:23:44.000,2024-10-14 01:15:35.000000,2024-10-14 01:14:53,1356.0,9.0,317.0,59.0,244.0,66.0,449.0,3652.0,STUMPY is a powerful and scalable Python library for modern time series analysis.,41.0,32,True,2024-07-09 04:43:23.000,1.13.0,29.0,stumpy,conda-forge/stumpy,,,,940.0,910.0,https://pypi.org/project/stumpy,2024-07-09 04:21:56.000,30.0,258547.0,278356.0,https://anaconda.org/conda-forge/stumpy,2024-07-09 04:54:55.949,1030115.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +226,GPyTorch,cornellius-gp/gpytorch,probabilistics,,https://github.com/cornellius-gp/gpytorch,https://github.com/cornellius-gp/gpytorch,MIT,2017-06-09 14:48:20.000,2024-10-11 19:04:52.000000,2024-09-27 22:14:33,3900.0,19.0,553.0,58.0,915.0,366.0,980.0,3559.0,A highly efficient implementation of Gaussian Processes in PyTorch.,135.0,32,True,2024-09-06 21:42:56.000,1.13,41.0,gpytorch,conda-forge/gpytorch,,,['pytorch'],2587.0,2418.0,https://pypi.org/project/gpytorch,2024-09-06 21:48:53.000,169.0,287067.0,290461.0,https://anaconda.org/conda-forge/gpytorch,2024-09-07 18:14:18.267,179893.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +227,torchtext,pytorch/text,nlp,,https://github.com/pytorch/text,https://github.com/pytorch/text,BSD-3-Clause,2016-12-12 00:56:03.000,2024-10-24 11:34:52.000000,2024-08-14 20:32:21,1311.0,2.0,813.0,307.0,1470.0,331.0,518.0,3511.0,"Models, data loaders and abstractions for language processing, powered by PyTorch.",156.0,32,True,2024-04-24 16:20:45.000,0.18.0,34.0,torchtext,,,,['pytorch'],285.0,,https://pypi.org/project/torchtext,2024-04-24 15:49:45.000,285.0,1548276.0,1548276.0,,,,,,,,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 07:55:42.000,2024-10-09 16:24:11.000000,2024-10-09 16:24:08,1187.0,1.0,1661.0,154.0,210.0,13.0,693.0,3477.0,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'],303.0,,https://pypi.org/project/tensorflow-hub,2024-01-30 14:49:07.000,303.0,1889864.0,1891998.0,https://anaconda.org/conda-forge/tensorflow-hub,2024-05-07 05:39:07.350,106709.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +229,NMSLIB,nmslib/nmslib,nn-search,,https://github.com/nmslib/nmslib,https://github.com/nmslib/nmslib,Apache-2.0,2013-07-10 11:06:06.000,2024-09-21 03:01:04.000000,2024-09-21 03:01:04,1581.0,21.0,447.0,93.0,126.0,91.0,348.0,3400.0,Non-Metric Space Library (NMSLIB): An efficient similarity search library and a toolkit for evaluation of k-NN methods..,49.0,32,True,2021-02-03 16:40:09.000,2.1.1,32.0,nmslib,conda-forge/nmslib,,,,1289.0,1226.0,https://pypi.org/project/nmslib,2021-02-03 00:02:08.000,63.0,336812.0,339979.0,https://anaconda.org/conda-forge/nmslib,2024-09-09 06:18:10.925,152021.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +230,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,,277.0,48.0,828.0,102.0,285.0,3180.0,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'],6691.0,6538.0,https://pypi.org/project/fairscale,2022-12-11 18:09:31.906,153.0,466520.0,475534.0,https://anaconda.org/conda-forge/fairscale,2023-11-28 00:29:10.363,315518.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +231,lightly,lightly-ai/lightly,image,,https://github.com/lightly-ai/lightly,https://github.com/lightly-ai/lightly,MIT,2020-10-13 13:02:56.000,2024-10-24 07:36:45.000000,2024-10-24 07:36:45,1274.0,50.0,276.0,29.0,1135.0,72.0,505.0,3144.0,A python library for self-supervised learning on images.,56.0,32,True,2024-09-24 08:48:24.000,1.5.13,127.0,lightly,,,,['pytorch'],339.0,325.0,https://pypi.org/project/lightly,2024-09-24 08:50:32.000,14.0,33507.0,33507.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +232,NeuralForecast,Nixtla/neuralforecast,time-series-data,,https://github.com/Nixtla/neuralforecast,https://github.com/Nixtla/neuralforecast,Apache-2.0,2021-04-26 00:15:19.000,2024-10-22 13:26:10.000000,2024-10-22 13:26:09,1201.0,33.0,346.0,36.0,540.0,114.0,444.0,3032.0,Scalable and user friendly neural forecasting algorithms.,48.0,32,True,2024-09-20 17:38:31.000,1.7.5,26.0,neuralforecast,conda-forge/neuralforecast,,,,253.0,236.0,https://pypi.org/project/neuralforecast,2024-09-20 17:38:31.000,17.0,65685.0,66454.0,https://anaconda.org/conda-forge/neuralforecast,2024-09-20 23:37:40.226,23844.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +233,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 19:32:37.000,2024-10-02 13:16:06.886000,2024-10-01 21:19:30,966.0,9.0,393.0,39.0,151.0,46.0,248.0,2408.0,A library of sklearn compatible categorical variable encoders.,70.0,32,True,2024-10-01 21:24:24.000,2.6.4,33.0,category_encoders,conda-forge/category_encoders,,,['sklearn'],2520.0,2236.0,https://pypi.org/project/category_encoders,2024-10-01 21:24:24.000,284.0,1486496.0,1494436.0,https://anaconda.org/conda-forge/category_encoders,2024-10-02 13:16:06.886,285875.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +234,Lifelines,CamDavidsonPilon/lifelines,medical-data,,https://github.com/CamDavidsonPilon/lifelines,https://github.com/CamDavidsonPilon/lifelines,MIT,2013-08-28 00:16:42.000,2024-09-05 19:07:36.000000,2024-09-05 19:07:36,2302.0,2.0,551.0,70.0,486.0,260.0,711.0,2361.0,Survival analysis in Python.,119.0,32,True,2024-06-26 15:36:45.000,0.29.0,171.0,lifelines,conda-forge/lifelines,,,,3156.0,3006.0,https://pypi.org/project/lifelines,2024-06-26 15:36:45.000,150.0,1891452.0,1898512.0,https://anaconda.org/conda-forge/lifelines,2024-06-27 16:03:16.815,374218.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +235,pygraphistry,graphistry/pygraphistry,graph,,https://github.com/graphistry/pygraphistry,https://github.com/graphistry/pygraphistry,BSD-3-Clause,2015-06-02 20:28:42.000,2024-10-20 18:42:06.000000,2024-10-20 18:42:03,1811.0,254.0,205.0,51.0,284.0,174.0,163.0,2148.0,"PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated..",45.0,32,True,2024-10-20 17:58:26.000,0.34.17,194.0,graphistry,,,,['jupyter'],126.0,120.0,https://pypi.org/project/graphistry,2024-10-20 17:58:26.000,6.0,16433.0,16433.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +236,evaluate,huggingface/evaluate,interpretability,,https://github.com/huggingface/evaluate,https://github.com/huggingface/evaluate,Apache-2.0,2022-03-30 15:08:26.000,2024-09-17 00:19:55.000000,2024-09-17 00:19:55,953.0,9.0,254.0,47.0,349.0,210.0,141.0,2006.0,Evaluate: A library for easily evaluating machine learning models and datasets.,129.0,32,True,2024-09-11 10:17:30.000,0.4.3,16.0,evaluate,,,,,13821.0,13418.0,https://pypi.org/project/evaluate,2024-09-11 10:15:30.000,403.0,2392636.0,2392636.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,, +237,torchrec,pytorch/torchrec,recommender-systems,,https://github.com/pytorch/torchrec,https://github.com/pytorch/torchrec,BSD-3-Clause,2021-07-12 23:15:48.000,2024-10-24 11:34:59.000000,2024-10-23 20:27:31,2186.0,205.0,422.0,32.0,2340.0,304.0,119.0,1921.0,Pytorch domain library for recommendation systems.,280.0,32,True,2024-10-21 22:05:16.000,1.0.0-rc3,77.0,torchrec-nightly-cpu,,,,,146.0,146.0,https://pypi.org/project/torchrec-nightly-cpu,2022-05-12 18:55:21.000,,11938.0,11938.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,, +238,PyCUDA,inducer/pycuda,gpu-utilities,,https://github.com/inducer/pycuda,https://github.com/inducer/pycuda,MIT,2011-04-06 02:53:31.000,2024-10-17 01:51:01.000000,2024-10-17 01:50:57,1610.0,7.0,285.0,56.0,142.0,83.0,192.0,1841.0,"CUDA integration for Python, plus shiny features.",82.0,32,True,2024-07-30 16:38:24.000,2024.1.2,55.0,pycuda,conda-forge/pycuda,,,,3333.0,3176.0,https://pypi.org/project/pycuda,2024-07-30 13:53:42.000,157.0,108315.0,122320.0,https://anaconda.org/conda-forge/pycuda,2024-08-17 22:59:08.823,602216.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +239,Opacus,pytorch/opacus,privacy-ml,,https://github.com/pytorch/opacus,https://github.com/pytorch/opacus,Apache-2.0,2019-12-07 01:58:09.000,2024-10-19 04:07:54.000000,2024-10-19 04:01:42,732.0,12.0,332.0,46.0,386.0,72.0,236.0,1699.0,Training PyTorch models with differential privacy.,82.0,32,True,2024-08-03 10:32:52.000,1.5.2,24.0,opacus,conda-forge/opacus,,,['pytorch'],927.0,891.0,https://pypi.org/project/opacus,2024-08-03 10:32:52.000,36.0,264575.0,265120.0,https://anaconda.org/conda-forge/opacus,2024-08-05 12:31:17.057,17924.0,,,,,2.0,127.0,,,,,,,,,,,,,,,,,,, +240,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,,610.0,57.0,1884.0,90.0,899.0,1693.0,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'],363.0,,https://pypi.org/project/tensorflow-addons,2023-11-28 01:45:31.000,363.0,1156617.0,1156617.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +241,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,,284.0,51.0,158.0,114.0,218.0,1621.0,Python Geocoder.,73.0,32,False,2021-12-15 15:58:16.110,1.1.4,110.0,geocoder,conda-forge/geocoder,,,,11939.0,11727.0,https://pypi.org/project/geocoder,2021-12-15 15:58:16.110,212.0,848159.0,849811.0,https://anaconda.org/conda-forge/geocoder,2023-06-16 13:21:27.128,152073.0,,,,,3.0,,,,,,,,,,,,,,,,,,,,geocoder +242,lets-plot,JetBrains/lets-plot,data-viz,,https://github.com/JetBrains/lets-plot,https://github.com/JetBrains/lets-plot,MIT,2019-03-20 16:13:03.000,2024-10-24 00:13:25.000000,2024-10-24 00:13:22,4421.0,205.0,51.0,168.0,587.0,157.0,472.0,1561.0,Multiplatform plotting library based on the Grammar of Graphics.,21.0,32,True,2024-10-23 16:21:21.000,4.5.0,81.0,lets-plot,,,,,143.0,130.0,https://pypi.org/project/lets-plot,2024-10-23 15:55:24.000,13.0,57188.0,57209.0,,,,,,,,2.0,1276.0,,,,,,,,,,,,,,,,,,, +243,ipyleaflet,jupyter-widgets/ipyleaflet,geospatial-data,,https://github.com/jupyter-widgets/ipyleaflet,https://github.com/jupyter-widgets/ipyleaflet,MIT,2014-05-07 16:32:10.000,2024-10-21 08:31:36.000000,2024-10-21 08:31:36,1194.0,1.0,363.0,67.0,616.0,292.0,360.0,1486.0,A Jupyter - Leaflet.js bridge.,90.0,32,True,2024-07-22 08:02:59.000,0.19.2,84.0,ipyleaflet,conda-forge/ipyleaflet,,,['jupyter'],12107.0,11823.0,https://pypi.org/project/ipyleaflet,2024-07-22 08:02:59.000,275.0,232334.0,263974.0,https://anaconda.org/conda-forge/ipyleaflet,2024-07-22 12:26:50.743,1280513.0,,,,,3.0,,,,,jupyter-leaflet,https://www.npmjs.com/package/jupyter-leaflet,2024-07-22 08:02:28.803,9.0,7480.0,,,,,,,,,,, +244,hvPlot,holoviz/hvplot,data-viz,,https://github.com/holoviz/hvplot,https://github.com/holoviz/hvplot,BSD-3-Clause,2018-03-19 14:22:41.000,2024-10-21 07:47:33.000000,2024-10-16 15:26:11,727.0,31.0,108.0,25.0,585.0,360.0,456.0,1122.0,"A high-level plotting API for pandas, dask, xarray, and networkx built on HoloViews.",50.0,32,True,2024-10-17 08:19:52.000,0.11.1,78.0,hvplot,conda-forge/hvplot,,,,6179.0,5975.0,https://pypi.org/project/hvplot,2024-10-16 15:27:44.000,204.0,225866.0,238543.0,https://anaconda.org/conda-forge/hvplot,2024-10-17 10:29:45.764,659209.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +245,Satpy,pytroll/satpy,geospatial-data,,https://github.com/pytroll/satpy,https://github.com/pytroll/satpy,GPL-3.0,2016-02-09 20:29:43.000,2024-10-23 18:18:25.000000,2024-10-23 18:18:25,14162.0,282.0,293.0,34.0,1881.0,493.0,671.0,1064.0,Python package for earth-observing satellite data processing.,166.0,32,False,2024-10-23 10:48:06.000,0.52.1,98.0,satpy,conda-forge/satpy,,,,177.0,147.0,https://pypi.org/project/satpy,2024-10-23 10:48:06.000,30.0,12477.0,16841.0,https://anaconda.org/conda-forge/satpy,2024-10-23 14:08:22.801,226966.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +246,Hail,hail-is/hail,medical-data,,https://github.com/hail-is/hail,https://github.com/hail-is/hail,MIT,2015-10-27 20:55:42.000,2024-10-24 04:49:14.000000,2024-10-23 23:31:29,11594.0,57.0,243.0,56.0,12318.0,255.0,2216.0,976.0,Cloud-native genomic dataframes and batch computing.,97.0,32,True,2024-10-04 20:34:16.000,0.2.133,155.0,hail,,,,['spark'],180.0,146.0,https://pypi.org/project/hail,2024-10-04 20:34:16.000,34.0,48701.0,48701.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +247,DIPY,dipy/dipy,medical-data,,https://github.com/dipy/dipy,https://github.com/dipy/dipy,,2010-02-06 11:43:08.000,2024-10-22 14:40:52.000000,2024-10-22 14:40:52,14517.0,315.0,434.0,54.0,2234.0,191.0,806.0,712.0,"DIPY is the paragon 3D/4D+ imaging library in Python. Contains generic methods for spatial normalization, signal..",165.0,32,False,2024-03-08 22:14:36.000,1.9.0,28.0,dipy,conda-forge/dipy,,,,1381.0,1258.0,https://pypi.org/project/dipy,2024-03-08 22:14:36.000,123.0,46527.0,57075.0,https://anaconda.org/conda-forge/dipy,2024-03-10 04:37:57.447,516858.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +248,datalad,datalad/datalad,others,,https://github.com/datalad/datalad,https://github.com/datalad/datalad,MIT,2013-11-01 19:40:08.000,2024-10-14 20:17:57.000000,2024-10-14 20:03:04,17285.0,34.0,111.0,28.0,3618.0,528.0,3413.0,534.0,"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,,,,521.0,426.0,https://pypi.org/project/datalad,2024-08-08 02:59:23.000,95.0,49515.0,61816.0,https://anaconda.org/conda-forge/datalad,2024-08-08 08:36:45.951,639663.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +249,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,,2816.0,386.0,124.0,239.0,561.0,25791.0,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'],822.0,810.0,https://pypi.org/project/spleeter,2022-06-10 13:19:35.000,12.0,22548.0,82187.0,https://anaconda.org/conda-forge/spleeter,2023-06-16 16:18:57.741,94741.0,,,,,2.0,3482048.0,,,,,,,,,,,,,,,,,,, +250,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 02:26:04,1422.0,1.0,3735.0,753.0,1140.0,413.0,589.0,19145.0,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'],540.0,535.0,https://pypi.org/project/magenta,2022-08-01 18:23:00.243,5.0,8100.0,8100.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +251,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,,1807.0,284.0,3507.0,417.0,1684.0,14026.0,"An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural..",192.0,31,True,2023-09-14 12:12:06.000,3.0,55.0,nni,,,,,68.0,21.0,https://pypi.org/project/nni,2023-09-14 12:22:00.000,47.0,18301.0,18301.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +252,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 03:17:23,2667.0,2.0,2074.0,182.0,1006.0,574.0,727.0,12708.0,"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'],1749.0,1742.0,https://pypi.org/project/paddlehub,2023-09-20 10:33:08.000,7.0,6203.0,6214.0,,,,,,,,2.0,801.0,,,,,,,,,,,,,,,,,,, +253,FinRL,AI4Finance-Foundation/FinRL,reinforcement-learning,,https://github.com/AI4Finance-Foundation/FinRL,https://github.com/AI4Finance-Foundation/FinRL,MIT,2020-07-26 13:18:16.000,2024-10-15 06:53:13.000000,2024-10-15 06:53:10,2964.0,11.0,2396.0,202.0,473.0,246.0,476.0,9973.0,FinRL: Financial Reinforcement Learning.,117.0,31,True,2023-02-07 13:58:00.815,0.3.6,8.0,finrl,,,,,51.0,51.0,https://pypi.org/project/finrl,2022-01-08 13:58:14.000,,2107.0,2107.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,, +254,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,,1569.0,288.0,434.0,295.0,639.0,9720.0,A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.,121.0,31,False,2024-02-23 19:06:10.000,0.12.2,63.0,tpot,conda-forge/tpot,,,['sklearn'],3072.0,3034.0,https://pypi.org/project/tpot,2024-02-23 19:06:10.000,38.0,47732.0,52982.0,https://anaconda.org/conda-forge/tpot,2024-02-26 15:57:08.680,273011.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +255,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,,2410.0,456.0,261.0,577.0,364.0,9617.0,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'],5043.0,5029.0,https://pypi.org/project/tflearn,2020-11-11 19:13:47.000,14.0,4660.0,4660.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +256,cleanlab,cleanlab/cleanlab,others,,https://github.com/cleanlab/cleanlab,https://github.com/cleanlab/cleanlab,AGPL-3.0,2018-05-11 01:55:21.000,2024-10-23 14:54:18.000000,2024-10-23 14:54:18,1743.0,26.0,729.0,90.0,802.0,112.0,271.0,9615.0,"The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.",52.0,31,False,2024-09-26 16:50:26.000,2.7.0,32.0,cleanlab,conda-forge/cleanlab,,,,412.0,394.0,https://pypi.org/project/cleanlab,2024-09-26 16:50:26.000,18.0,25994.0,26735.0,https://anaconda.org/conda-forge/cleanlab,2024-06-26 17:29:18.404,31162.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +257,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,,876.0,258.0,148.0,107.0,104.0,9224.0,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,,,,1211.0,21.0,https://pypi.org/project/fuzzywuzzy,2020-02-13 21:06:25.000,1190.0,7406936.0,7412630.0,https://anaconda.org/conda-forge/fuzzywuzzy,2023-06-16 13:22:53.603,563752.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +258,AutoKeras,keras-team/autokeras,hyperopt,,https://github.com/keras-team/autokeras,https://github.com/keras-team/autokeras,Apache-2.0,2017-11-19 23:18:20.000,2024-10-17 18:06:07.000000,2024-10-17 18:06:07,1392.0,1.0,1399.0,301.0,895.0,143.0,759.0,9136.0,AutoML library for deep learning.,144.0,31,True,2024-03-20 21:40:33.000,2.0.0,59.0,autokeras,,,,['tensorflow'],759.0,746.0,https://pypi.org/project/autokeras,2024-03-20 21:40:33.000,13.0,30031.0,30259.0,,,,,,,,2.0,18941.0,,,,,,,,,,,,,,,,,,, +259,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,,2157.0,290.0,98.0,311.0,446.0,8608.0,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,,,,1704.0,1685.0,https://pypi.org/project/imageai,2023-01-02 17:10:24.749,19.0,10463.0,22713.0,https://anaconda.org/conda-forge/imageai,2023-06-16 19:21:01.568,8070.0,,,,,2.0,943194.0,,,,,,,,,,,,,,,,,,, +260,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 20:47:58,560.0,2.0,1206.0,170.0,436.0,68.0,474.0,8416.0,Automatic extraction of relevant features from time series:.,97.0,31,True,2024-08-03 20:51:43.000,0.20.3,32.0,tsfresh,conda-forge/tsfresh,,,['sklearn'],114.0,21.0,https://pypi.org/project/tsfresh,2024-08-03 20:51:43.000,93.0,236974.0,263309.0,https://anaconda.org/conda-forge/tsfresh,2024-08-04 02:13:02.666,1395773.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +261,Darts,unit8co/darts,time-series-data,,https://github.com/unit8co/darts,https://github.com/unit8co/darts,Apache-2.0,2018-09-13 15:17:28.000,2024-10-15 15:56:12.000000,2024-10-13 12:15:09,1247.0,20.0,869.0,60.0,1021.0,244.0,1323.0,8017.0,A python library for user-friendly forecasting and anomaly detection on time series.,125.0,31,True,2024-10-13 12:29:02.000,0.31.0,44.0,u8darts,conda-forge/u8darts-all,unit8/darts,,,10.0,,https://pypi.org/project/u8darts,2024-10-13 12:29:02.000,10.0,67117.0,68665.0,https://anaconda.org/conda-forge/u8darts-all,2024-10-13 21:33:50.942,59991.0,https://hub.docker.com/r/unit8/darts,2024-04-17 11:31:17.149896,,787.0,2.0,,,,,,,,,,,,,,,,,,,, +262,auto-sklearn,automl/auto-sklearn,hyperopt,,https://github.com/automl/auto-sklearn,https://github.com/automl/auto-sklearn,BSD-3-Clause,2015-07-02 15:38:10.000,2024-10-24 14:24:25.000000,2023-04-18 11:08:13,2759.0,,1269.0,215.0,722.0,196.0,829.0,7604.0,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'],648.0,614.0,https://pypi.org/project/auto-sklearn,2022-09-20 10:32:07.471,34.0,22292.0,22915.0,https://anaconda.org/conda-forge/auto-sklearn,2023-06-16 19:25:30.278,26178.0,,,,,2.0,62.0,,,,,,,,,,,,,,,,,,, +263,DeepPavlov,deepmipt/DeepPavlov,nlp,,https://github.com/deeppavlov/DeepPavlov,https://github.com/deeppavlov/DeepPavlov,Apache-2.0,2017-11-17 14:35:29.000,2024-10-22 21:21:38.000000,2024-08-12 17:08:04,2710.0,2.0,1140.0,210.0,1051.0,25.0,615.0,6705.0,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'],418.0,414.0,https://pypi.org/project/deeppavlov,2024-08-12 17:22:54.000,4.0,14738.0,14738.0,,,,,,,,2.0,,,,deeppavlov/DeepPavlov,,,,,,,,,,,,,,,, +264,skorch,skorch-dev/skorch,ml-frameworks,,https://github.com/skorch-dev/skorch,https://github.com/skorch-dev/skorch,BSD-3-Clause,2017-07-18 00:13:54.000,2024-10-18 16:49:16.000000,2024-09-20 10:02:01,1094.0,3.0,386.0,81.0,540.0,62.0,458.0,5860.0,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']",1504.0,1419.0,https://pypi.org/project/skorch,2024-05-27 15:23:17.000,85.0,152446.0,168517.0,https://anaconda.org/conda-forge/skorch,2024-05-30 08:55:05.943,787506.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +265,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,,1760.0,302.0,296.0,161.0,267.0,5676.0,Portfolio and risk analytics in Python.,60.0,31,False,2019-04-15 15:00:21.000,0.9.2,22.0,pyfolio,conda-forge/pyfolio,,,,1096.0,1082.0,https://pypi.org/project/pyfolio,2019-04-15 15:00:21.000,14.0,8102.0,8277.0,https://anaconda.org/conda-forge/pyfolio,2023-06-16 16:07:59.111,14030.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +266,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,,910.0,125.0,38.0,74.0,147.0,5540.0,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'],4056.0,3956.0,https://pypi.org/project/torchdiffeq,2024-05-29 15:01:39.000,100.0,861793.0,862132.0,https://anaconda.org/conda-forge/torchdiffeq,2023-06-16 19:19:05.182,17997.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +267,causalml,uber/causalml,others,,https://github.com/uber/causalml,https://github.com/uber/causalml,Apache-2.0,2019-07-09 02:08:58.000,2024-10-16 13:17:50.000000,2024-10-16 13:17:49,626.0,10.0,776.0,85.0,354.0,54.0,346.0,5052.0,Uplift modeling and causal inference with machine learning algorithms.,64.0,31,True,2024-10-01 06:25:01.000,0.15.2,25.0,causalml,,,,,229.0,227.0,https://pypi.org/project/causalml,2024-10-01 06:25:01.000,2.0,60318.0,60318.0,,,,,,,,2.0,,2.0,,,,,,,,,,,,,,,,,, +268,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,,1026.0,152.0,116.0,162.0,79.0,4534.0,"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,,,,47097.0,46662.0,https://pypi.org/project/imutils,2021-01-15 10:53:17.000,435.0,459712.0,463541.0,https://anaconda.org/conda-forge/imutils,2023-10-27 09:12:56.985,195300.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +269,cuML,rapidsai/cuml,gpu-utilities,,https://github.com/rapidsai/cuml,https://github.com/rapidsai/cuml,Apache-2.0,2018-10-11 15:45:35.000,2024-10-24 12:56:18.000000,2024-10-17 23:50:48,15558.0,76.0,527.0,74.0,3639.0,914.0,1615.0,4203.0,cuML - RAPIDS Machine Learning Library.,178.0,31,True,2024-10-09 20:29:23.000,24.10.00,42.0,cuml,,,,,14.0,,https://pypi.org/project/cuml,2020-06-01 20:09:10.000,14.0,3182.0,3182.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +270,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,,704.0,184.0,737.0,277.0,669.0,3423.0,DyNet: The Dynamic Neural Network Toolkit.,160.0,31,True,2020-10-21 14:31:01.000,2.1.2,24.0,dyNET,,,,,282.0,264.0,https://pypi.org/project/dyNET,2020-10-21 14:31:01.000,18.0,309167.0,309347.0,,,,,,,,3.0,17295.0,,,,,,,,,,,,,,,,,,, +271,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,,621.0,77.0,79.0,73.0,162.0,3333.0,"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,,,,7409.0,7289.0,https://pypi.org/project/filterpy,2021-12-15 15:49:27.374,120.0,2195615.0,2198566.0,https://anaconda.org/conda-forge/filterpy,2023-06-16 13:24:39.196,259736.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +272,ImageHash,JohannesBuchner/imagehash,image,,https://github.com/JohannesBuchner/imagehash,https://github.com/JohannesBuchner/imagehash,BSD-2-Clause,2013-03-02 23:32:48.000,2024-10-09 08:38:40.000000,2024-10-09 08:38:39,344.0,5.0,329.0,65.0,77.0,20.0,123.0,3157.0,A Python Perceptual Image Hashing Module.,27.0,31,True,2022-09-28 08:48:24.658,4.3.1,20.0,ImageHash,conda-forge/imagehash,,,,14826.0,14584.0,https://pypi.org/project/ImageHash,2022-09-28 08:48:24.658,242.0,1559203.0,1563423.0,https://anaconda.org/conda-forge/imagehash,2023-06-16 13:23:10.041,400933.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +273,hmmlearn,hmmlearn/hmmlearn,probabilistics,,https://github.com/hmmlearn/hmmlearn,https://github.com/hmmlearn/hmmlearn,BSD-3-Clause,2014-03-23 10:33:09.000,2024-10-07 08:34:51.000000,2024-10-07 08:34:51,479.0,3.0,737.0,121.0,130.0,69.0,373.0,3055.0,"Hidden Markov Models in Python, with scikit-learn like API.",49.0,31,True,2024-03-02 03:05:38.000,0.3.2,13.0,hmmlearn,conda-forge/hmmlearn,,,['sklearn'],2932.0,2845.0,https://pypi.org/project/hmmlearn,2024-03-02 03:05:38.000,87.0,673589.0,679477.0,https://anaconda.org/conda-forge/hmmlearn,2024-09-11 23:07:53.942,288551.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +274,Determined,determined-ai/determined,ml-frameworks,,https://github.com/determined-ai/determined,https://github.com/determined-ai/determined,Apache-2.0,2020-04-07 16:12:29.000,2024-10-24 14:12:23.000000,2024-10-24 14:12:22,8309.0,289.0,347.0,84.0,9720.0,108.0,348.0,3024.0,"Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning,..",121.0,31,True,2024-09-30 15:28:11.000,0.37.0,589.0,determined,,,https://docs.determined.ai,"['pytorch', 'tensorflow']",4.0,,https://pypi.org/project/determined,2024-09-30 15:49:23.000,4.0,54966.0,55208.0,,,,,,,,3.0,11622.0,,,,,,,,,,,,,,,,,,, +275,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,,336.0,59.0,194.0,135.0,196.0,2900.0,The machine learning toolkit for time series analysis in Python.,43.0,31,True,2023-12-12 14:39:23.000,0.6.3,100.0,tslearn,conda-forge/tslearn,,,['sklearn'],1542.0,1463.0,https://pypi.org/project/tslearn,2023-12-12 14:39:23.000,79.0,427235.0,454758.0,https://anaconda.org/conda-forge/tslearn,2024-07-26 07:25:11.554,1431199.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +276,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 07:14:02.000,2024-10-24 14:13:34.000000,2024-10-24 07:22:43,991.0,9.0,233.0,37.0,551.0,75.0,175.0,2887.0,JAX-based neural network library.,83.0,31,True,2024-10-16 09:11:35.000,0.0.13,16.0,dm-haiku,conda-forge/dm-haiku,,,,2287.0,2112.0,https://pypi.org/project/dm-haiku,2024-10-16 09:11:35.000,175.0,247017.0,247541.0,https://anaconda.org/conda-forge/dm-haiku,2024-10-23 19:46:21.263,23067.0,,,,,3.0,,,,google-deepmind/dm-haiku,,,,,,,,,,,,,,,, +277,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,,392.0,63.0,497.0,218.0,273.0,2857.0,A Hyperparameter Tuning Library for Keras.,61.0,31,True,2024-03-04 19:41:39.000,1.4.7,35.0,keras-tuner,conda-forge/keras-tuner,,,['tensorflow'],4630.0,4515.0,https://pypi.org/project/keras-tuner,2024-03-04 19:41:39.000,115.0,242896.0,243978.0,https://anaconda.org/conda-forge/keras-tuner,2024-03-05 15:33:09.039,41149.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +278,shapash,MAIF/shapash,interpretability,,https://github.com/MAIF/shapash,https://github.com/MAIF/shapash,Apache-2.0,2020-04-29 07:34:23.000,2024-10-24 09:49:13.000000,2024-10-24 09:29:18,1680.0,49.0,331.0,38.0,362.0,38.0,181.0,2729.0,Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models.,40.0,31,True,2024-10-24 09:49:13.000,2.7.3,46.0,shapash,,,,['jupyter'],180.0,176.0,https://pypi.org/project/shapash,2024-10-24 09:49:13.000,4.0,39439.0,39439.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +279,bt,pmorissette/bt,financial-data,,https://github.com/pmorissette/bt,https://github.com/pmorissette/bt,MIT,2014-06-19 16:06:28.000,2024-10-01 15:28:33.000000,2024-10-01 15:28:28,557.0,14.0,428.0,90.0,117.0,76.0,265.0,2255.0,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,,,,1636.0,1626.0,https://pypi.org/project/bt,2024-08-06 00:08:14.000,10.0,12815.0,13950.0,https://anaconda.org/conda-forge/bt,2024-09-21 21:55:35.462,47709.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +280,equinox,patrick-kidger/equinox,jax-utils,,https://github.com/patrick-kidger/equinox,https://github.com/patrick-kidger/equinox,Apache-2.0,2021-07-29 02:21:39.000,2024-10-18 17:19:32.000000,2024-10-18 17:08:47,954.0,36.0,138.0,24.0,439.0,156.0,296.0,2089.0,Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/.,56.0,31,True,2024-10-18 17:19:32.000,0.11.8,52.0,equinox,,,,['jax'],955.0,789.0,https://pypi.org/project/equinox,2024-10-18 17:19:32.000,166.0,249678.0,249678.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,, +281,audiomentations,iver56/audiomentations,audio,,https://github.com/iver56/audiomentations,https://github.com/iver56/audiomentations,MIT,2019-02-12 16:36:24.000,2024-10-07 10:29:52.000000,2024-10-07 10:29:49,1258.0,58.0,186.0,21.0,177.0,47.0,137.0,1852.0,A Python library for audio data augmentation. Inspired by albumentations. Useful for machine learning.,29.0,31,True,2024-09-03 07:35:15.000,0.37.0,41.0,audiomentations,,,,,606.0,588.0,https://pypi.org/project/audiomentations,2024-09-03 07:35:15.000,18.0,51935.0,51935.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +282,PyKEEN,pykeen/pykeen,graph,,https://github.com/pykeen/pykeen,https://github.com/pykeen/pykeen,MIT,2020-02-24 07:26:03.000,2024-10-24 14:25:52.000000,2024-10-23 10:24:39,2880.0,46.0,184.0,27.0,721.0,118.0,458.0,1649.0,A Python library for learning and evaluating knowledge graph embeddings.,41.0,31,True,2024-02-19 21:29:27.000,1.10.2,47.0,pykeen,,,,,252.0,246.0,https://pypi.org/project/pykeen,2024-02-19 21:25:43.000,6.0,10984.0,10988.0,,,,,,,,2.0,214.0,,,,,,,,,,,,,,,,,,, +283,pmdarima,alkaline-ml/pmdarima,time-series-data,,https://github.com/alkaline-ml/pmdarima,https://github.com/alkaline-ml/pmdarima,MIT,2017-03-30 14:58:30.000,2024-09-25 17:37:58.000000,2024-09-24 16:10:31,1080.0,1.0,234.0,36.0,255.0,62.0,274.0,1582.0,"A statistical library designed to fill the void in Pythons time series analysis capabilities, including the equivalent..",23.0,31,True,2023-10-23 16:52:00.000,2.0.4,44.0,pmdarima,conda-forge/pmdarima,,,,9706.0,9553.0,https://pypi.org/project/pmdarima,2023-10-23 14:02:41.000,153.0,2543896.0,2568725.0,https://anaconda.org/conda-forge/pmdarima,2024-07-14 16:03:51.778,1191799.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +284,emcee,dfm/emcee,probabilistics,,https://github.com/dfm/emcee,https://github.com/dfm/emcee,MIT,2011-11-07 16:17:08.000,2024-10-10 00:53:03.000000,2024-10-10 00:53:03,951.0,3.0,431.0,85.0,234.0,57.0,242.0,1463.0,The Python ensemble sampling toolkit for affine-invariant MCMC.,74.0,31,True,2024-04-19 10:03:17.000,3.1.6,27.0,emcee,conda-forge/emcee,,,,3080.0,2642.0,https://pypi.org/project/emcee,2024-04-19 10:03:17.000,438.0,1265612.0,1274722.0,https://anaconda.org/conda-forge/emcee,2024-04-22 14:43:59.507,364404.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +285,pyjanitor,pyjanitor-devs/pyjanitor,others,,https://github.com/pyjanitor-devs/pyjanitor,https://github.com/pyjanitor-devs/pyjanitor,MIT,2018-03-04 22:43:33.000,2024-10-21 20:12:33.000000,2024-10-20 18:26:50,1613.0,33.0,169.0,18.0,845.0,110.0,455.0,1353.0,Clean APIs for data cleaning. Python implementation of R package Janitor.,109.0,31,True,2024-09-28 19:45:17.000,0.29.2,65.0,pyjanitor,conda-forge/pyjanitor,,,,765.0,733.0,https://pypi.org/project/pyjanitor,2024-09-28 19:45:12.000,32.0,88546.0,92616.0,https://anaconda.org/conda-forge/pyjanitor,2024-09-28 23:43:58.175,215721.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +286,arch,bashtage/arch,financial-data,,https://github.com/bashtage/arch,https://github.com/bashtage/arch,,2014-08-29 15:41:28.000,2024-10-22 08:24:56.000000,2024-10-22 08:21:54,1141.0,9.0,248.0,48.0,538.0,31.0,185.0,1334.0,ARCH models in Python.,35.0,31,False,2024-09-24 09:58:38.000,7.1.0,48.0,arch,conda-forge/arch-py,,,,2129.0,2020.0,https://pypi.org/project/arch,2024-09-24 09:58:38.000,109.0,472048.0,480063.0,https://anaconda.org/conda-forge/arch-py,2024-09-24 16:15:26.723,416795.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +287,PySAL,pysal/pysal,geospatial-data,,https://github.com/pysal/pysal,https://github.com/pysal/pysal,BSD-3-Clause,2013-02-19 17:27:42.000,2024-10-07 15:49:46.000000,2024-10-07 15:49:42,4366.0,14.0,303.0,79.0,671.0,17.0,634.0,1323.0,PySAL: Python Spatial Analysis Library Meta-Package.,79.0,31,True,2024-07-30 17:42:50.000,24.07,41.0,pysal,conda-forge/pysal,,,,1724.0,1675.0,https://pypi.org/project/pysal,2024-07-30 17:42:53.000,49.0,45888.0,57292.0,https://anaconda.org/conda-forge/pysal,2024-07-30 21:31:48.610,581621.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +288,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 22:15:53.000,2024-10-18 06:37:03.000000,2024-10-18 06:36:56,1147.0,14.0,211.0,23.0,153.0,25.0,200.0,1128.0,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'],651.0,618.0,https://pypi.org/project/scikit-survival,2024-06-30 09:36:26.000,33.0,145939.0,150351.0,https://anaconda.org/conda-forge/scikit-survival,2024-06-30 11:16:56.800,154426.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +289,pyopencl,inducer/pyopencl,others,,https://github.com/inducer/pyopencl,https://github.com/inducer/pyopencl,MIT,2011-04-06 02:51:33.000,2024-10-22 02:56:13.460000,2024-10-18 18:58:53,3385.0,20.0,242.0,50.0,412.0,76.0,279.0,1063.0,"OpenCL integration for Python, plus shiny features.",96.0,31,True,2024-10-18 17:14:33.000,2024.3,103.0,pyopencl,conda-forge/pyopencl,,,,2230.0,2056.0,https://pypi.org/project/pyopencl,2024-10-18 17:25:30.000,174.0,98156.0,123636.0,https://anaconda.org/conda-forge/pyopencl,2024-10-22 02:56:13.460,1325004.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +290,SALib,SALib/SALib,probabilistics,,https://github.com/SALib/SALib,https://github.com/SALib/SALib,MIT,2013-05-30 13:38:10.000,2024-10-10 16:48:51.000000,2024-10-10 16:48:51,1966.0,11.0,234.0,18.0,301.0,53.0,285.0,877.0,"Sensitivity Analysis Library in Python. Contains Sobol, Morris, FAST, and other methods.",48.0,31,True,2024-08-19 16:35:23.000,1.5.1,49.0,salib,conda-forge/salib,,,,1414.0,1287.0,https://pypi.org/project/salib,2024-08-19 16:35:23.000,127.0,320353.0,324238.0,https://anaconda.org/conda-forge/salib,2024-09-20 11:56:36.472,186486.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +291,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 21:24:50.000,2024-10-24 11:11:25.000000,2024-10-18 19:54:10,175445.0,3383.0,94.0,50.0,2349.0,92.0,286.0,685.0,TensorFlow ROCm port.,4727.0,31,True,2022-12-06 16:42:53.965,2.9.4,100.0,tensorflow-rocm,,,,['tensorflow'],9.0,,https://pypi.org/project/tensorflow-rocm,2024-01-10 14:33:03.000,9.0,7449.0,7449.0,,,,,,,,3.0,25.0,,,ROCm/tensorflow-upstream,,,,,,,,,,,,,,,, +292,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,,4286.0,1249.0,557.0,840.0,2543.0,17515.0,"Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit.",274.0,30,False,2019-04-26 14:13:32.000,2.7,32.0,cntk,,,,,5.0,2.0,https://pypi.org/project/cntk,2020-12-09 22:21:57.000,3.0,2454.0,2594.0,,,,,,,,3.0,14719.0,,,,,,,,,,,,,,,,,,, +293,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,,4867.0,647.0,375.0,504.0,436.0,15753.0,OpenAI Baselines: high-quality implementations of reinforcement learning algorithms.,115.0,30,False,2018-02-26 17:07:07.000,0.1.5,6.0,baselines,,,,,588.0,585.0,https://pypi.org/project/baselines,2018-02-26 17:07:07.000,3.0,2308.0,2308.0,,,,,,,,1.0,,,,,,,,,,,,,,,,,,,, +294,Qlib,microsoft/qlib,financial-data,,https://github.com/microsoft/qlib,https://github.com/microsoft/qlib,MIT,2020-08-14 06:46:00.000,2024-09-12 15:44:41.000000,2024-09-12 15:44:27,1995.0,5.0,2585.0,298.0,940.0,238.0,690.0,15393.0,"Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and..",134.0,30,True,2024-05-24 08:18:55.000,0.9.5,34.0,pyqlib,,,,['pytorch'],22.0,21.0,https://pypi.org/project/pyqlib,2024-05-24 08:18:55.000,1.0,7685.0,7699.0,,,,,,,,2.0,727.0,,,,,,,,,,,,,,,,,,, +295,Apex,NVIDIA/apex,gpu-utilities,,https://github.com/NVIDIA/apex,https://github.com/NVIDIA/apex,BSD-3-Clause,2018-04-23 16:28:52.000,2024-10-17 04:06:27.000000,2024-10-17 04:06:27,1187.0,8.0,1387.0,100.0,659.0,729.0,527.0,8372.0,A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch.,129.0,30,True,,,4.0,,conda-forge/nvidia-apex,,,['pytorch'],2770.0,2770.0,,,,,6993.0,https://anaconda.org/conda-forge/nvidia-apex,2024-09-10 09:10:05.964,335681.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +296,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,,1029.0,110.0,250.0,114.0,480.0,5326.0,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'],4391.0,4271.0,https://pypi.org/project/pandas-ta,2021-07-28 20:51:17.000,120.0,172370.0,172984.0,https://anaconda.org/conda-forge/pandas-ta,2023-06-16 19:27:34.124,22131.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +297,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 09:34:48.000,2024-10-24 13:21:24.000000,2024-09-10 14:13:20,813.0,8.0,402.0,75.0,298.0,60.0,529.0,4753.0,Visualizer for pandas data structures.,30.0,30,True,2024-09-10 15:24:26.000,3.14.1,186.0,dtale,conda-forge/dtale,,,"['pandas', 'jupyter']",1281.0,1237.0,https://pypi.org/project/dtale,2024-09-10 15:17:39.000,44.0,123177.0,129644.0,https://anaconda.org/conda-forge/dtale,2024-09-10 15:55:41.876,342795.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +298,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,,280.0,44.0,51.0,28.0,97.0,4053.0,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,,,,6285.0,6135.0,https://pypi.org/project/gpustat,2023-08-22 19:39:06.000,150.0,2132153.0,2138404.0,https://anaconda.org/conda-forge/gpustat,2023-08-23 10:35:25.821,293831.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +299,anomalib,openvinotoolkit/anomalib,others,,https://github.com/openvinotoolkit/anomalib,https://github.com/openvinotoolkit/anomalib,Apache-2.0,2021-11-02 09:11:38.000,2024-10-24 14:12:16.000000,2024-10-24 14:12:15,698.0,40.0,660.0,38.0,989.0,147.0,790.0,3754.0,"An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-..",81.0,30,True,2024-08-12 12:57:29.000,1.1.1,32.0,anomalib,,,,,108.0,103.0,https://pypi.org/project/anomalib,2024-08-12 12:57:52.000,5.0,67769.0,68196.0,,,,,,,,2.0,14531.0,,,,,,,,,,,,,,,,,,, +300,Porcupine,Picovoice/Porcupine,audio,,https://github.com/Picovoice/porcupine,https://github.com/Picovoice/porcupine,Apache-2.0,2018-03-08 01:55:25.000,2024-10-24 00:50:17.000000,2024-10-22 23:18:27,1239.0,19.0,496.0,65.0,761.0,3.0,551.0,3744.0,On-device wake word detection powered by deep learning.,39.0,30,True,2024-08-27 00:05:29.000,3.0.3,35.0,pvporcupine,,,,,69.0,34.0,https://pypi.org/project/pvporcupine,2024-08-27 00:05:29.000,35.0,12508.0,12508.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +301,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,,605.0,76.0,231.0,89.0,406.0,3545.0,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,,,,1542.0,1513.0,https://pypi.org/project/implicit,2023-09-29 21:07:11.000,29.0,255533.0,273854.0,https://anaconda.org/conda-forge/implicit,2024-08-23 13:53:47.619,895594.0,,,,,2.0,1475.0,,,,,,,,,,,,,,,,,,, +302,TextDistance,life4/textdistance,nlp,,https://github.com/life4/textdistance,https://github.com/life4/textdistance,MIT,2017-05-05 08:46:10.000,2024-09-09 06:24:01.000000,2024-09-09 06:24:01,415.0,6.0,248.0,64.0,56.0,9.0,,3376.0,"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,,,,7319.0,7220.0,https://pypi.org/project/textdistance,2024-07-16 09:34:51.000,99.0,877214.0,890988.0,https://anaconda.org/conda-forge/textdistance,2024-07-17 15:04:16.210,646849.0,,,,,2.0,1037.0,,,,,,,,,,,,,,,,,,, +303,mljar-supervised,mljar/mljar-supervised,hyperopt,,https://github.com/mljar/mljar-supervised,https://github.com/mljar/mljar-supervised,MIT,2018-11-05 12:58:04.000,2024-10-14 11:19:45.000000,2024-10-14 11:19:45,1218.0,33.0,404.0,50.0,94.0,140.0,521.0,3040.0,"Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and..",29.0,30,True,2024-10-09 07:20:59.000,1.1.12,95.0,mljar-supervised,conda-forge/mljar-supervised,,,,135.0,131.0,https://pypi.org/project/mljar-supervised,2024-10-09 07:10:53.000,4.0,8971.0,9550.0,https://anaconda.org/conda-forge/mljar-supervised,2024-09-10 16:42:21.786,23174.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +304,USearch,unum-cloud/usearch,nn-search,,https://github.com/unum-cloud/usearch,https://github.com/unum-cloud/usearch,Apache-2.0,2023-02-22 09:20:20.000,2024-10-22 13:53:13.000000,2024-10-10 04:10:55,1896.0,144.0,130.0,28.0,357.0,54.0,107.0,2185.0,"Fast Open-Source Search & Clustering engine for Vectors & Strings in C++, C, Python, JavaScript, Rust, Java,..",54.0,30,True,2024-10-10 05:09:50.000,2.15.3,125.0,usearch,,unum/usearch,,,162.0,127.0,https://pypi.org/project/usearch,2024-10-10 05:09:50.000,21.0,197923.0,207079.0,,,,https://hub.docker.com/r/unum/usearch,2024-10-10 04:15:31.133870,1.0,131.0,3.0,29410.0,,,,usearch,https://www.npmjs.com/package/usearch,2024-10-10 04:16:54.769,14.0,7312.0,,,,,,,,,,, +305,tesserocr,sirfz/tesserocr,ocr,,https://github.com/sirfz/tesserocr,https://github.com/sirfz/tesserocr,MIT,2015-12-17 23:29:36.000,2024-09-13 13:36:57.070000,2024-08-26 17:26:56,210.0,1.0,254.0,56.0,78.0,51.0,229.0,2009.0,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,,,,1137.0,1101.0,https://pypi.org/project/tesserocr,2024-08-26 20:21:57.000,36.0,107195.0,110874.0,https://anaconda.org/conda-forge/tesserocr,2024-09-13 13:36:57.070,187334.0,,,,,2.0,602.0,,,,,,,,,,,,,,,,,,, +306,GPflow,GPflow/GPflow,probabilistics,,https://github.com/GPflow/GPflow,https://github.com/GPflow/GPflow,Apache-2.0,2016-01-14 11:29:24.000,2024-10-14 11:41:15.000000,2024-10-04 09:56:03,2451.0,1.0,435.0,76.0,1271.0,154.0,682.0,1846.0,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'],729.0,694.0,https://pypi.org/project/gpflow,2024-06-17 13:05:05.000,35.0,72875.0,73968.0,https://anaconda.org/conda-forge/gpflow,2024-06-26 16:24:01.852,34990.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +307,ViZDoom,mwydmuch/ViZDoom,reinforcement-learning,,https://github.com/Farama-Foundation/ViZDoom,https://github.com/Farama-Foundation/ViZDoom,MIT,2015-06-26 18:38:23.000,2024-09-08 19:48:30.000000,2024-09-08 00:19:34,1851.0,42.0,381.0,50.0,136.0,29.0,435.0,1732.0,Reinforcement Learning environments based on the 1993 game Doom.,55.0,30,True,2024-08-20 10:48:59.000,1.2.4,30.0,vizdoom,,,,,290.0,275.0,https://pypi.org/project/vizdoom,2024-08-20 10:48:59.000,15.0,6344.0,6461.0,,,,,,,,1.0,12078.0,,,Farama-Foundation/ViZDoom,,,,,,,,,,,,,,,, +308,pingouin,raphaelvallat/pingouin,probabilistics,,https://github.com/raphaelvallat/pingouin,https://github.com/raphaelvallat/pingouin,GPL-3.0,2018-04-01 01:10:22.000,2024-10-17 05:15:24.000000,2024-10-17 05:15:24,1257.0,5.0,138.0,32.0,121.0,35.0,268.0,1619.0,Statistical package in Python based on Pandas.,48.0,30,False,2024-09-04 10:48:32.000,0.5.5,41.0,pingouin,conda-forge/pingouin,,,,2616.0,2460.0,https://pypi.org/project/pingouin,2024-09-04 10:42:50.000,156.0,158825.0,161468.0,https://anaconda.org/conda-forge/pingouin,2024-09-04 22:25:36.166,137473.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +309,Geomstats,geomstats/geomstats,ml-frameworks,,https://github.com/geomstats/geomstats,https://github.com/geomstats/geomstats,MIT,2017-10-25 00:44:57.000,2024-10-08 19:34:40.000000,2024-10-08 19:34:40,10790.0,32.0,245.0,38.0,1505.0,208.0,354.0,1257.0,Computations and statistics on manifolds with geometric structures.,93.0,30,True,2024-09-09 17:46:06.000,2.8.0,33.0,geomstats,conda-forge/geomstats,,https://geomstats.github.io/,,135.0,123.0,https://pypi.org/project/geomstats,2024-09-09 17:41:39.000,12.0,4964.0,5103.0,https://anaconda.org/conda-forge/geomstats,2024-09-10 11:38:37.614,3910.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +310,skforecast,JoaquinAmatRodrigo/skforecast,time-series-data,,https://github.com/skforecast/skforecast,https://github.com/skforecast/skforecast,BSD-3-Clause,2021-02-10 11:40:34.000,2024-10-24 14:35:44.000000,2024-08-13 21:16:30,3511.0,61.0,131.0,10.0,638.0,23.0,151.0,1113.0,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'],352.0,337.0,https://pypi.org/project/skforecast,2024-08-01 12:24:50.000,15.0,90363.0,90363.0,,,,,,,,2.0,,,,skforecast/skforecast,,,,,,,,,,,,,,,, +311,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,,103.0,33.0,61.0,73.0,82.0,946.0,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,,,,107815.0,107288.0,https://pypi.org/project/patsy,2024-01-04 18:55:57.000,527.0,15475923.0,15813181.0,https://anaconda.org/conda-forge/patsy,2024-01-05 15:46:09.327,12478554.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +312,geojson,jazzband/geojson,geospatial-data,,https://github.com/jazzband/geojson,https://github.com/jazzband/geojson,BSD-3-Clause,2011-07-01 20:39:48.000,2024-10-07 18:17:28.000000,2024-10-04 14:18:34,499.0,5.0,121.0,32.0,132.0,25.0,75.0,915.0,Python bindings and utilities for GeoJSON.,58.0,30,True,2023-11-05 21:06:50.000,3.1.0,31.0,geojson,conda-forge/geojson,,,,19207.0,18506.0,https://pypi.org/project/geojson,2023-11-05 21:06:50.000,701.0,2984335.0,3027513.0,https://anaconda.org/conda-forge/geojson,2023-11-06 11:21:40.354,863577.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +313,CellProfiler,CellProfiler/CellProfiler,image,,https://github.com/CellProfiler/CellProfiler,https://github.com/CellProfiler/CellProfiler,BSD-3-Clause,2011-04-05 12:10:12.000,2024-09-27 19:27:52.000000,2024-09-24 16:01:52,16653.0,59.0,377.0,45.0,1649.0,306.0,2982.0,908.0,An open-source application for biological image analysis.,144.0,30,True,2024-09-27 21:18:50.000,4.2.8,35.0,cellprofiler,,,,,26.0,24.0,https://pypi.org/project/cellprofiler,2024-09-16 19:44:11.000,2.0,3539.0,3600.0,,,,,,,,2.0,7936.0,,,,,,,,,,,,,,,,,,, +314,mpi4py,mpi4py/mpi4py,distributed-ml,,https://github.com/mpi4py/mpi4py,https://github.com/mpi4py/mpi4py,BSD-3-Clause,2013-09-05 14:44:25.000,2024-10-17 07:40:52.000000,2024-10-14 07:43:05,3203.0,40.0,119.0,16.0,317.0,8.0,175.0,801.0,Python bindings for MPI.,27.0,30,True,2024-10-11 10:59:53.000,4.0.1,30.0,mpi4py,conda-forge/mpi4py,,,,750.0,,https://pypi.org/project/mpi4py,2024-10-11 10:59:53.000,750.0,556262.0,619574.0,https://anaconda.org/conda-forge/mpi4py,2024-10-12 13:31:50.789,3012948.0,,,,,2.0,27696.0,,,,,,,,,,,,,,,,,,, +315,snowballstemmer,snowballstem/snowball,nlp,,https://github.com/snowballstem/snowball,https://github.com/snowballstem/snowball,BSD-3-Clause,2013-02-23 07:17:42.000,2024-10-17 00:00:24.000000,2024-10-16 23:59:42,1092.0,19.0,174.0,35.0,117.0,27.0,65.0,756.0,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,,,,459.0,10.0,https://pypi.org/project/snowballstemmer,2021-11-16 18:38:34.000,449.0,22592529.0,22682003.0,https://anaconda.org/conda-forge/snowballstemmer,2023-06-16 13:16:49.834,8768507.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +316,TensorFlow I/O,tensorflow/io,tensorflow-utils,,https://github.com/tensorflow/io,https://github.com/tensorflow/io,Apache-2.0,2018-11-09 22:44:05.000,2024-10-23 19:47:51.000000,2024-07-01 21:47:36,1690.0,,283.0,42.0,1429.0,290.0,371.0,704.0,"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'],61.0,,https://pypi.org/project/tensorflow-io,2024-07-01 23:43:17.000,61.0,1337614.0,1337614.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +317,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,,107.0,25.0,53.0,37.0,57.0,486.0,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,,,,25014.0,24879.0,https://pypi.org/project/audioread,2023-09-27 19:27:51.000,135.0,2177393.0,2195821.0,https://anaconda.org/conda-forge/audioread,2024-09-03 10:05:52.331,884582.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +318,Cython BLIS,explosion/cython-blis,others,,https://github.com/explosion/cython-blis,https://github.com/explosion/cython-blis,BSD-3-Clause,2017-10-15 09:56:16.000,2024-10-23 06:29:06.515000,2024-09-12 22:24:23,593.0,5.0,37.0,10.0,75.0,10.0,26.0,219.0,Fast matrix-multiplication as a self-contained Python library no system dependencies!.,14.0,30,False,2024-09-13 08:21:34.000,1.0.1,49.0,blis,conda-forge/cython-blis,,,,50536.0,50435.0,https://pypi.org/project/blis,2024-09-13 08:21:34.000,101.0,12116655.0,12163720.0,https://anaconda.org/conda-forge/cython-blis,2024-10-23 06:29:06.515,2306073.0,,,,,2.0,188.0,,,,,,,,,,,,,,,,,,, +319,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,,3895.0,610.0,233.0,53.0,,14320.0,Python Backtesting library for trading strategies.,56.0,29,False,,,157.0,backtrader,,,,,2429.0,2355.0,https://pypi.org/project/backtrader,2023-04-19 14:15:00.742,74.0,41917.0,41917.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +320,PaddleDetection,PaddlePaddle/PaddleDetection,image,,https://github.com/PaddlePaddle/PaddleDetection,https://github.com/PaddlePaddle/PaddleDetection,Apache-2.0,2019-10-25 07:21:14.000,2024-10-18 10:13:38.000000,2024-10-18 10:13:38,2296.0,29.0,2856.0,198.0,3752.0,1237.0,4198.0,12728.0,"Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object..",181.0,29,True,2023-10-19 03:47:18.000,2.7.0,9.0,paddledet,,,,['paddle'],2.0,,https://pypi.org/project/paddledet,2022-09-19 20:42:09.271,2.0,745.0,745.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +321,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,,1834.0,214.0,46.0,101.0,94.0,9029.0,"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'],86.0,20.0,https://pypi.org/project/pretrainedmodels,2018-10-29 08:18:45.000,66.0,168905.0,169740.0,https://anaconda.org/conda-forge/pretrainedmodels,2023-06-16 19:20:12.183,43432.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +322,DoWhy,py-why/dowhy,interpretability,,https://github.com/py-why/dowhy,https://github.com/py-why/dowhy,MIT,2018-05-31 13:07:04.000,2024-10-22 21:00:36.000000,2024-10-22 00:36:18,1049.0,23.0,928.0,138.0,744.0,135.0,346.0,7083.0,DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions...,95.0,29,True,2023-12-25 07:11:09.000,0.11.1,15.0,dowhy,conda-forge/dowhy,,,,443.0,436.0,https://pypi.org/project/dowhy,2023-12-25 07:11:09.000,7.0,55329.0,56042.0,https://anaconda.org/conda-forge/dowhy,2024-01-26 10:57:10.385,33541.0,,,,,2.0,40.0,,,,,,,,,,,,,,,,,,, +323,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,,1389.0,190.0,786.0,45.0,423.0,6194.0,"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'],766.0,759.0,https://pypi.org/project/cleverhans,2021-07-24 08:53:21.000,7.0,2246.0,2421.0,https://anaconda.org/conda-forge/cleverhans,2023-06-16 19:20:32.486,9130.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +324,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,,1214.0,152.0,952.0,58.0,788.0,5821.0,Gluon CV Toolkit.,119.0,29,False,2022-03-07 23:40:19.000,0.10.5,1535.0,gluoncv,,,,['mxnet'],76.0,21.0,https://pypi.org/project/gluoncv,2023-02-03 18:46:00.371,55.0,157679.0,157679.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +325,SynapseML,microsoft/SynapseML,distributed-ml,,https://github.com/microsoft/SynapseML,https://github.com/microsoft/SynapseML,MIT,2017-06-05 08:23:44.000,2024-10-16 04:33:49.000000,2024-10-16 04:12:35,1641.0,24.0,830.0,145.0,1571.0,376.0,403.0,5061.0,Simple and Distributed Machine Learning.,120.0,29,True,2024-10-16 04:33:49.000,1.0.8,58.0,synapseml,,,,,5.0,,https://pypi.org/project/synapseml,2024-10-16 04:33:49.000,5.0,233764.0,233764.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +326,GluonTS,awslabs/gluon-ts,time-series-data,,https://github.com/awslabs/gluonts,https://github.com/awslabs/gluonts,Apache-2.0,2019-05-15 17:17:29.000,2024-10-21 13:12:43.000000,2024-10-17 12:23:01,1475.0,2.0,750.0,75.0,1818.0,327.0,634.0,4597.0,Probabilistic time series modeling in Python.,117.0,29,True,2024-06-03 07:20:43.000,0.15.1,111.0,gluonts,anaconda/gluonts,,,['mxnet'],33.0,,https://pypi.org/project/gluonts,2024-10-21 13:12:43.000,33.0,689866.0,689893.0,https://anaconda.org/anaconda/gluonts,2023-12-22 09:31:03.436,985.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +327,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,,457.0,42.0,126.0,75.0,154.0,4434.0,Data augmentation for NLP.,33.0,29,False,2022-07-07 05:24:14.000,1.1.11,37.0,nlpaug,conda-forge/nlpaug,,,,1473.0,1408.0,https://pypi.org/project/nlpaug,2022-07-07 05:23:07.000,65.0,140367.0,141022.0,https://anaconda.org/conda-forge/nlpaug,2023-06-16 19:26:38.185,26207.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +328,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,,902.0,148.0,132.0,138.0,104.0,4321.0,Technical Analysis Library using Pandas and Numpy.,34.0,29,True,2023-11-02 13:53:35.000,0.11.0,56.0,ta,conda-forge/ta,,,,4387.0,4280.0,https://pypi.org/project/ta,2023-11-02 13:53:35.000,107.0,159645.0,160327.0,https://anaconda.org/conda-forge/ta,2023-11-02 22:03:30.766,30029.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +329,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 11:02:25,515.0,4.0,568.0,44.0,541.0,14.0,,4041.0,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,,,,1437.0,1411.0,https://pypi.org/project/sahi,2024-07-10 10:19:56.000,26.0,140592.0,143341.0,https://anaconda.org/conda-forge/sahi,2024-07-24 03:28:58.170,76007.0,,,,,2.0,28096.0,,,,,,,,,,,,,,,,,,, +330,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,,515.0,77.0,38.0,14.0,121.0,3938.0,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,,,,18556.0,18434.0,https://pypi.org/project/missingno,2023-02-26 20:11:59.371,122.0,228034.0,280318.0,https://anaconda.org/conda-forge/missingno,2024-03-02 01:06:27.711,365990.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +331,NeuralProphet,ourownstory/neural_prophet,time-series-data,,https://github.com/ourownstory/neural_prophet,https://github.com/ourownstory/neural_prophet,MIT,2020-05-04 05:12:43.000,2024-09-16 21:51:17.000000,2024-09-13 01:42:25,1464.0,18.0,471.0,55.0,823.0,58.0,497.0,3860.0,NeuralProphet: A simple forecasting package.,56.0,29,True,2024-06-21 07:42:22.000,0.9.0,36.0,neuralprophet,,,,['pytorch'],8.0,,https://pypi.org/project/neuralprophet,2024-06-26 23:51:51.000,8.0,116098.0,116098.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +332,doctr,mindee/doctr,image,,https://github.com/mindee/doctr,https://github.com/mindee/doctr,Apache-2.0,2021-01-08 16:05:12.000,2024-10-24 09:42:40.000000,2024-10-24 09:38:13,895.0,23.0,428.0,43.0,985.0,27.0,339.0,3755.0,"docTR (Document Text Recognition) - a seamless, high-performing & accessible library for OCR-related tasks powered by..",52.0,29,True,2024-10-21 08:40:28.000,0.10.0,17.0,python-doctr,,,,"['tensorflow', 'pytorch']",12.0,,https://pypi.org/project/python-doctr,2024-10-21 08:40:28.000,12.0,50198.0,141052.0,,,,,,,,2.0,3997584.0,,,,,,,,,,,,,,,,,,, +333,bqplot,bqplot/bqplot,data-viz,,https://github.com/bqplot/bqplot,https://github.com/bqplot/bqplot,Apache-2.0,2015-09-26 04:02:18.000,2024-10-22 15:06:47.000000,2024-10-22 15:05:01,3667.0,6.0,463.0,102.0,1060.0,259.0,368.0,3620.0,Plotting library for IPython/Jupyter notebooks.,65.0,29,True,2024-02-27 15:38:38.000,0.12.43,112.0,bqplot,conda-forge/bqplot,,,['jupyter'],179.0,59.0,https://pypi.org/project/bqplot,2024-03-25 09:03:21.000,99.0,196525.0,225581.0,https://anaconda.org/conda-forge/bqplot,2024-02-19 16:46:43.025,1401548.0,,,,,3.0,,,,,bqplot,https://www.npmjs.com/package/bqplot,2024-03-25 09:04:27.051,21.0,2612.0,,,,,,,,,,, +334,Deep Checks,deepchecks/deepchecks,interpretability,,https://github.com/deepchecks/deepchecks,https://github.com/deepchecks/deepchecks,AGPL-3.0,2021-10-11 14:48:38.000,2024-10-14 13:03:13.000000,2024-02-22 12:17:17,1487.0,,253.0,21.0,1746.0,295.0,726.0,3598.0,Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all..,53.0,29,False,2024-01-31 13:08:55.000,0.18.1,60.0,deepchecks,,,,,461.0,449.0,https://pypi.org/project/deepchecks,2024-01-31 13:08:49.000,12.0,89893.0,89927.0,,,,,,,,2.0,1225.0,,,,,,,,,,,,,,,,,,, +335,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,,252.0,61.0,121.0,8.0,289.0,3359.0,A High-performance cross-platform Video Processing Python framework powerpacked with unique trailblazing features.,14.0,29,True,2024-06-22 19:12:02.000,0.3.3,23.0,vidgear,,,,,640.0,625.0,https://pypi.org/project/vidgear,2024-06-22 19:12:02.000,15.0,23725.0,23751.0,,,,,,,,2.0,1770.0,,,,,,,,,,,,,,,,,,, +336,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,,450.0,83.0,245.0,69.0,155.0,3066.0,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,,,,,205.0,202.0,https://pypi.org/project/fastnlp,2022-10-31 14:47:34.183,3.0,122997.0,122998.0,,,,,,,,2.0,89.0,,,,,,,,,,,,,,,,,,, +337,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,,676.0,108.0,74.0,102.0,123.0,3028.0,Productivity Tools for Plotly + Pandas.,39.0,29,False,2020-03-01 17:42:01.000,0.17.3,28.0,cufflinks,,,,['pandas'],12089.0,11980.0,https://pypi.org/project/cufflinks,2020-03-01 17:42:01.000,109.0,81812.0,81812.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +338,TF-Agents,tensorflow/agents,reinforcement-learning,,https://github.com/tensorflow/agents,https://github.com/tensorflow/agents,Apache-2.0,2018-11-17 00:29:12.000,2024-10-09 07:57:26.000000,2024-10-09 07:56:44,2306.0,7.0,721.0,79.0,206.0,199.0,469.0,2793.0,"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'],14.0,,https://pypi.org/project/tf-agents,2023-12-14 04:07:38.000,14.0,93460.0,93460.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +339,Neural Network Libraries,sony/nnabla,ml-frameworks,,https://github.com/sony/nnabla,https://github.com/sony/nnabla,Apache-2.0,2017-06-26 01:07:10.000,2024-09-24 01:23:55.000000,2024-09-24 01:23:52,3553.0,9.0,333.0,154.0,1182.0,35.0,60.0,2724.0,Neural Network Libraries.,76.0,29,True,2024-05-29 05:14:17.000,1.39.0,79.0,nnabla,,,,,44.0,,https://pypi.org/project/nnabla,2024-05-29 02:51:02.000,44.0,15012.0,15023.0,,,,,,,,3.0,980.0,,,,,,,,,,,,,,,,,,, +340,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'],1645.0,1623.0,https://pypi.org/project/gluonnlp,2020-08-13 19:17:42.000,22.0,98897.0,98897.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +341,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.,13.0,29,False,2018-08-19 12:25:39.290,0.3.7,27.0,scikit-plot,conda-forge/scikit-plot,,,['sklearn'],5604.0,5519.0,https://pypi.org/project/scikit-plot,2018-08-19 12:25:39.290,85.0,460252.0,462398.0,https://anaconda.org/conda-forge/scikit-plot,2023-06-16 13:22:21.652,186787.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +342,mpld3,mpld3/mpld3,data-viz,,https://github.com/mpld3/mpld3,https://github.com/mpld3/mpld3,BSD-3-Clause,2013-12-18 01:48:30.000,2024-10-23 10:38:04.000000,2024-10-23 10:38:02,888.0,1.0,360.0,82.0,168.0,217.0,148.0,2355.0,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,,,,6757.0,6602.0,https://pypi.org/project/mpld3,2023-12-23 13:03:02.000,146.0,351858.0,356761.0,https://anaconda.org/conda-forge/mpld3,2023-12-23 15:16:22.285,211480.0,,,,,3.0,,,,,mpld3,https://www.npmjs.com/package/mpld3,2023-12-23 13:04:29.963,9.0,837.0,,,,,,,,,,, +343,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,,328.0,22.0,49.0,35.0,203.0,2304.0,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,,,,556.0,546.0,https://pypi.org/project/explainerdashboard,2024-03-18 21:02:33.000,10.0,80572.0,81752.0,https://anaconda.org/conda-forge/explainerdashboard,2024-03-18 22:16:35.129,54280.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +344,mtcnn,ipazc/mtcnn,image,,https://github.com/ipazc/mtcnn,https://github.com/ipazc/mtcnn,MIT,2018-01-05 04:08:32.000,2024-10-08 16:09:34.000000,2024-10-08 16:09:34,62.0,6.0,526.0,43.0,29.0,49.0,81.0,2215.0,"MTCNN face detection implementation for TensorFlow, as a PIP package.",16.0,29,True,2024-10-08 01:42:18.000,1.0.0,12.0,mtcnn,conda-forge/mtcnn,,,['tensorflow'],6335.0,6262.0,https://pypi.org/project/mtcnn,2024-10-08 01:42:18.000,73.0,122378.0,122619.0,https://anaconda.org/conda-forge/mtcnn,2023-06-16 19:18:00.316,13273.0,,,,,2.0,4.0,,,,,,,,,,,,,,,,,,, +345,ffn,pmorissette/ffn,financial-data,,https://github.com/pmorissette/ffn,https://github.com/pmorissette/ffn,MIT,2014-06-19 15:54:09.000,2024-10-22 13:55:50.000000,2024-10-01 13:02:45,487.0,10.0,292.0,64.0,123.0,22.0,105.0,2023.0,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,,,,513.0,495.0,https://pypi.org/project/ffn,2024-08-05 23:48:25.000,18.0,18612.0,18910.0,https://anaconda.org/conda-forge/ffn,2024-08-06 14:03:54.464,12547.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +346,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,,400.0,41.0,63.0,25.0,272.0,1936.0,"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,,,,2034.0,2012.0,https://pypi.org/project/ogb,2022-11-02 22:00:56.960,22.0,68234.0,69035.0,https://anaconda.org/conda-forge/ogb,2023-06-16 19:21:31.692,39267.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +347,fairlearn,fairlearn/fairlearn,interpretability,,https://github.com/fairlearn/fairlearn,https://github.com/fairlearn/fairlearn,MIT,2018-05-15 01:51:35.000,2024-10-24 10:47:06.000000,2024-10-24 10:47:06,883.0,11.0,415.0,39.0,910.0,162.0,323.0,1931.0,A Python package to assess and improve fairness of machine learning models.,84.0,29,True,2023-12-19 14:14:09.000,0.10.0,20.0,fairlearn,conda-forge/fairlearn,,,['sklearn'],58.0,3.0,https://pypi.org/project/fairlearn,2023-12-19 02:11:12.000,55.0,175239.0,176026.0,https://anaconda.org/conda-forge/fairlearn,2023-12-20 11:56:56.090,37002.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +348,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,,359.0,47.0,80.0,78.0,113.0,1803.0,Python library for interactive topic model visualization. Port of the R LDAvis package.,42.0,29,True,2023-04-23 23:55:02.142,3.4.1,26.0,pyldavis,conda-forge/pyldavis,,,['jupyter'],6634.0,6531.0,https://pypi.org/project/pyldavis,2023-04-23 23:55:02.142,103.0,133832.0,134977.0,https://anaconda.org/conda-forge/pyldavis,2023-06-16 16:08:55.034,87087.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +349,SciSpacy,allenai/scispacy,nlp,,https://github.com/allenai/scispacy,https://github.com/allenai/scispacy,Apache-2.0,2018-09-24 21:45:52.000,2024-09-15 02:16:48.000000,2024-09-15 02:16:48,1062.0,3.0,225.0,51.0,208.0,32.0,290.0,1700.0,A full spaCy pipeline and models for scientific/biomedical documents.,34.0,29,True,2024-03-08 05:58:36.000,0.5.4,15.0,scispacy,,,,,1012.0,978.0,https://pypi.org/project/scispacy,2024-03-08 05:58:36.000,34.0,25785.0,25785.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +350,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,,197.0,34.0,73.0,29.0,52.0,1570.0,Differentiable SDE solvers with GPU support and efficient sensitivity analysis.,8.0,29,False,2023-09-26 22:07:23.000,0.2.6,5.0,torchsde,conda-forge/torchsde,,,['pytorch'],3895.0,3858.0,https://pypi.org/project/torchsde,2023-09-26 21:52:19.000,37.0,1896487.0,1897128.0,https://anaconda.org/conda-forge/torchsde,2023-06-16 19:24:16.458,28883.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +351,TabPy,tableau/TabPy,others,,https://github.com/tableau/TabPy,https://github.com/tableau/TabPy,MIT,2016-09-27 21:26:03.000,2024-09-23 20:40:57.000000,2024-09-23 18:45:00,1017.0,35.0,592.0,106.0,292.0,22.0,300.0,1561.0,Execute Python code on the fly and display results in Tableau visualizations:.,51.0,29,True,2024-09-23 20:40:57.000,2.12.0,34.0,tabpy,anaconda/tabpy-client,,,,186.0,184.0,https://pypi.org/project/tabpy,2024-09-23 20:40:57.000,2.0,41724.0,41775.0,https://anaconda.org/anaconda/tabpy-client,2023-06-16 13:20:17.078,4632.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +352,dstack,dstackai/dstack,others,,https://github.com/dstackai/dstack,https://github.com/dstackai/dstack,MPL-2.0,2022-01-04 10:29:46.000,2024-10-24 13:17:28.000000,2024-10-24 13:17:26,2200.0,249.0,140.0,11.0,891.0,105.0,878.0,1413.0,"dstack is an open-source alternative to Kubernetes, designed to simplify development, training, and deployment of AI..",42.0,29,True,2024-10-23 10:09:34.000,0.18.20,236.0,dstack,,,,,16.0,16.0,https://pypi.org/project/dstack,2024-10-23 09:10:59.000,,17760.0,17760.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +353,Submit it,facebookincubator/submitit,distributed-ml,,https://github.com/facebookincubator/submitit,https://github.com/facebookincubator/submitit,MIT,2020-04-24 07:41:09.000,2024-09-18 16:05:13.000000,2024-09-18 16:03:14,147.0,6.0,120.0,24.0,110.0,46.0,78.0,1284.0,Python 3.8+ toolbox for submitting jobs to Slurm.,25.0,29,True,2024-09-18 16:05:09.000,1.5.2,24.0,submitit,conda-forge/submitit,,,,3402.0,3353.0,https://pypi.org/project/submitit,2024-09-18 16:05:09.000,49.0,541461.0,542294.0,https://anaconda.org/conda-forge/submitit,2023-11-24 07:58:55.401,41663.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +354,Prince,MaxHalford/prince,others,,https://github.com/MaxHalford/prince,https://github.com/MaxHalford/prince,MIT,2016-10-22 12:36:06.000,2024-09-08 06:00:12.000000,2024-09-07 18:33:30,408.0,10.0,182.0,26.0,39.0,9.0,130.0,1263.0,"Multivariate exploratory data analysis in Python PCA, CA, MCA, MFA, FAMD, GPA.",16.0,29,True,2024-09-07 18:34:31.000,0.13.1,60.0,prince,conda-forge/prince-factor-analysis,,,['sklearn'],637.0,619.0,https://pypi.org/project/prince,2024-09-07 18:34:31.000,18.0,201246.0,201601.0,https://anaconda.org/conda-forge/prince-factor-analysis,2023-06-16 16:19:02.748,21003.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +355,Model Analysis,tensorflow/model-analysis,interpretability,,https://github.com/tensorflow/model-analysis,https://github.com/tensorflow/model-analysis,Apache-2.0,2018-03-23 19:08:49.000,2024-10-17 18:35:06.000000,2024-10-17 18:35:05,1523.0,60.0,274.0,72.0,108.0,33.0,55.0,1256.0,Model analysis tools for TensorFlow.,58.0,29,True,2024-04-25 08:57:36.000,0.46.0,57.0,tensorflow-model-analysis,,,,"['tensorflow', 'jupyter']",19.0,,https://pypi.org/project/tensorflow-model-analysis,2024-04-25 08:57:36.000,19.0,127028.0,127028.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +356,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,,268.0,35.0,38.0,1.0,497.0,1230.0,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'],559.0,555.0,https://pypi.org/project/ktrain,2024-06-19 01:15:40.000,4.0,16367.0,16367.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +357,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,,328.0,65.0,690.0,36.0,533.0,836.0,The Classical Language Toolkit.,121.0,29,True,2024-05-13 16:48:36.000,1.2.6,217.0,cltk,,,,,289.0,274.0,https://pypi.org/project/cltk,2024-05-12 23:09:13.000,15.0,14396.0,14396.0,,,,,,,,2.0,98.0,,,,,,,,,,,,,,,,,,, +358,GeoViews,holoviz/geoviews,geospatial-data,,https://github.com/holoviz/geoviews,https://github.com/holoviz/geoviews,BSD-3-Clause,2016-04-19 16:27:01.000,2024-10-16 18:50:37.000000,2024-10-08 15:25:16,847.0,17.0,76.0,26.0,406.0,105.0,241.0,595.0,"Simple, concise geographical visualization in Python.",32.0,29,True,2024-09-18 10:30:55.000,1.13.0,66.0,geoviews,conda-forge/geoviews,,,,1203.0,1144.0,https://pypi.org/project/geoviews,2024-09-16 16:00:44.000,59.0,20244.0,25393.0,https://anaconda.org/conda-forge/geoviews,2024-09-17 10:57:22.057,252349.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +359,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 11:25:57.000,2024-10-18 14:32:51.000000,2024-09-26 12:17:28,2097.0,4.0,63.0,17.0,1635.0,29.0,215.0,579.0,The experiment tracker for foundation model training.,54.0,29,True,2024-10-02 08:04:08.000,1.12.0,210.0,neptune-client,conda-forge/neptune-client,,,,711.0,634.0,https://pypi.org/project/neptune-client,2024-10-02 08:04:08.000,77.0,498932.0,504319.0,https://anaconda.org/conda-forge/neptune-client,2024-10-02 12:46:58.862,285514.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +360,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,,1154.0,239.0,456.0,75.0,264.0,18128.0,"Automatically decrypt encryptions without knowing the key or cipher, decode encodings, and crack hashes.",48.0,28,True,2021-06-06 17:15:00.281,5.14.0,50.0,ciphey,,remnux/ciphey,,,,,https://pypi.org/project/ciphey,2021-06-06 17:15:00.281,,186011.0,186427.0,,,,https://hub.docker.com/r/remnux/ciphey,2023-10-14 18:53:31.974373,17.0,26240.0,2.0,,,,,,,,,,,,,,,,,,,, +361,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,,1146.0,349.0,81.0,50.0,231.0,8020.0,StarCraft II Learning Environment.,39.0,28,False,2022-07-13 12:08:43.000,4.0,8.0,pysc2,,,,,857.0,831.0,https://pypi.org/project/pysc2,2022-07-13 12:02:04.256,26.0,2941.0,3312.0,,,,,,,,2.0,31942.0,,,google-deepmind/pysc2,,,,,,,,,,,,,,,, +362,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,,886.0,268.0,98.0,82.0,81.0,7355.0,Visualizations for machine learning datasets.,31.0,28,False,2023-05-24 15:58:01.158,1.1.1,9.0,facets-overview,,,,['jupyter'],279.0,271.0,https://pypi.org/project/facets-overview,2023-05-24 15:58:01.158,8.0,95632.0,95632.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +363,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 14:19:23,221.0,1.0,1338.0,172.0,46.0,80.0,241.0,7056.0,2D 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'],31.0,21.0,https://pypi.org/project/face-alignment,2023-08-17 14:43:11.000,10.0,59941.0,59941.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +364,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,,1011.0,145.0,100.0,87.0,310.0,6389.0,A Python scikit for building and analyzing recommender systems.,46.0,28,True,2024-05-19 14:25:59.000,1.1.4,12.0,scikit-surprise,conda-forge/scikit-surprise,,,,58.0,21.0,https://pypi.org/project/scikit-surprise,2024-05-19 14:25:59.000,37.0,90065.0,98281.0,https://anaconda.org/conda-forge/scikit-surprise,2024-05-20 10:08:43.793,419037.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +365,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,,1190.0,210.0,92.0,201.0,122.0,5859.0,"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,,,,,534.0,522.0,https://pypi.org/project/pyAudioAnalysis,2022-02-07 22:36:53.000,12.0,14276.0,14276.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +366,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,,1362.0,200.0,158.0,49.0,227.0,5522.0,Deep Reinforcement Learning for Keras.,41.0,28,False,2018-06-01 07:52:24.000,0.4.2,8.0,keras-rl,,,,['tensorflow'],800.0,794.0,https://pypi.org/project/keras-rl,2018-06-01 07:52:24.000,6.0,1268.0,1268.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +367,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,,461.0,74.0,63.0,110.0,57.0,4863.0,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,,,,,3065.0,3043.0,https://pypi.org/project/layoutparser,2022-04-06 04:38:09.000,22.0,382870.0,382870.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +368,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,,780.0,271.0,438.0,221.0,329.0,4834.0,"A probabilistic programming language in TensorFlow. Deep generative models, variational inference.",87.0,28,False,2018-01-22 06:03:37.000,1.3.5,28.0,edward,,,,['tensorflow'],332.0,330.0,https://pypi.org/project/edward,2018-01-22 06:03:05.000,2.0,3372.0,3372.0,,,,,,,,3.0,25.0,,,,,,,,,,,,,,,,,,, +369,VisualDL,PaddlePaddle/VisualDL,ml-experiments,,https://github.com/PaddlePaddle/VisualDL,https://github.com/PaddlePaddle/VisualDL,Apache-2.0,2017-12-20 12:34:31.000,2024-10-14 11:22:26.000000,2024-10-14 11:22:26,921.0,3.0,634.0,148.0,792.0,141.0,356.0,4773.0,Deep Learning Visualization Toolkit.,35.0,28,True,2023-06-05 07:21:00.910,2.5.3,43.0,visualdl,,,,['paddle'],84.0,2.0,https://pypi.org/project/visualdl,2023-06-05 07:21:00.910,82.0,170429.0,170437.0,,,,,,,,2.0,455.0,,,,,,,,,,,,,,,,,,, +370,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,,686.0,87.0,209.0,157.0,358.0,4759.0,"A Python implementation of LightFM, a hybrid recommendation algorithm.",47.0,28,False,2023-03-20 04:08:46.000,1.17,15.0,lightfm,conda-forge/lightfm,,,,1592.0,1560.0,https://pypi.org/project/lightfm,2023-03-20 04:15:00.582,32.0,316956.0,319778.0,https://anaconda.org/conda-forge/lightfm,2023-06-16 16:08:40.466,228616.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +371,ArrayFire,arrayfire/arrayfire,gpu-utilities,,https://github.com/arrayfire/arrayfire,https://github.com/arrayfire/arrayfire,BSD-3-Clause,2014-10-28 20:58:33.000,2024-10-23 00:34:12.000000,2024-10-23 00:34:11,6176.0,23.0,529.0,147.0,1948.0,338.0,1385.0,4558.0,ArrayFire: a general purpose GPU library.,94.0,28,True,2023-08-29 19:49:26.000,3.9.0,34.0,arrayfire,,,,,10.0,,https://pypi.org/project/arrayfire,2022-02-22 21:42:15.000,10.0,6210.0,6273.0,,,,,,,,2.0,7135.0,,,,,,,,,,,,,,,,,,, +372,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,,736.0,175.0,90.0,1.0,288.0,4260.0,A python wrapper for Alpha Vantage API for financial data.,44.0,28,True,2024-07-18 14:29:16.000,3.0.0,35.0,alpha_vantage,conda-forge/alpha_vantage,,,,35.0,,https://pypi.org/project/alpha_vantage,2024-07-18 14:29:16.000,35.0,44248.0,44417.0,https://anaconda.org/conda-forge/alpha_vantage,2024-08-09 13:30:50.391,7612.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +373,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,,949.0,218.0,408.0,139.0,402.0,3844.0,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,,,,,1076.0,1064.0,https://pypi.org/project/lasagne,2015-08-13 21:10:53.000,12.0,2387.0,2387.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +374,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,,526.0,113.0,93.0,23.0,101.0,3515.0,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,,,,3198.0,3167.0,https://pypi.org/project/sumy,2022-10-23 16:42:18.783,31.0,402656.0,402895.0,https://anaconda.org/conda-forge/sumy,2023-06-16 19:26:28.563,9588.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +375,Acme,deepmind/acme,reinforcement-learning,,https://github.com/google-deepmind/acme,https://github.com/google-deepmind/acme,Apache-2.0,2020-05-01 09:18:12.000,2024-09-17 20:09:27.000000,2024-09-17 20:08:40,1205.0,3.0,422.0,84.0,55.0,62.0,203.0,3495.0,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'],221.0,218.0,https://pypi.org/project/dm-acme,2022-02-10 06:52:27.000,3.0,2167.0,2381.0,https://anaconda.org/conda-forge/dm-acme,2023-06-16 19:23:44.096,10079.0,,,,,2.0,,,,google-deepmind/acme,,,,,,,,,,,,,,,, +376,LIT,PAIR-code/lit,interpretability,,https://github.com/PAIR-code/lit,https://github.com/PAIR-code/lit,Apache-2.0,2020-07-28 13:07:26.000,2024-10-22 19:57:27.000000,2024-10-22 19:55:17,1581.0,83.0,354.0,67.0,1449.0,115.0,85.0,3482.0,The Learning Interpretability Tool: Interactively analyze ML models to understand their behavior in an extensible and..,38.0,28,True,2024-10-22 20:02:07.000,1.3,19.0,lit-nlp,conda-forge/lit-nlp,,,,43.0,40.0,https://pypi.org/project/lit-nlp,2024-10-22 19:57:27.000,3.0,4221.0,6100.0,https://anaconda.org/conda-forge/lit-nlp,2023-06-16 19:21:41.530,92092.0,,,,,2.0,,3.0,,,,,,,,,,,,,,,,,, +377,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,,371.0,83.0,66.0,156.0,189.0,3301.0,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,,,,504.0,487.0,https://pypi.org/project/aubio,2019-02-08 11:21:02.000,17.0,8697.0,16668.0,https://anaconda.org/conda-forge/aubio,2023-06-16 13:24:40.255,725402.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +378,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,,387.0,46.0,1085.0,2.0,353.0,3286.0,Accelerated deep learning R&D.,104.0,28,False,2022-04-29 04:45:11.000,22.04,108.0,catalyst,,,,['pytorch'],1234.0,1204.0,https://pypi.org/project/catalyst,2022-04-29 04:46:04.000,30.0,43835.0,43835.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +379,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 16:58:41,621.0,2.0,334.0,46.0,121.0,72.0,137.0,2955.0,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,,,,1375.0,1322.0,https://pypi.org/project/dtreeviz,2022-07-07 17:18:00.886,53.0,114844.0,116676.0,https://anaconda.org/conda-forge/dtreeviz,2023-07-13 20:18:43.899,86149.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +380,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,,429.0,62.0,933.0,325.0,747.0,2945.0,StellarGraph - Machine Learning on Graphs.,37.0,28,False,2021-02-22 06:35:38.731,1.2.1,25.0,stellargraph,,,,['tensorflow'],292.0,281.0,https://pypi.org/project/stellargraph,2021-02-22 06:35:38.731,11.0,17681.0,17681.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +381,Essentia,MTG/essentia,audio,,https://github.com/MTG/essentia,https://github.com/MTG/essentia,AGPL-3.0,2013-06-03 14:53:47.000,2024-10-23 10:52:14.000000,2024-10-23 10:52:14,3642.0,15.0,522.0,108.0,364.0,388.0,689.0,2838.0,"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,,,,,816.0,796.0,https://pypi.org/project/essentia,2024-04-29 15:12:27.000,20.0,20379.0,20379.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +382,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 14:54:41,1058.0,5.0,411.0,124.0,144.0,198.0,247.0,2648.0,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,,,,101.0,,https://pypi.org/project/pygal,2024-08-12 14:55:21.000,101.0,221868.0,225257.0,https://anaconda.org/conda-forge/pygal,2024-08-13 16:15:34.495,71187.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +383,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,,997.0,123.0,526.0,65.0,300.0,2588.0,IPython Parallel: Interactive Parallel Computing in Python.,113.0,28,False,2024-04-05 11:35:24.000,8.8.0,47.0,ipyparallel,conda-forge/ipyparallel,,,['jupyter'],112.0,,https://pypi.org/project/ipyparallel,2024-04-05 11:35:24.000,112.0,486638.0,510136.0,https://anaconda.org/conda-forge/ipyparallel,2024-04-05 13:21:22.787,1127915.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +384,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,,336.0,45.0,57.0,69.0,209.0,2367.0,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'],344.0,337.0,https://pypi.org/project/spektral,2024-01-21 16:17:36.000,7.0,12215.0,12215.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +385,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,,315.0,65.0,14.0,28.0,47.0,2313.0,Stand-alone language identification system.,9.0,28,False,2016-04-05 22:34:15.000,1.1.6,8.0,langid,,,,,11852.0,11697.0,https://pypi.org/project/langid,2016-04-05 22:34:15.000,155.0,398258.0,398258.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +386,modAL,modAL-python/modAL,others,,https://github.com/modAL-python/modAL,https://github.com/modAL-python/modAL,MIT,2017-11-14 14:01:15.000,2024-10-24 09:38:19.000000,2023-06-01 12:18:23,739.0,,320.0,44.0,44.0,99.0,56.0,2213.0,A modular active learning framework for Python.,20.0,28,False,2024-10-24 09:38:19.000,0.64.223,1343.0,modAL,,,,['sklearn'],65.0,,https://pypi.org/project/modAL,2024-10-24 09:38:19.000,65.0,797308.0,797308.0,,,,,,,,2.0,42.0,,,,,,,,,,,,,,,,,,, +387,Labml,labmlai/labml,ml-experiments,,https://github.com/labmlai/labml,https://github.com/labmlai/labml,MIT,2018-11-16 09:34:48.000,2024-10-22 17:33:41.000000,2024-10-22 17:33:41,2283.0,172.0,135.0,27.0,259.0,5.0,42.0,2038.0,Monitor deep learning model training and hardware usage from your mobile phone.,9.0,28,True,2024-09-15 02:15:00.000,0.5.3,147.0,labml,,,,,188.0,174.0,https://pypi.org/project/labml,2024-09-15 02:15:00.000,14.0,13474.0,13474.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +388,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,,279.0,40.0,495.0,172.0,151.0,1794.0,Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets..,50.0,28,True,2022-12-16 20:54:02.878,0.12.1,86.0,petastorm,,,,,193.0,185.0,https://pypi.org/project/petastorm,2023-02-03 00:33:00.499,8.0,162773.0,162779.0,,,,,,,,2.0,521.0,,,,,,,,,,,,,,,,,,, +389,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,,245.0,53.0,446.0,6.0,402.0,1737.0,Fast & easy transfer learning for NLP. Harvesting language models for the industry. Focus on Question Answering.,37.0,28,False,2023-03-07 23:47:39.075,0.7.1,25.0,farm,conda-forge/farm,,,['pytorch'],232.0,229.0,https://pypi.org/project/farm,2020-09-14 15:23:01.000,3.0,60691.0,60786.0,https://anaconda.org/conda-forge/farm,2023-06-16 19:25:45.236,3994.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +390,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 20:34:28.000,2024-10-24 09:14:19.000000,2024-09-25 00:22:36,832.0,1.0,320.0,120.0,786.0,225.0,168.0,1490.0,"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'],45.0,,https://pypi.org/project/tensorflow-model-optimization,2024-02-08 01:57:17.000,45.0,809415.0,809415.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +391,openTSNE,pavlin-policar/openTSNE,data-viz,,https://github.com/pavlin-policar/openTSNE,https://github.com/pavlin-policar/openTSNE,BSD-3-Clause,2018-06-08 18:42:09.000,2024-09-13 08:50:44.958000,2024-08-13 10:02:03,694.0,3.0,158.0,22.0,126.0,5.0,131.0,1462.0,"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,,,,942.0,895.0,https://pypi.org/project/opentsne,2024-08-13 11:02:01.000,47.0,42255.0,48727.0,https://anaconda.org/conda-forge/opentsne,2024-09-13 08:50:44.958,323641.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +392,pycm,sepandhaghighi/pycm,others,,https://github.com/sepandhaghighi/pycm,https://github.com/sepandhaghighi/pycm,MIT,2018-01-22 19:46:54.000,2024-10-17 16:26:25.000000,2024-10-15 17:52:15,3072.0,12.0,123.0,36.0,369.0,12.0,191.0,1449.0,Multi-class confusion matrix library in Python.,17.0,28,True,2024-10-17 14:28:07.000,4.1,45.0,pycm,,,,,368.0,344.0,https://pypi.org/project/pycm,2024-10-17 14:28:28.000,24.0,40692.0,40692.0,,,,,,,,2.0,,2.0,,,,,,,,,,,,,,,,,, +393,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 13:05:21,610.0,18.0,417.0,31.0,51.0,16.0,128.0,1435.0,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,,,,,697.0,666.0,https://pypi.org/project/minisom,2024-08-23 12:22:45.000,31.0,27880.0,27880.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +394,underthesea,undertheseanlp/underthesea,nlp,,https://github.com/undertheseanlp/underthesea,https://github.com/undertheseanlp/underthesea,GPL-3.0,2017-03-01 10:24:26.000,2024-10-23 17:45:04.000000,2024-10-06 04:17:23,862.0,4.0,270.0,78.0,492.0,53.0,206.0,1397.0,Underthesea - Vietnamese NLP Toolkit.,19.0,28,False,2024-06-22 10:18:00.000,6.8.4,127.0,underthesea,,,,,1217.0,1206.0,https://pypi.org/project/underthesea,2024-06-22 10:18:00.000,11.0,22898.0,22978.0,,,,,,,,2.0,7134.0,,,,,,,,,,,,,,,,,,, +395,DALEX,ModelOriented/DALEX,interpretability,,https://github.com/ModelOriented/DALEX,https://github.com/ModelOriented/DALEX,GPL-3.0,2018-02-18 03:24:12.000,2024-10-02 18:05:47.000000,2024-10-02 18:05:45,687.0,9.0,165.0,50.0,164.0,25.0,384.0,1367.0,moDel Agnostic Language for Exploration and eXplanation.,26.0,28,False,2024-10-02 18:03:07.000,1.7.1,28.0,dalex,conda-forge/dalex,,,,192.0,185.0,https://pypi.org/project/dalex,2024-10-02 18:03:07.000,7.0,27874.0,28250.0,https://anaconda.org/conda-forge/dalex,2024-02-29 10:49:59.696,16926.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +396,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,,,1345.0,"Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy.",22.0,28,True,2024-04-25 12:54:53.000,1.3.5,77.0,spacy-transformers,conda-forge/spacy-transformers,,,['spacy'],1990.0,1903.0,https://pypi.org/project/spacy-transformers,2024-04-25 12:53:43.000,87.0,397296.0,399247.0,https://anaconda.org/conda-forge/spacy-transformers,2023-12-19 11:34:09.090,68319.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +397,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,,330.0,39.0,302.0,31.0,200.0,1274.0,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,,,,,466.0,444.0,https://pypi.org/project/pyswarms,2021-01-03 21:34:15.000,22.0,31094.0,31094.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +398,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,,416.0,52.0,41.0,17.0,139.0,1240.0,"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,,,,2886.0,2848.0,https://pypi.org/project/kmodes,2022-09-06 19:38:02.764,38.0,260128.0,261056.0,https://anaconda.org/conda-forge/kmodes,2023-06-16 19:18:39.600,50137.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +399,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'],311.0,,https://pypi.org/project/keras-preprocessing,2020-05-14 03:55:22.223,311.0,4097851.0,4128348.0,https://anaconda.org/conda-forge/keras-preprocessing,2023-06-16 16:10:42.597,2317808.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +400,pythreejs,jupyter-widgets/pythreejs,data-viz,,https://github.com/jupyter-widgets/pythreejs,https://github.com/jupyter-widgets/pythreejs,BSD-3-Clause,2013-12-23 17:02:11.000,2024-10-10 15:48:16.000000,2023-02-20 00:24:10,1723.0,,185.0,41.0,176.0,65.0,174.0,951.0,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'],96.0,,https://pypi.org/project/pythreejs,2023-02-20 00:24:01.104,82.0,88274.0,96822.0,https://anaconda.org/conda-forge/pythreejs,2023-06-16 13:16:30.947,604420.0,,,,,3.0,,,,,jupyter-threejs,https://www.npmjs.com/package/jupyter-threejs,2023-02-20 00:16:17.277,14.0,2564.0,,,,,,,,,,, +401,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,,256.0,40.0,513.0,280.0,257.0,898.0,Scalable Machine Learning with Dask.,80.0,28,True,2024-04-02 02:33:18.000,2024.4.4,37.0,dask-ml,conda-forge/dask-ml,,,,1218.0,1125.0,https://pypi.org/project/dask-ml,2024-04-02 02:33:18.000,93.0,121143.0,138157.0,https://anaconda.org/conda-forge/dask-ml,2024-06-17 15:22:39.176,901772.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +402,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,,105.0,14.0,99.0,73.0,67.0,883.0,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,,,,8323.0,8167.0,https://pypi.org/project/pynndescent,2024-06-17 15:48:31.000,156.0,1607949.0,1648265.0,https://anaconda.org/conda-forge/pynndescent,2024-06-17 19:35:33.219,2056118.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +403,Cornac,PreferredAI/cornac,recommender-systems,,https://github.com/PreferredAI/cornac,https://github.com/PreferredAI/cornac,Apache-2.0,2018-07-17 06:31:35.000,2024-09-14 05:03:32.000000,2024-09-14 05:03:32,1368.0,5.0,139.0,26.0,487.0,19.0,140.0,875.0,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,,,,257.0,239.0,https://pypi.org/project/cornac,2024-08-15 06:52:10.000,18.0,64389.0,75753.0,https://anaconda.org/conda-forge/cornac,2024-09-13 18:17:19.820,590959.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +404,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,,149.0,50.0,59.0,21.0,70.0,842.0,Computer Vision in Python.,35.0,28,True,2024-07-17 21:10:14.000,1.4.18,63.0,mahotas,conda-forge/mahotas,,,,1432.0,1369.0,https://pypi.org/project/mahotas,2024-07-17 21:10:14.000,63.0,30417.0,40188.0,https://anaconda.org/conda-forge/mahotas,2024-07-18 20:23:32.152,508135.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +405,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 07:14:46,566.0,1.0,106.0,16.0,196.0,119.0,139.0,710.0,"SoundFile is an audio library based on libsndfile, CFFI, and NumPy.",34.0,28,True,2023-02-15 15:39:02.000,0.12.1,15.0,soundfile,anaconda/pysoundfile,,,,44774.0,43994.0,https://pypi.org/project/soundfile,2023-02-15 15:39:00.786,780.0,4791984.0,4792141.0,https://anaconda.org/anaconda/pysoundfile,,,,,,,3.0,20215.0,,,,,,,,,,,,,,,,,,, +406,tinytag,devsnd/tinytag,audio,,https://github.com/tinytag/tinytag,https://github.com/tinytag/tinytag,MIT,2014-01-27 15:27:01.000,2024-10-20 22:08:45.000000,2024-10-20 22:07:58,610.0,45.0,101.0,23.0,112.0,15.0,112.0,696.0,Python library for reading audio file metadata.,27.0,28,True,2023-10-26 19:30:36.000,1.10.1,41.0,tinytag,,,,,1193.0,1080.0,https://pypi.org/project/tinytag,2023-10-26 19:30:36.000,113.0,26740.0,26740.0,,,,,,,,3.0,,4.0,,tinytag/tinytag,,,,,,,,,,,,,,,, +407,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,,58.0,14.0,207.0,12.0,187.0,341.0,"PyStan, a Python interface to Stan, a platform for statistical modeling. Documentation: https://pystan.readthedocs.io.",14.0,28,True,2024-07-03 17:04:15.000,3.10.0,73.0,pystan,conda-forge/pystan,,,,10229.0,10068.0,https://pypi.org/project/pystan,2024-07-03 17:04:15.000,161.0,739995.0,772013.0,https://anaconda.org/conda-forge/pystan,2023-06-16 13:14:39.735,2913720.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +408,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,,1816.0,207.0,74.0,113.0,37.0,10596.0,A text file containing 479k English words for all your dictionary/word-based projects e.g: auto-completion /..,32.0,27,True,2023-05-24 15:11:00.531,2.0.1,9.0,english-words,,,,,16.0,2.0,https://pypi.org/project/english-words,2023-05-24 15:11:00.531,14.0,193983.0,193983.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +409,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,,1378.0,425.0,51.0,104.0,88.0,10544.0,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'],31.0,21.0,https://pypi.org/project/dopamine-rl,2024-05-06 20:38:27.000,10.0,42601.0,42601.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +410,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,,1523.0,132.0,51.0,163.0,141.0,7898.0,A PyTorch implementation of EfficientNet.,24.0,27,False,2021-04-15 15:17:23.000,0.7.1,13.0,efficientnet-pytorch,,,,['pytorch'],73.0,1.0,https://pypi.org/project/efficientnet-pytorch,2021-04-15 15:17:23.000,72.0,204026.0,281167.0,,,,,,,,2.0,4242770.0,,,,,,,,,,,,,,,,,,, +411,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,,1609.0,458.0,699.0,33.0,441.0,7330.0,Deep Learning and Reinforcement Learning Library for Scientists and Engineers.,136.0,27,False,2022-02-15 02:05:47.000,2.2.5,84.0,tensorlayer,,,,['tensorflow'],11.0,,https://pypi.org/project/tensorlayer,2022-02-15 02:05:47.000,11.0,4451.0,4476.0,,,,,,,,2.0,2478.0,,,,,,,,,,,,,,,,,,, +412,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,,1356.0,350.0,14.0,42.0,66.0,6419.0,Python library for processing Chinese text.,8.0,27,False,2015-09-27 16:35:23.000,0.12.3,17.0,snownlp,,,,,1442.0,1434.0,https://pypi.org/project/snownlp,2015-09-27 16:35:23.000,8.0,26059.0,26059.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +413,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,,1586.0,627.0,2111.0,453.0,1338.0,6338.0,"Numenta Platform for Intelligent Computing is an implementation of Hierarchical Temporal Memory (HTM), a theory of..",123.0,27,False,2018-06-01 15:39:25.550,1.0.5,53.0,nupic,,,,,21.0,21.0,https://pypi.org/project/nupic,2016-09-01 21:30:21.000,,4203.0,4203.0,,,,,,,,3.0,13.0,,,numenta/nupic-legacy,,,,,,,,,,,,,,,, +414,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 08:16:49,252.0,1.0,945.0,53.0,57.0,76.0,108.0,4509.0,Pretrained Pytorch face detection (MTCNN) and facial recognition (InceptionResnet) models.,18.0,27,True,2024-04-29 17:50:14.000,2.6.0,33.0,facenet-pytorch,,,,['pytorch'],2368.0,2317.0,https://pypi.org/project/facenet-pytorch,2024-04-29 17:50:14.000,51.0,72512.0,95513.0,,,,,,,,3.0,1357065.0,,,,,,,,,,,,,,,,,,, +415,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,,999.0,147.0,31.0,52.0,77.0,4439.0,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,,,,9495.0,9398.0,https://pypi.org/project/vadersentiment,2020-05-22 15:07:00.000,97.0,344946.0,345291.0,https://anaconda.org/conda-forge/vadersentiment,2023-06-16 19:25:16.902,14867.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +416,yellowbrick,DistrictDataLabs/yellowbrick,interpretability,,https://github.com/DistrictDataLabs/yellowbrick,https://github.com/DistrictDataLabs/yellowbrick,Apache-2.0,2016-05-18 14:12:17.000,2024-09-27 16:58:57.000000,2023-07-05 18:14:28,901.0,,554.0,103.0,618.0,98.0,608.0,4284.0,Visual analysis and diagnostic tools to facilitate machine learning model selection.,113.0,27,False,2022-08-21 12:49:43.000,1.5,24.0,yellowbrick,conda-forge/yellowbrick,,,['sklearn'],105.0,,https://pypi.org/project/yellowbrick,2022-08-21 16:11:55.287,105.0,385260.0,386951.0,https://anaconda.org/conda-forge/yellowbrick,2023-06-16 19:21:13.554,84584.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +417,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,,412.0,37.0,56.0,138.0,43.0,4012.0,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'],16521.0,16386.0,https://pypi.org/project/torchsummary,2018-09-26 05:07:28.000,135.0,212905.0,212905.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +418,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,,964.0,282.0,226.0,12.0,356.0,3875.0,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']",5.0,,https://pypi.org/project/tensorflowonspark,2022-04-21 20:05:56.000,5.0,627767.0,628193.0,https://anaconda.org/conda-forge/tensorflowonspark,2023-06-16 16:19:28.736,24753.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +419,Chartify,spotify/chartify,data-viz,,https://github.com/spotify/chartify,https://github.com/spotify/chartify,Apache-2.0,2018-09-17 14:12:05.000,2024-10-16 14:48:03.000000,2024-10-16 14:45:12,235.0,26.0,323.0,89.0,102.0,51.0,32.0,3528.0,Python library that makes it easy for data scientists to create charts.,27.0,27,True,2024-10-16 14:48:03.000,5.0.1,27.0,chartify,conda-forge/chartify,,,,89.0,80.0,https://pypi.org/project/chartify,2024-10-16 14:48:03.000,9.0,4363.0,4833.0,https://anaconda.org/conda-forge/chartify,2023-06-16 16:11:58.064,33415.0,,,,,3.0,,3.0,,,,,,,,,,,,,,,,,, +420,DeepKE,zjunlp/deepke,nlp,,https://github.com/zjunlp/DeepKE,https://github.com/zjunlp/DeepKE,MIT,2018-08-01 01:54:52.000,2024-10-22 08:45:06.000000,2024-10-22 08:45:06,1672.0,20.0,678.0,43.0,28.0,7.0,559.0,3504.0,[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'],24.0,24.0,https://pypi.org/project/deepke,2023-09-21 04:12:03.000,,5436.0,5436.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +421,pomegranate,jmschrei/pomegranate,probabilistics,,https://github.com/jmschrei/pomegranate,https://github.com/jmschrei/pomegranate,MIT,2014-11-24 18:36:58.000,2024-10-18 19:28:12.000000,2024-10-18 19:27:15,995.0,2.0,589.0,95.0,338.0,20.0,761.0,3364.0,"Fast, flexible and easy to use probabilistic modelling in Python.",75.0,27,True,2024-10-18 19:28:12.000,1.1.1,77.0,pomegranate,conda-forge/pomegranate,,,,59.0,,https://pypi.org/project/pomegranate,2024-10-18 19:28:12.000,59.0,25759.0,29088.0,https://anaconda.org/conda-forge/pomegranate,2023-12-10 17:04:41.093,176462.0,,,,,3.0,,-2.0,,,,,,,,,,,,,,,,,, +422,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,,1139.0,165.0,215.0,49.0,146.0,3335.0,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,,,,720.0,715.0,https://pypi.org/project/alphalens,2020-04-27 21:03:10.000,5.0,2920.0,3197.0,https://anaconda.org/conda-forge/alphalens,2023-06-16 16:09:06.563,22236.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +423,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,,381.0,38.0,522.0,60.0,217.0,2943.0,"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,,,,319.0,308.0,https://pypi.org/project/textattack,2024-03-11 02:20:29.000,11.0,6886.0,7062.0,https://anaconda.org/conda-forge/textattack,2023-06-16 19:22:50.186,8664.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +424,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,,277.0,53.0,21.0,45.0,97.0,2936.0,"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,,,,2625.0,2595.0,https://pypi.org/project/sweetviz,2023-11-29 13:27:52.000,30.0,77504.0,78300.0,https://anaconda.org/conda-forge/sweetviz,2023-12-04 12:10:57.449,35065.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +425,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,,758.0,182.0,75.0,21.0,565.0,2823.0,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,,,,44.0,,https://pypi.org/project/ib_insync,2022-11-21 09:32:01.715,44.0,48734.0,49496.0,https://anaconda.org/conda-forge/ib-insync,2023-06-16 16:16:07.159,48033.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +426,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,,425.0,46.0,366.0,27.0,350.0,2748.0,"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,,,,650.0,636.0,https://pypi.org/project/foolbox,2024-03-04 20:59:17.000,14.0,7691.0,7988.0,https://anaconda.org/conda-forge/foolbox,2023-06-16 19:20:41.396,15157.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +427,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,,256.0,27.0,1132.0,77.0,224.0,2632.0,Database system for AI-powered apps.,73.0,27,True,2023-11-19 16:35:30.000,0.3.9,45.0,evadb,,,,['pytorch'],149.0,149.0,https://pypi.org/project/evadb,2023-11-19 16:35:24.000,,3562.0,18958.0,,,,,,,,3.0,415712.0,,,georgia-tech-db/evadb,,,,,,,,,,,,,,,, +428,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 16:21:43.000,2024-10-13 18:48:52.000000,2024-10-13 18:48:52,141.0,12.0,336.0,30.0,329.0,45.0,341.0,2556.0,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'],125.0,113.0,https://pypi.org/project/adapter-transformers,2024-07-07 11:49:43.000,12.0,32305.0,32305.0,,,,,,,,3.0,,,,adapter-hub/adapters,,,,,,,,,,,,,,,, +429,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,,719.0,166.0,94.0,136.0,358.0,2487.0,An Algorithmic Trading Library for Crypto-Assets in Python.,152.0,27,False,2018-11-11 16:46:28.000,0.5.21,52.0,enigma-catalyst,,,,,29.0,27.0,https://pypi.org/project/enigma-catalyst,2018-11-11 16:46:28.000,2.0,3161.0,3161.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +430,alibi-detect,SeldonIO/alibi-detect,others,,https://github.com/SeldonIO/alibi-detect,https://github.com/SeldonIO/alibi-detect,Intel,2019-10-07 13:29:13.000,2024-10-16 05:57:04.000000,2024-10-16 05:57:02,728.0,1.0,223.0,41.0,547.0,136.0,235.0,2226.0,"Algorithms for outlier, adversarial and drift detection.",24.0,27,False,2024-04-17 16:12:46.000,0.12.0,38.0,alibi-detect,,,,,491.0,484.0,https://pypi.org/project/alibi-detect,2024-04-17 16:12:46.000,7.0,77739.0,77739.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +431,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,,255.0,87.0,124.0,33.0,230.0,2212.0,"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,,,,1942.0,1876.0,https://pypi.org/project/textacy,2023-04-02 23:06:15.139,66.0,31225.0,33087.0,https://anaconda.org/conda-forge/textacy,2023-06-16 13:22:44.862,165746.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +432,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,,317.0,63.0,38.0,97.0,160.0,2177.0,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'],387.0,381.0,https://pypi.org/project/hyperas,2019-02-28 09:16:54.000,6.0,14309.0,14309.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +433,Pillow-SIMD,uploadcare/pillow-simd,image,,https://github.com/uploadcare/pillow-simd,https://github.com/uploadcare/pillow-simd,PIL,2014-11-12 15:33:02.000,2024-10-07 11:50:22.000000,2024-09-23 17:14:22,14660.0,13.0,86.0,42.0,59.0,13.0,78.0,2165.0,The friendly PIL fork.,435.0,27,False,,,72.0,pillow-simd,,,,,65.0,,https://pypi.org/project/pillow-simd,2024-09-23 18:27:59.000,65.0,40139.0,40139.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +434,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,,213.0,36.0,1081.0,25.0,496.0,1743.0,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'],306.0,301.0,https://pypi.org/project/lightning-flash,2022-05-11 18:17:54.000,5.0,4011.0,4612.0,https://anaconda.org/conda-forge/lightning-flash,2023-07-04 02:12:18.993,22874.0,,,,,2.0,,,,Lightning-Universe/lightning-flash,,,,,,,,,,,,,,,, +435,cuGraph,rapidsai/cugraph,gpu-utilities,,https://github.com/rapidsai/cugraph,https://github.com/rapidsai/cugraph,Apache-2.0,2018-11-15 18:07:11.000,2024-10-24 02:06:23.000000,2024-10-23 19:49:59,6633.0,132.0,300.0,45.0,2957.0,180.0,1575.0,1701.0,cuGraph - RAPIDS Graph Analytics Library.,117.0,27,True,2024-10-09 20:36:36.000,24.10.00,40.0,cugraph,conda-forge/libcugraph,,,,4.0,,https://pypi.org/project/cugraph,2020-06-01 20:09:06.000,4.0,295.0,869.0,https://anaconda.org/conda-forge/libcugraph,2023-06-16 19:25:39.870,24149.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +436,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,,312.0,73.0,742.0,58.0,168.0,1481.0,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,,,,,412.0,410.0,https://pypi.org/project/chainercv,2019-06-12 11:55:40.000,2.0,2806.0,2806.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +437,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,,330.0,49.0,44.0,100.0,114.0,1391.0,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'],582.0,574.0,https://pypi.org/project/keras-ocr,2023-11-06 16:35:44.000,8.0,30638.0,65938.0,https://anaconda.org/anaconda/keras-ocr,2023-06-16 19:23:39.693,335.0,,,,,3.0,1729363.0,,,,,,,,,,,,,,,,,,, +438,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 11:43:40,1753.0,1.0,202.0,43.0,258.0,68.0,213.0,1326.0,Python audio and music signal processing library.,24.0,27,True,2018-11-14 14:57:41.000,0.16.1,11.0,madmom,,,,,467.0,440.0,https://pypi.org/project/madmom,2018-11-14 14:56:22.000,27.0,2717.0,2717.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +439,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,,402.0,71.0,89.0,36.0,26.0,1296.0,Common financial risk and performance metrics. Used by zipline and pyfolio.,23.0,27,False,2020-10-13 21:29:19.000,0.5.5,21.0,empyrical,conda-forge/empyrical,,,,1528.0,1472.0,https://pypi.org/project/empyrical,2020-10-13 21:29:19.000,56.0,23567.0,23939.0,https://anaconda.org/conda-forge/empyrical,2023-06-16 16:07:55.979,29817.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +440,scikit-lego,koaning/scikit-lego,sklearn-utils,,https://github.com/koaning/scikit-lego,https://github.com/koaning/scikit-lego,MIT,2019-01-21 15:30:15.000,2024-10-24 13:57:34.000000,2024-09-23 20:28:19,536.0,7.0,115.0,25.0,387.0,32.0,286.0,1265.0,Extra blocks for scikit-learn pipelines.,67.0,27,True,2024-07-10 14:32:19.000,0.9.1,52.0,scikit-lego,conda-forge/scikit-lego,,,['sklearn'],174.0,163.0,https://pypi.org/project/scikit-lego,2024-07-10 14:08:28.000,11.0,30537.0,31612.0,https://anaconda.org/conda-forge/scikit-lego,2024-07-10 21:13:14.463,57017.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +441,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,,175.0,25.0,36.0,1.0,116.0,1250.0,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'],1705.0,1684.0,https://pypi.org/project/fancyimpute,2021-10-21 17:50:40.000,21.0,95831.0,95831.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +442,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,,148.0,34.0,215.0,118.0,152.0,1240.0,Real-time stream processing for python.,48.0,27,False,2022-07-27 18:09:03.803,0.6.4,17.0,streamz,conda-forge/streamz,,,,554.0,497.0,https://pypi.org/project/streamz,2022-07-27 18:09:03.803,57.0,148102.0,160835.0,https://anaconda.org/conda-forge/streamz,2023-06-16 13:22:22.238,1082363.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +443,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,,250.0,41.0,39.0,76.0,591.0,1168.0,"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,,,,777.0,745.0,https://pypi.org/project/pyclustering,2020-11-25 22:41:20.000,32.0,29782.0,31583.0,https://anaconda.org/conda-forge/pyclustering,2023-11-16 19:00:50.847,91595.0,,,,,3.0,604.0,,,,,,,,,,,,,,,,,,, +444,TensorFlow Transform,tensorflow/transform,tensorflow-utils,,https://github.com/tensorflow/transform,https://github.com/tensorflow/transform,Apache-2.0,2017-02-10 00:36:53.000,2024-10-21 20:34:50.000000,2024-10-21 20:34:49,942.0,6.0,211.0,58.0,103.0,45.0,174.0,985.0,Input pipeline framework.,29.0,27,True,2024-04-24 22:55:08.000,1.15.0,57.0,tensorflow-transform,,,,['tensorflow'],18.0,,https://pypi.org/project/tensorflow-transform,2024-04-24 22:55:08.000,18.0,580468.0,580468.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +445,Sentinelsat,sentinelsat/sentinelsat,geospatial-data,,https://github.com/sentinelsat/sentinelsat,https://github.com/sentinelsat/sentinelsat,GPL-3.0,2015-05-22 20:32:26.000,2024-10-02 09:22:49.000000,2024-02-29 13:41:11,1144.0,,236.0,61.0,249.0,22.0,367.0,983.0,Search and download Copernicus Sentinel satellite images.,44.0,27,False,2023-03-10 17:53:00.587,1.2.1,41.0,sentinelsat,conda-forge/sentinelsat,,,,624.0,590.0,https://pypi.org/project/sentinelsat,2017-03-06 02:33:09.000,34.0,26366.0,27054.0,https://anaconda.org/conda-forge/sentinelsat,2023-06-16 19:22:55.678,32908.0,,,,,3.0,317.0,,,,,,,,,,,,,,,,,,, +446,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,,174.0,33.0,86.0,88.0,123.0,921.0,A scikit-learn based module for multi-label et. al. classification.,28.0,27,False,2018-12-10 16:24:47.000,0.2.0,7.0,scikit-multilearn,,,,['sklearn'],1813.0,1788.0,https://pypi.org/project/scikit-multilearn,2018-12-10 16:24:47.000,25.0,60551.0,60551.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +447,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,,81.0,12.0,50.0,22.0,53.0,796.0,pySBD (Python Sentence Boundary Disambiguation) is a rule-based sentence boundary detection that works out-of-the-box.,6.0,27,False,2021-02-11 16:42:37.000,0.3.4,15.0,pysbd,conda-forge/pysbd,,,,4216.0,4139.0,https://pypi.org/project/pysbd,2021-02-11 16:36:33.000,77.0,971082.0,971276.0,https://anaconda.org/conda-forge/pysbd,2023-06-16 19:27:37.870,6997.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +448,pyRiemann,pyRiemann/pyRiemann,ml-frameworks,,https://github.com/pyRiemann/pyRiemann,https://github.com/pyRiemann/pyRiemann,BSD-3-Clause,2015-04-19 16:01:44.000,2024-10-22 11:59:56.000000,2024-10-22 11:59:56,632.0,10.0,164.0,31.0,225.0,5.0,103.0,634.0,Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python.,35.0,27,True,2024-10-03 19:57:53.000,0.7,13.0,pyriemann,conda-forge/pyriemann,,https://pyriemann.readthedocs.io/en/latest/,['sklearn'],429.0,401.0,https://pypi.org/project/pyriemann,2024-10-03 19:58:27.000,28.0,40282.0,40579.0,https://anaconda.org/conda-forge/pyriemann,2024-10-04 03:48:24.751,8330.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +449,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'],8067.0,7928.0,https://pypi.org/project/sklearn-crfsuite,2024-06-18 11:08:22.000,139.0,245836.0,246592.0,https://anaconda.org/conda-forge/sklearn-crfsuite,2023-06-16 19:18:37.991,40858.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +450,NIPY,nipy/nipy,medical-data,,https://github.com/nipy/nipy,https://github.com/nipy/nipy,,2010-05-02 10:00:33.000,2024-10-06 20:12:28.000000,2024-10-06 19:51:01,6795.0,77.0,145.0,36.0,412.0,37.0,140.0,383.0,Neuroimaging in Python FMRI analysis package.,71.0,27,False,2024-10-06 19:42:32.000,0.6.1,9.0,nipy,conda-forge/nipy,,,,260.0,236.0,https://pypi.org/project/nipy,2024-10-06 19:42:32.000,24.0,7899.0,50194.0,https://anaconda.org/conda-forge/nipy,2024-07-28 17:27:34.085,126885.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +451,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,,1206.0,185.0,213.0,30.0,534.0,9327.0,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,,,,,,21.0,21.0,,,,,302.0,,,,,,,,3.0,13591.0,,,,,,,,,,,,,,,,,,, +452,Trax,google/trax,others,,https://github.com/google/trax,https://github.com/google/trax,Apache-2.0,2019-10-05 15:09:14.000,2024-09-10 20:43:39.000000,2024-09-10 20:43:30,1626.0,6.0,814.0,141.0,1571.0,122.0,125.0,8077.0,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,,,,,180.0,179.0,https://pypi.org/project/trax,2021-10-26 20:29:00.538,1.0,5841.0,5841.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +453,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 07:30:27,13839.0,25.0,1545.0,136.0,3616.0,64.0,1978.0,5703.0,An Industrial Grade Federated Learning Framework.,101.0,26,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,,,,,,,,,,,,,,,,,,,, +454,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,,599.0,142.0,31.0,69.0,55.0,5591.0,Extract Keywords from sentence or Replace keywords in sentences.,7.0,26,False,,,18.0,flashtext,conda-forge/flashtext,,,,1862.0,1806.0,https://pypi.org/project/flashtext,2018-02-16 05:24:17.000,56.0,1647744.0,1648133.0,https://anaconda.org/conda-forge/flashtext,2023-06-16 19:20:49.106,19869.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +455,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,,867.0,123.0,64.0,136.0,74.0,5065.0,Image augmentation library in Python for machine learning.,23.0,26,False,2023-03-29 07:06:01.465,0.2.12,24.0,Augmentor,,,,,841.0,829.0,https://pypi.org/project/Augmentor,2022-04-27 09:29:23.000,12.0,18109.0,18109.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +456,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,,658.0,158.0,130.0,83.0,101.0,4665.0,A collection of infrastructure and tools for research in neural network interpretability.,40.0,26,False,2021-03-19 16:01:00.000,0.3.10,17.0,lucid,,,,['tensorflow'],790.0,784.0,https://pypi.org/project/lucid,2021-03-19 16:01:00.000,6.0,1239.0,1239.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +457,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,,1021.0,243.0,218.0,52.0,203.0,4539.0,"An open source reinforcement learning framework for training, evaluating, and deploying robust trading agents.",61.0,26,True,2021-05-10 18:04:30.000,1.0.3,27.0,tensortrade,conda-forge/tensortrade,,,,65.0,64.0,https://pypi.org/project/tensortrade,2021-05-10 18:00:35.000,1.0,2009.0,2106.0,https://anaconda.org/conda-forge/tensortrade,2023-06-16 19:25:40.006,4077.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +458,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,,740.0,58.0,1015.0,187.0,742.0,4325.0,"OpenMMLab Text Detection, Recognition and Understanding Toolbox.",90.0,26,True,2023-07-04 07:12:41.567,1.0.1,20.0,mmocr,,,,['pytorch'],173.0,169.0,https://pypi.org/project/mmocr,2022-05-05 14:21:18.000,4.0,4849.0,4849.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +459,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,,511.0,134.0,649.0,65.0,198.0,3891.0,Snips Python library to extract meaning from text.,22.0,26,False,2020-01-15 10:13:17.000,0.20.2,58.0,snips-nlu,,,,,13.0,,https://pypi.org/project/snips-nlu,2020-01-15 10:13:17.000,13.0,10676.0,10676.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +460,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,,897.0,176.0,386.0,34.0,430.0,3837.0,"Facilitating the design, comparison and sharing of deep text matching models.",37.0,26,False,2019-10-24 13:09:11.000,2.2.0,5.0,matchzoo,,,,['tensorflow'],18.0,18.0,https://pypi.org/project/matchzoo,2019-10-24 13:09:11.000,,210.0,210.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +461,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 20:26:47,2116.0,2.0,532.0,141.0,240.0,42.0,635.0,3298.0,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'],459.0,455.0,https://pypi.org/project/tensorforce,2021-08-30 20:13:45.000,4.0,1588.0,1588.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +462,Towhee,towhee-io/towhee,ml-frameworks,,https://github.com/towhee-io/towhee,https://github.com/towhee-io/towhee,Apache-2.0,2021-07-13 08:28:50.000,2024-10-18 00:01:12.000000,2024-10-18 00:01:11,1586.0,10.0,246.0,29.0,2020.0,6.0,659.0,3208.0,Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.,38.0,26,True,2023-12-05 02:33:36.000,1.1.3,26.0,towhee,,,,,,,https://pypi.org/project/towhee,2023-12-04 07:25:10.000,,15756.0,15835.0,,,,,,,,3.0,2713.0,,,,,,,,,,,,,,,,,,, +463,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,,1050.0,215.0,3649.0,429.0,1111.0,3029.0,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,shogun/shogun,,,,,,,,,1705.0,https://anaconda.org/conda-forge/shogun,2023-06-16 13:22:38.816,147598.0,https://hub.docker.com/r/shogun/shogun,2019-01-31 13:45:10.435327,1.0,1516.0,3.0,,,,,,,,,,shogun,,,,,,,,,, +464,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,,295.0,33.0,476.0,54.0,30.0,3028.0,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'],86.0,,https://pypi.org/project/torch_optimizer,2021-10-31 03:00:19.000,86.0,154155.0,154434.0,https://anaconda.org/conda-forge/torch-optimizer,2023-06-16 19:25:40.043,11744.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +465,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,,342.0,30.0,322.0,82.0,39.0,2995.0,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'],1122.0,1121.0,https://pypi.org/project/lazypredict,2022-09-28 08:51:19.531,1.0,17531.0,17626.0,https://anaconda.org/conda-forge/lazypredict,2023-06-16 19:27:14.287,3630.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +466,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,,233.0,50.0,482.0,45.0,70.0,2809.0,"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,,,,,269.0,266.0,https://pypi.org/project/m2cgen,2022-04-26 01:24:34.000,3.0,29409.0,29410.0,,,,,,,,2.0,85.0,,,,,,,,,,,,,,,,,,, +467,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,,223.0,64.0,42.0,17.0,24.0,2782.0,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,,,,1173.0,1168.0,https://pypi.org/project/knockknock,2020-03-16 14:30:23.000,5.0,68934.0,69206.0,https://anaconda.org/conda-forge/knockknock,2023-06-16 16:18:44.705,16320.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +468,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,,329.0,69.0,167.0,164.0,113.0,2758.0,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,,,,61.0,,https://pypi.org/project/eli5,2022-05-11 09:37:12.000,61.0,179623.0,181484.0,https://anaconda.org/conda-forge/eli5,2023-06-16 13:18:29.838,165695.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +469,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,,473.0,97.0,43.0,89.0,240.0,2741.0,Learning to Rank in TensorFlow.,36.0,26,True,2024-03-18 21:00:38.000,0.5.5,23.0,tensorflow_ranking,,,,['tensorflow'],15.0,,https://pypi.org/project/tensorflow_ranking,2024-03-18 21:00:38.000,15.0,111102.0,111102.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +470,TabNet,dreamquark-ai/tabnet,pytorch-utils,,https://github.com/dreamquark-ai/tabnet,https://github.com/dreamquark-ai/tabnet,MIT,2019-10-17 11:17:32.000,2024-10-23 15:36:38.000000,2023-07-23 14:42:27,191.0,,484.0,38.0,250.0,52.0,290.0,2621.0,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'],11.0,,https://pypi.org/project/pytorch-tabnet,2023-07-23 13:26:57.000,11.0,42023.0,42269.0,https://anaconda.org/conda-forge/pytorch-tabnet,2023-12-20 04:10:30.919,8367.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +471,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,,831.0,90.0,287.0,200.0,103.0,2435.0,"A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and..",73.0,26,True,2024-04-08 20:03:12.000,0.6.1,12.0,aif360,conda-forge/aif360,,,,530.0,498.0,https://pypi.org/project/aif360,2024-04-08 20:03:12.000,32.0,39908.0,40220.0,https://anaconda.org/conda-forge/aif360,2024-04-09 06:44:48.814,15324.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +472,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,,249.0,58.0,659.0,147.0,225.0,2399.0,Algorithms for explaining machine learning models.,22.0,26,False,2024-04-18 15:30:25.000,0.9.6,34.0,alibi,,,,,688.0,663.0,https://pypi.org/project/alibi,2024-04-18 15:29:10.000,25.0,26919.0,26919.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +473,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,,338.0,77.0,55.0,170.0,68.0,2311.0,Multilingual text (NLP) processing toolkit.,26.0,26,False,2021-12-15 16:11:38.716,15.5.1,9.0,polyglot,,,,,1425.0,1376.0,https://pypi.org/project/polyglot,2021-12-15 16:11:38.716,49.0,43376.0,43376.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +474,scattertext,JasonKessler/scattertext,nlp,,https://github.com/JasonKessler/scattertext,https://github.com/JasonKessler/scattertext,Apache-2.0,2016-07-21 01:47:12.000,2024-09-23 05:35:47.000000,2024-09-23 05:24:01,389.0,1.0,289.0,55.0,14.0,22.0,80.0,2240.0,Beautiful visualizations of how language differs among document types.,14.0,26,True,2024-09-23 05:35:47.000,0.2.2,151.0,scattertext,conda-forge/scattertext,,,,639.0,634.0,https://pypi.org/project/scattertext,2024-09-23 05:35:47.000,5.0,22329.0,23488.0,https://anaconda.org/conda-forge/scattertext,2023-06-16 13:23:09.869,99700.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +475,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,,251.0,66.0,63.0,41.0,198.0,2146.0,Python library for Representation Learning on Knowledge Graphs https://docs.ampligraph.org.,21.0,26,True,2024-02-28 15:44:03.000,2.1.0,15.0,ampligraph,,,,['tensorflow'],58.0,56.0,https://pypi.org/project/ampligraph,2024-02-26 17:12:26.000,2.0,2927.0,2927.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +476,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,,336.0,64.0,160.0,13.0,92.0,2135.0,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,,,,,749.0,730.0,https://pypi.org/project/pytextrank,2024-02-21 23:17:37.000,19.0,65636.0,65636.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +477,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,,463.0,38.0,43.0,64.0,58.0,2065.0,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'],2323.0,2309.0,https://pypi.org/project/efficientnet,2020-09-15 16:26:00.000,14.0,117452.0,121471.0,https://anaconda.org/anaconda/efficientnet,2024-04-08 21:03:52.579,526.0,,,,,3.0,260544.0,,,,,,,,,,,,,,,,,,, +478,TensorFlow Privacy,tensorflow/privacy,privacy-ml,,https://github.com/tensorflow/privacy,https://github.com/tensorflow/privacy,Apache-2.0,2018-12-21 18:46:46.000,2024-10-24 12:14:44.000000,2024-09-20 02:51:40,888.0,12.0,444.0,60.0,358.0,117.0,92.0,1932.0,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'],21.0,,https://pypi.org/project/tensorflow-privacy,2024-02-14 19:08:50.000,21.0,23694.0,23696.0,,,,,,,,2.0,173.0,,,,,,,,,,,,,,,,,,, +479,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,,310.0,56.0,1313.0,234.0,810.0,1874.0,A toolkit for reproducible reinforcement learning research.,79.0,26,False,2021-03-23 22:18:36.000,2021.3.0,21.0,garage,,,,['tensorflow'],119.0,115.0,https://pypi.org/project/garage,2021-03-23 22:18:36.000,4.0,1645.0,1645.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +480,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 13:01:11,360.0,15.0,307.0,1.0,1.0,1.0,,1843.0,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,,,,159.0,,https://pypi.org/project/feature_engine,2024-08-31 13:22:28.000,159.0,219307.0,220478.0,https://anaconda.org/conda-forge/feature_engine,2024-09-01 13:51:20.563,58593.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +481,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,,160.0,60.0,68.0,67.0,130.0,1824.0,A Python toolbox for gaining geometric insights into high-dimensional data.,22.0,26,True,2022-02-12 03:29:55.000,0.8.0,21.0,hypertools,,,,,486.0,484.0,https://pypi.org/project/hypertools,2022-02-12 02:43:24.000,2.0,2362.0,2362.0,,,,,,,,3.0,51.0,,,,,,,,,,,,,,,,,,, +482,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,,288.0,29.0,578.0,93.0,722.0,1768.0,Avalanche: an End-to-End Library for Continual Learning based on PyTorch.,80.0,26,True,2024-02-27 17:02:40.000,0.5.0,8.0,avalanche-lib,,,,,110.0,107.0,https://pypi.org/project/avalanche-lib,2024-02-27 16:52:08.000,3.0,2847.0,2847.0,,,,,,,,3.0,35.0,,,,,,,,,,,,,,,,,,, +483,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,,161.0,25.0,81.0,47.0,35.0,1764.0,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,,,,746.0,701.0,https://pypi.org/project/pyts,2023-06-18 12:36:11.801,45.0,137371.0,138136.0,https://anaconda.org/conda-forge/pyts,2023-06-18 16:28:23.633,27549.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +484,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,,196.0,33.0,20.0,3.0,91.0,1719.0,"Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators..",17.0,26,True,2024-06-10 12:09:16.000,0.1.905,90.0,autoviz,conda-forge/autoviz,,,,781.0,770.0,https://pypi.org/project/autoviz,2024-06-10 12:09:16.000,11.0,42706.0,44445.0,https://anaconda.org/conda-forge/autoviz,2024-04-26 17:50:17.078,66119.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +485,TNT,pytorch/tnt,ml-experiments,,https://github.com/pytorch/tnt,https://github.com/pytorch/tnt,BSD-3-Clause,2016-12-10 11:49:58.000,2024-10-20 16:35:57.000000,2024-10-20 16:29:35,1018.0,55.0,271.0,43.0,861.0,79.0,66.0,1661.0,A lightweight library for PyTorch training tools and utilities.,136.0,26,True,2018-07-29 23:16:03.000,0.0.4,3.0,torchnet,,,,['pytorch'],24.0,,https://pypi.org/project/torchnet,2018-07-29 23:16:03.000,24.0,6276.0,6276.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +486,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,,282.0,51.0,87.0,24.0,191.0,1598.0,"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'],681.0,662.0,https://pypi.org/project/gplearn,2022-05-03 10:47:30.000,19.0,22230.0,22383.0,https://anaconda.org/conda-forge/gplearn,2023-06-16 19:20:25.471,7960.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +487,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,,309.0,28.0,380.0,56.0,155.0,1572.0,Paddle Graph Learning (PGL) is an efficient and flexible graph learning framework based on PaddlePaddle.,31.0,26,False,2023-09-26 07:49:38.000,2.2.6,21.0,pgl,,,,['paddle'],62.0,61.0,https://pypi.org/project/pgl,2023-09-26 07:49:38.000,1.0,7890.0,7890.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +488,imodels,csinva/imodels,interpretability,,https://github.com/csinva/imodels,https://github.com/csinva/imodels,MIT,2019-07-04 15:38:48.000,2024-10-16 18:33:17.000000,2024-10-16 18:33:15,1068.0,9.0,122.0,24.0,116.0,36.0,57.0,1387.0,"Interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compatible).",24.0,26,True,2024-10-15 14:24:34.000,2.0.0,50.0,imodels,,,,,117.0,108.0,https://pypi.org/project/imodels,2024-10-15 14:23:49.000,9.0,31960.0,31960.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +489,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 01:34:48,1970.0,1.0,348.0,31.0,2281.0,86.0,231.0,1370.0,Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and..,43.0,26,True,2024-07-08 18:03:34.000,0.36.0,57.0,raiwidgets,,,,"['pytorch', 'tensorflow', 'jupyter']",6.0,,https://pypi.org/project/raiwidgets,2024-07-08 16:42:42.000,6.0,12118.0,12118.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +490,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,,235.0,34.0,68.0,57.0,206.0,1264.0,A toolbox to iNNvestigate neural networks predictions!.,22.0,26,True,2023-10-12 14:58:48.000,2.1.2,8.0,innvestigate,,,,['tensorflow'],142.0,140.0,https://pypi.org/project/innvestigate,2023-10-12 14:55:59.000,2.0,1336.0,1341.0,,,,,,,,2.0,155.0,,,,,,,,,,,,,,,,,,, +491,hls4ml,fastmachinelearning/hls4ml,model-serialisation,,https://github.com/fastmachinelearning/hls4ml,https://github.com/fastmachinelearning/hls4ml,Apache-2.0,2017-10-25 21:43:56.000,2024-10-24 12:36:44.000000,2024-10-24 12:34:53,2162.0,63.0,388.0,58.0,547.0,176.0,258.0,1255.0,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']",,,https://pypi.org/project/hls4ml,2023-12-19 21:00:58.000,,1985.0,2165.0,https://anaconda.org/conda-forge/hls4ml,2023-06-16 19:22:51.232,8864.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +492,metricflow,transform-data/metricflow,others,,https://github.com/dbt-labs/metricflow,https://github.com/dbt-labs/metricflow,,2022-04-04 18:33:06.000,2024-10-23 23:20:21.000000,2024-10-21 19:44:49,2560.0,89.0,94.0,19.0,1149.0,76.0,237.0,1141.0,"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,,,,,30.0,26.0,https://pypi.org/project/metricflow,2024-07-09 00:14:45.000,4.0,25685.0,25685.0,,,,,,,,3.0,,,,dbt-labs/metricflow,,,,,,,,,,,,,,,, +493,SMAC3,automl/SMAC3,hyperopt,,https://github.com/automl/SMAC3,https://github.com/automl/SMAC3,BSD-1-Clause,2016-08-17 10:58:05.000,2024-10-24 12:28:16.000000,2024-07-24 14:36:04,2074.0,,222.0,42.0,608.0,98.0,449.0,1081.0,SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization.,41.0,26,False,2024-07-24 14:42:30.000,2.2.0,49.0,smac,conda-forge/smac,,,,40.0,,https://pypi.org/project/smac,2024-07-24 14:42:30.000,40.0,22532.0,23112.0,https://anaconda.org/conda-forge/smac,2024-05-16 20:20:11.437,24965.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +494,bambi,bambinos/bambi,probabilistics,,https://github.com/bambinos/bambi,https://github.com/bambinos/bambi,MIT,2016-05-16 03:21:00.000,2024-09-26 19:00:31.000000,2024-09-26 18:59:07,823.0,8.0,122.0,31.0,425.0,81.0,334.0,1074.0,BAyesian Model-Building Interface (Bambi) in Python.,40.0,26,True,2024-07-10 09:48:04.000,0.14.0,29.0,bambi,conda-forge/bambi,,,,163.0,153.0,https://pypi.org/project/bambi,2024-07-10 09:48:04.000,10.0,35062.0,35895.0,https://anaconda.org/conda-forge/bambi,2024-07-10 16:37:21.380,38348.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +495,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,,261.0,44.0,72.0,104.0,188.0,928.0,Gaussian Process Optimization using GPy.,50.0,26,False,2020-03-19 21:21:18.000,1.2.6,11.0,gpyopt,,,,,574.0,537.0,https://pypi.org/project/gpyopt,2020-03-19 11:37:45.000,37.0,24296.0,24296.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +496,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 15:47:02.000,2024-10-23 23:01:01.000000,2024-10-23 23:00:59,975.0,9.0,170.0,48.0,89.0,37.0,144.0,762.0,Library for exploring and validating machine learning data.,27.0,26,True,2024-10-15 19:51:40.000,1.16.1,48.0,tensorflow-data-validation,,,,"['tensorflow', 'jupyter']",31.0,,https://pypi.org/project/tensorflow-data-validation,2024-10-15 20:20:03.000,31.0,170599.0,170611.0,,,,,,,,3.0,879.0,,,,,,,,,,,,,,,,,,, +497,pyvips,libvips/pyvips,image,,https://github.com/libvips/pyvips,https://github.com/libvips/pyvips,MIT,2017-07-28 16:39:43.000,2024-10-12 13:28:51.000000,2024-10-12 13:28:40,485.0,8.0,49.0,9.0,65.0,191.0,255.0,641.0,python binding for libvips using cffi.,16.0,26,True,2024-04-28 11:19:58.000,2.2.3,26.0,pyvips,conda-forge/pyvips,,,,896.0,819.0,https://pypi.org/project/pyvips,2024-04-28 11:19:58.000,77.0,69695.0,72510.0,https://anaconda.org/conda-forge/pyvips,2024-09-06 03:01:34.001,135162.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +498,quinn,MrPowers/quinn,ml-experiments,,https://github.com/mrpowers-io/quinn,https://github.com/mrpowers-io/quinn,Apache-2.0,2017-09-15 13:02:42.000,2024-10-12 15:09:33.000000,2024-10-12 15:08:21,367.0,15.0,97.0,20.0,150.0,36.0,98.0,632.0,pyspark methods to enhance developer productivity.,32.0,26,True,2024-02-13 12:31:37.000,0.10.3,16.0,quinn,,,,['spark'],93.0,86.0,https://pypi.org/project/quinn,2024-02-13 12:31:37.000,7.0,668366.0,668366.0,,,,,,,,3.0,41.0,,,mrpowers-io/quinn,,,,,,,,,,,,,,,, +499,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 21:02:09.000,2024-10-09 18:57:29.000000,2024-10-09 18:57:29,854.0,8.0,145.0,29.0,96.0,49.0,75.0,619.0,For recording and retrieving metadata associated with ML developer and data scientist workflows.,20.0,26,True,2024-10-01 23:08:54.000,1.16.0,44.0,ml-metadata,,,,,605.0,574.0,https://pypi.org/project/ml-metadata,2024-10-01 23:08:54.000,31.0,80342.0,80382.0,,,,,,,,3.0,2691.0,,,,,,,,,,,,,,,,,,, +500,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,,154.0,18.0,717.0,27.0,208.0,507.0,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,,,,394.0,377.0,https://pypi.org/project/earthpy,2021-10-01 22:51:04.000,17.0,10163.0,11423.0,https://anaconda.org/conda-forge/earthpy,2023-06-16 16:14:50.280,83222.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +501,scikit-posthocs,maximtrp/scikit-posthocs,probabilistics,,https://github.com/maximtrp/scikit-posthocs,https://github.com/maximtrp/scikit-posthocs,MIT,2017-06-22 19:41:37.000,2024-10-24 09:13:26.312000,2024-10-20 09:40:24,539.0,4.0,40.0,5.0,16.0,6.0,56.0,344.0,Multiple Pairwise Comparisons (Post Hoc) Tests in Python.,15.0,26,True,2024-10-20 09:53:20.000,0.10.0,27.0,scikit-posthocs,conda-forge/scikit-posthocs,,,['sklearn'],915.0,861.0,https://pypi.org/project/scikit-posthocs,2024-10-20 09:53:20.000,54.0,83255.0,103566.0,https://anaconda.org/conda-forge/scikit-posthocs,2024-10-24 09:13:26.312,974973.0,,,,,3.0,64.0,,,,,,,,,,,,,,,,,,, +502,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,,801.0,169.0,1588.0,145.0,74.0,6339.0,A natural language modeling framework based on PyTorch.,234.0,25,False,2020-06-08 23:30:58.000,0.3.3,13.0,pytext-nlp,,,,['pytorch'],21.0,21.0,https://pypi.org/project/pytext-nlp,2020-06-08 22:49:33.000,,912.0,917.0,,,,,,,,3.0,406.0,,,,,,,,,,,,,,,,,,, +503,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,,966.0,181.0,328.0,338.0,294.0,5794.0,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,,,,,136.0,136.0,https://pypi.org/project/mmdnn,2020-07-24 06:34:39.000,,917.0,963.0,,,,,,,,3.0,3835.0,,,,,,,,,,,,,,,,,,, +504,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,,924.0,114.0,676.0,146.0,543.0,5490.0,A modular framework for vision & language multimodal research from Facebook AI Research (FAIR).,118.0,25,True,2019-08-26 19:04:21.000,0.3.1,12.0,mmf,,,,['pytorch'],22.0,21.0,https://pypi.org/project/mmf,2020-06-12 22:15:02.000,1.0,2077.0,2077.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +505,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,,990.0,46.0,34.0,66.0,112.0,5253.0,"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'],246.0,231.0,https://pypi.org/project/scikit-opt,2022-01-14 08:49:08.000,15.0,6728.0,6728.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +506,DALI,NVIDIA/DALI,gpu-utilities,,https://github.com/NVIDIA/DALI,https://github.com/NVIDIA/DALI,Apache-2.0,2018-06-01 22:18:01.000,2024-10-24 07:21:11.000000,2024-10-24 07:21:10,3708.0,69.0,619.0,92.0,4072.0,241.0,1407.0,5119.0,A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to..,94.0,25,True,2024-09-30 16:53:23.000,1.42.0,83.0,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +507,AugLy,facebookresearch/AugLy,others,,https://github.com/facebookresearch/AugLy,https://github.com/facebookresearch/AugLy,MIT,2021-06-09 17:57:28.000,2024-10-09 22:24:15.000000,2024-10-09 22:17:48,223.0,5.0,297.0,78.0,179.0,24.0,54.0,4956.0,"A data augmentations library for audio, image, text, and video.",37.0,25,True,2023-12-05 20:52:12.000,1.0.1,18.0,augly,,,,,150.0,146.0,https://pypi.org/project/augly,2023-12-05 20:52:12.000,4.0,4377.0,4377.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +508,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,,749.0,136.0,43.0,141.0,98.0,4941.0,Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines..,19.0,25,False,2020-02-03 01:07:00.000,2.0.0,14.0,textgenrnn,,,,['tensorflow'],1149.0,1133.0,https://pypi.org/project/textgenrnn,2020-02-02 21:16:15.000,16.0,1131.0,1143.0,,,,,,,,3.0,963.0,,,,,,,,,,,,,,,,,,, +509,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.,27.0,25,False,2020-07-09 21:03:28.000,0.9.0,13.0,adanet,,,,['tensorflow'],62.0,60.0,https://pypi.org/project/adanet,2020-07-09 21:03:28.000,2.0,5037.0,5037.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +510,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 04:03:53,4353.0,8.0,609.0,42.0,1013.0,283.0,709.0,3410.0,"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'],2.0,,https://pypi.org/project/recbole,2023-10-31 12:52:34.000,2.0,27989.0,28123.0,https://anaconda.org/aibox/recbole,2023-11-01 15:53:42.380,6319.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +511,Hummingbird,microsoft/hummingbird,model-serialisation,,https://github.com/microsoft/hummingbird,https://github.com/microsoft/hummingbird,MIT,2020-03-12 20:27:03.000,2024-10-17 01:47:47.000000,2024-10-16 18:15:09,479.0,6.0,276.0,51.0,476.0,70.0,261.0,3343.0,Hummingbird compiles trained ML models into tensor computation for faster inference.,40.0,25,True,2024-03-08 20:24:53.000,0.4.11,24.0,hummingbird-ml,conda-forge/hummingbird-ml,,,,7.0,,https://pypi.org/project/hummingbird-ml,2024-03-08 20:21:40.000,7.0,7790.0,8954.0,https://anaconda.org/conda-forge/hummingbird-ml,2024-03-08 22:15:29.532,49529.0,,,,,3.0,705.0,,,,,,,,,,,,,,,,,,, +512,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 17:16:53,181.0,1.0,413.0,156.0,85.0,105.0,101.0,3306.0,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'],24.0,,https://pypi.org/project/pytorchvideo,2022-01-20 00:16:35.000,24.0,18517.0,18517.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +513,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,,817.0,62.0,642.0,133.0,404.0,3261.0,A high-performance distributed training framework for Reinforcement Learning.,45.0,25,True,2023-03-14 02:03:08.557,2.2.1,29.0,parl,,,,['paddle'],131.0,130.0,https://pypi.org/project/parl,2022-05-13 04:46:41.000,1.0,1920.0,1920.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +514,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,,528.0,111.0,73.0,193.0,118.0,3086.0,"High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization..",30.0,25,False,2019-04-25 02:10:05.000,0.4.4,15.0,xlearn,,,,,164.0,152.0,https://pypi.org/project/xlearn,2018-12-04 11:05:06.000,12.0,1420.0,1479.0,,,,,,,,3.0,4718.0,,,,,,,,,,,,,,,,,,, +515,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,,664.0,71.0,25.0,117.0,101.0,2979.0,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'],2978.0,2977.0,https://pypi.org/project/keras-vis,2017-07-06 05:11:22.255,1.0,1619.0,1619.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +516,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,,475.0,97.0,49.0,65.0,254.0,2855.0,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,,,,750.0,729.0,https://pypi.org/project/neuralcoref,2019-04-08 09:56:00.000,21.0,3691.0,4039.0,https://anaconda.org/conda-forge/neuralcoref,2023-06-16 19:17:56.088,18861.0,,,,,3.0,1101.0,,,,,,,,,,,,,,,,,,, +517,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,,179.0,21.0,79.0,112.0,179.0,2852.0,FFCV: Fast Forward Computer Vision (and other ML workloads!).,31.0,25,True,2023-03-05 05:44:00.314,1.0.2,7.0,ffcv,,,,,55.0,54.0,https://pypi.org/project/ffcv,2022-01-28 20:40:22.000,1.0,1136.0,1136.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +518,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,,141.0,28.0,200.0,20.0,73.0,2745.0,HiPlot makes understanding high dimensional data easy.,9.0,25,False,2022-05-31 09:00:35.000,0.1.33,113.0,hiplot,conda-forge/hiplot,,,,480.0,454.0,https://pypi.org/project/hiplot,2022-07-05 08:51:12.000,26.0,56527.0,60277.0,https://anaconda.org/conda-forge/hiplot,2023-06-16 19:18:10.488,210038.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +519,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 01:11:33.000,2024-10-14 19:46:14.000000,2024-10-14 19:46:14,1949.0,6.0,369.0,38.0,94.0,41.0,158.0,2648.0,PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021).,34.0,25,True,2022-09-04 16:37:07.000,0.54.0,46.0,torch-geometric-temporal,,,,['pytorch'],7.0,,https://pypi.org/project/torch-geometric-temporal,2022-09-04 16:10:00.738,7.0,3067.0,3067.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +520,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 16:14:15,696.0,1.0,243.0,35.0,147.0,24.0,146.0,2398.0,Lightweight Python library for adding real-time multi-object tracking to any detector.,31.0,25,True,2023-01-04 21:42:02.301,2.2.0,19.0,norfair,,,,,239.0,230.0,https://pypi.org/project/norfair,2022-05-30 21:14:58.000,9.0,23599.0,23605.0,,,,,,,,3.0,336.0,,,,,,,,,,,,,,,,,,, +521,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,,440.0,64.0,123.0,32.0,350.0,2391.0,Kashgari is a production-level NLP Transfer learning framework built on top of tf.keras for text-labeling and text-..,21.0,25,False,2021-07-04 10:44:36.000,2.0.2,24.0,kashgari-tf,,,,['tensorflow'],72.0,70.0,https://pypi.org/project/kashgari-tf,2019-10-18 07:57:55.000,2.0,866.0,866.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +522,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,,255.0,51.0,98.0,24.0,116.0,2234.0,A Python library that helps data scientists to infer causation rather than observing correlation.,40.0,25,True,2023-06-22 13:11:59.629,0.12.1,20.0,causalnex,,,,"['pytorch', 'sklearn']",136.0,132.0,https://pypi.org/project/causalnex,2023-06-22 13:11:59.629,4.0,11498.0,11498.0,,,,,,,,3.0,,,,mckinsey/causalnex,,,,,,,,,,,,,,,, +523,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,,251.0,56.0,56.0,19.0,50.0,2212.0,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'],749.0,730.0,https://pypi.org/project/pytorch-nlp,2019-11-04 04:35:18.000,19.0,9448.0,9448.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +524,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,,240.0,70.0,21.0,93.0,66.0,2108.0,Open source time series library for Python.,6.0,25,False,2017-11-21 16:27:06.000,0.4.16,36.0,pyflux,,,,,278.0,274.0,https://pypi.org/project/pyflux,2017-11-21 16:27:06.000,4.0,146537.0,146537.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +525,Opik,comet-ml/opik,nlp,,https://github.com/comet-ml/opik,https://github.com/comet-ml/opik,Apache-2.0,2023-05-10 12:57:13.000,2024-10-24 11:08:48.000000,2024-10-24 09:43:40,319.0,319.0,106.0,25.0,439.0,10.0,24.0,1792.0,Open-source end-to-end LLM Development Platform.,23.0,25,True,2024-10-18 10:22:21.000,0.2.2,54.0,opik,,,,,,,https://pypi.org/project/opik,2024-10-23 14:49:33.000,,5522.0,5522.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +526,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,,269.0,27.0,187.0,11.0,390.0,1622.0,Hyperparameter Experiments with TensorFlow and Keras.,23.0,25,True,2024-04-21 09:02:06.000,1.4,18.0,talos,,,,['tensorflow'],199.0,191.0,https://pypi.org/project/talos,2024-04-21 09:02:29.000,8.0,3091.0,3091.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +527,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,,308.0,102.0,49.0,8.0,151.0,1574.0,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']",,,https://pypi.org/project/elephas,2024-08-04 13:39:34.000,,41186.0,41434.0,https://anaconda.org/conda-forge/elephas,2023-06-16 16:16:35.554,15423.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +528,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,,214.0,43.0,12.0,4.0,51.0,1565.0,"Pretrained EfficientNet, EfficientNet-Lite, MixNet, MobileNetV3 / V2, MNASNet A1 and B1, FBNet, Single-Path NAS.",5.0,25,True,2021-07-08 19:05:05.000,1.0.2,10.0,geffnet,,,,['pytorch'],265.0,261.0,https://pypi.org/project/geffnet,2021-07-08 19:05:05.000,4.0,161107.0,161107.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,, +529,torch-scatter,rusty1s/pytorch_scatter,pytorch-utils,,https://github.com/rusty1s/pytorch_scatter,https://github.com/rusty1s/pytorch_scatter,MIT,2017-12-16 16:34:23.000,2024-10-08 05:32:52.462000,2024-08-15 08:12:47,1036.0,1.0,179.0,17.0,74.0,30.0,362.0,1548.0,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'],152.0,,https://pypi.org/project/torch-scatter,2023-10-06 08:49:07.000,152.0,44589.0,54452.0,https://anaconda.org/conda-forge/pytorch_scatter,2024-10-08 05:32:52.462,512918.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +530,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 19:34:12,297.0,2.0,231.0,46.0,186.0,53.0,121.0,1396.0,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'],416.0,409.0,https://pypi.org/project/metric-learn,2023-10-09 04:53:59.000,7.0,5401.0,5663.0,https://anaconda.org/conda-forge/metric-learn,2023-10-09 05:53:11.819,13372.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +531,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,,404.0,90.0,165.0,103.0,224.0,1367.0,[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'],46.0,46.0,https://pypi.org/project/niftynet,2019-10-10 10:59:33.000,,476.0,476.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +532,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'],1712.0,1696.0,https://pypi.org/project/livelossplot,2022-04-04 16:14:08.000,16.0,15276.0,15276.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +533,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,,296.0,55.0,63.0,16.0,111.0,1290.0,Supply a wrapper ``StockDataFrame`` based on the ``pandas.DataFrame`` with inline stock statistics/indicators support.,10.0,25,True,2023-07-30 07:07:37.000,0.6.2,24.0,stockstats,,,,,1122.0,1111.0,https://pypi.org/project/stockstats,2023-07-30 07:07:37.000,11.0,9493.0,9493.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +534,RLax,deepmind/rlax,reinforcement-learning,,https://github.com/google-deepmind/rlax,https://github.com/google-deepmind/rlax,Apache-2.0,2020-02-18 07:14:59.000,2024-09-24 21:15:08.000000,2024-05-24 12:07:18,209.0,,85.0,34.0,111.0,8.0,18.0,1252.0,A library of reinforcement learning building blocks in JAX.,21.0,25,True,2023-06-29 15:05:00.621,0.1.6,10.0,rlax,,,,['jax'],285.0,274.0,https://pypi.org/project/rlax,2023-01-09 22:29:35.947,11.0,21386.0,21386.0,,,,,,,,3.0,,,,google-deepmind/rlax,,,,,,,,,,,,,,,, +535,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 18:22:13.000,2024-09-25 05:32:38.000000,2024-09-25 05:32:38,605.0,1.0,214.0,53.0,461.0,145.0,295.0,1206.0,A Framework for Encrypted Machine Learning in TensorFlow.,29.0,25,True,2023-02-08 02:53:00.720,0.9.1,41.0,tf-encrypted,,,,['tensorflow'],77.0,68.0,https://pypi.org/project/tf-encrypted,2022-11-16 09:12:55.841,9.0,3346.0,3346.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +536,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,,119.0,11.0,23.0,28.0,15.0,1134.0,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,,,,,6781.0,6309.0,https://pypi.org/project/gputil,2018-12-18 09:12:13.000,472.0,571360.0,571360.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +537,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,,184.0,33.0,74.0,3.0,86.0,1043.0,Layers Outputs and Gradients in Keras. Made easy.,16.0,25,True,2022-09-25 14:40:40.377,4.5.1,39.0,keract,,,,['tensorflow'],236.0,227.0,https://pypi.org/project/keract,2022-09-25 14:40:40.377,9.0,11745.0,11745.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +538,aequitas,dssg/aequitas,interpretability,,https://github.com/dssg/aequitas,https://github.com/dssg/aequitas,MIT,2018-02-13 19:40:30.000,2024-09-11 16:24:06.000000,2024-09-11 10:27:00,921.0,10.0,113.0,43.0,118.0,51.0,48.0,685.0,Bias Auditing & Fair ML Toolkit.,22.0,25,True,2024-01-30 12:03:19.000,1.0.0,18.0,aequitas,,,,,180.0,172.0,https://pypi.org/project/aequitas,2024-01-30 12:03:19.000,8.0,35271.0,35271.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +539,FEDOT,nccr-itmo/FEDOT,hyperopt,,https://github.com/aimclub/FEDOT,https://github.com/aimclub/FEDOT,BSD-3-Clause,2020-01-13 12:48:37.000,2024-10-24 13:32:06.000000,2024-10-17 21:07:47,898.0,16.0,86.0,11.0,766.0,64.0,488.0,640.0,Automated modeling and machine learning framework FEDOT.,35.0,25,True,2024-08-28 11:07:57.000,0.7.4,23.0,fedot,,,,,60.0,55.0,https://pypi.org/project/fedot,2024-08-28 10:34:09.000,5.0,3202.0,3202.0,,,,,,,,2.0,,,,aimclub/FEDOT,,,,,,,,,,,,,,,, +540,MedPy,loli/medpy,medical-data,,https://github.com/loli/medpy,https://github.com/loli/medpy,GPL-3.0,2012-05-11 10:57:34.000,2024-09-18 15:23:28.852000,2024-07-23 14:46:53,413.0,,137.0,21.0,49.0,1.0,87.0,575.0,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,,,,2351.0,2298.0,https://pypi.org/project/MedPy,2024-07-23 14:23:57.000,53.0,25517.0,27076.0,https://anaconda.org/conda-forge/medpy,2024-09-18 15:23:28.852,62381.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +541,SKLL,EducationalTestingService/skll,ml-experiments,,https://github.com/EducationalTestingService/skll,https://github.com/EducationalTestingService/skll,BSD-1-Clause,2013-08-02 14:31:46.000,2024-10-21 13:56:47.000000,2024-10-21 13:56:46,3772.0,13.0,69.0,46.0,360.0,21.0,399.0,552.0,SciKit-Learn Laboratory (SKLL) makes it easy to run machine learning experiments.,39.0,25,False,2024-03-08 20:13:23.000,5.0.1,71.0,skll,conda-forge/skll,,,['sklearn'],48.0,46.0,https://pypi.org/project/skll,2024-03-08 20:01:40.000,2.0,3412.0,3906.0,https://anaconda.org/conda-forge/skll,2024-03-09 00:32:37.185,17308.0,,,,,3.0,15.0,,,,,,,,,,,,,,,,,,, +542,Hyperactive,SimonBlanke/Hyperactive,hyperopt,,https://github.com/SimonBlanke/Hyperactive,https://github.com/SimonBlanke/Hyperactive,MIT,2018-11-01 08:53:30.000,2024-10-13 06:00:41.000000,2024-10-12 06:59:18,2380.0,90.0,42.0,12.0,16.0,15.0,61.0,511.0,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,,,,,49.0,36.0,https://pypi.org/project/hyperactive,2024-08-15 14:23:15.000,13.0,5455.0,5458.0,,,,,,,,2.0,254.0,,,,,,,,,,,,,,,,,,, +543,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 00:21:15,339.0,35.0,30.0,9.0,7.0,7.0,78.0,350.0,Multiple Imputation with LightGBM in Python.,8.0,25,True,2024-08-02 00:43:48.000,6.0.3,48.0,miceforest,conda-forge/miceforest,,,,177.0,168.0,https://pypi.org/project/miceforest,2024-08-02 00:43:48.000,9.0,65784.0,66181.0,https://anaconda.org/conda-forge/miceforest,2023-06-16 19:26:58.237,15513.0,,,,,1.0,,,,,,,,,,,,,,,,,,,, +544,gokart,m3dev/gokart,ml-experiments,,https://github.com/m3dev/gokart,https://github.com/m3dev/gokart,MIT,2018-12-23 07:40:27.000,2024-10-14 17:15:14.000000,2024-09-29 01:46:34,567.0,9.0,57.0,41.0,321.0,20.0,63.0,315.0,"Gokart solves reproducibility, task dependencies, constraints of good code, and ease of use for Machine Learning..",41.0,25,True,2024-09-19 03:59:24.000,1.6.1,84.0,gokart,,,,,90.0,82.0,https://pypi.org/project/gokart,2024-09-19 03:59:24.000,8.0,8565.0,8565.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +545,lkpy,lenskit/lkpy,recommender-systems,,https://github.com/lenskit/lkpy,https://github.com/lenskit/lkpy,MIT,2018-06-08 21:05:10.000,2024-10-16 11:07:10.000000,2024-10-16 11:00:09,3718.0,377.0,60.0,7.0,331.0,48.0,103.0,267.0,Python recommendation toolkit.,14.0,25,False,2024-02-16 21:04:30.000,0.14.4,25.0,lenskit,conda-forge/lenskit,,,,122.0,116.0,https://pypi.org/project/lenskit,2024-02-16 21:03:49.000,6.0,3072.0,3807.0,https://anaconda.org/conda-forge/lenskit,2024-04-18 13:51:51.378,34558.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +546,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,,526.0,82.0,39.0,63.0,27.0,11136.0,"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,,,,58.0,58.0,https://pypi.org/project/prettymaps,2024-07-02 22:56:31.000,,1582.0,1690.0,https://anaconda.org/conda-forge/prettymaps,2024-07-03 13:55:21.192,3586.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +547,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 21:45:14.000,2024-09-20 17:59:42.000000,2024-06-28 18:04:28,599.0,,749.0,108.0,590.0,107.0,345.0,6147.0,Code for the paper Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer.,59.0,24,True,2023-03-30 16:55:07.154,0.9.4,29.0,t5,,,,['tensorflow'],2.0,,https://pypi.org/project/t5,2021-10-18 13:55:26.000,2.0,46742.0,46742.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +548,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,,450.0,63.0,94.0,36.0,88.0,5142.0,Finding duplicate images made easy!.,15.0,24,False,2023-04-28 17:29:01.612,0.3.2,12.0,imagededup,,,,['tensorflow'],151.0,146.0,https://pypi.org/project/imagededup,2023-04-28 17:29:01.612,5.0,53167.0,53167.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +549,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 11:16:16,206.0,1.0,1032.0,92.0,64.0,271.0,270.0,4740.0,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'],28.0,,https://pypi.org/project/segmentation_models,2020-01-10 11:36:02.000,28.0,27593.0,27593.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +550,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,,1385.0,354.0,59.0,51.0,,4426.0,Python Algorithmic Trading Library.,11.0,24,False,,,8.0,pyalgotrade,,,,,193.0,193.0,https://pypi.org/project/pyalgotrade,2018-08-21 01:48:25.000,,1046.0,1046.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +551,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,,450.0,44.0,55.0,95.0,174.0,4340.0,An Open-Source Framework for Prompt-Learning.,24.0,24,False,2022-07-06 14:27:42.000,1.0.1,5.0,openprompt,,,,,152.0,149.0,https://pypi.org/project/openprompt,2022-07-06 14:27:42.000,3.0,872.0,872.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +552,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,,727.0,62.0,247.0,130.0,824.0,4150.0,"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,,,,,21.0,,https://pypi.org/project/stable-baselines,2021-04-06 12:38:10.521,21.0,7252.0,7252.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +553,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,,811.0,326.0,89.0,91.0,306.0,3872.0,Intel Nervana reference deep learning framework committed to best performance on all hardware.,108.0,24,False,2018-01-05 23:25:04.000,2.6.0,32.0,nervananeon,anaconda/neon,,,,,,https://pypi.org/project/nervananeon,2018-01-05 23:25:04.000,,364.0,385.0,https://anaconda.org/anaconda/neon,2024-08-13 17:48:41.449,1748.0,,,,,3.0,420.0,,,,,,,,,,,,,,,,,,, +554,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,,447.0,89.0,78.0,67.0,137.0,3373.0,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'],2.0,,https://pypi.org/project/torchbiggraph,2019-10-14 16:44:41.000,2.0,452419.0,452422.0,,,,,,,,2.0,207.0,,,,,,,,,,,,,,,,,,, +555,Apache Singa,apache/singa,distributed-ml,,https://github.com/apache/singa,https://github.com/apache/singa,Apache-2.0,2015-04-02 07:00:05.000,2024-10-22 07:31:07.000000,2024-08-17 14:22:50,2847.0,36.0,1241.0,134.0,1117.0,50.0,83.0,3370.0,a distributed deep learning platform.,91.0,24,True,2020-04-21 08:01:08.000,3.0.0,16.0,,nusdbsystem/singa,apache/singa,,,5.0,5.0,,,,,79.0,https://anaconda.org/nusdbsystem/singa,2023-06-16 13:23:56.805,801.0,https://hub.docker.com/r/apache/singa,2022-05-31 15:24:19.649658,4.0,8184.0,3.0,,,,,,,,,,,,,,,,,,,, +556,DeepVariant,google/deepvariant,medical-data,,https://github.com/google/deepvariant,https://github.com/google/deepvariant,BSD-3-Clause,2017-11-23 01:56:22.000,2024-10-23 13:32:58.000000,2024-03-18 19:51:35,2374.0,,712.0,156.0,63.0,7.0,828.0,3208.0,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'],,,,,,,920.0,https://anaconda.org/bioconda/deepvariant,2023-06-16 16:08:50.013,69848.0,,,,,3.0,4785.0,,,,,,,,,,,,,,,,,,, +557,DDSP,magenta/ddsp,audio,,https://github.com/magenta/ddsp,https://github.com/magenta/ddsp,Apache-2.0,2020-01-14 18:38:27.000,2024-09-23 16:30:28.000000,2024-09-23 16:30:23,472.0,1.0,324.0,65.0,319.0,50.0,124.0,2889.0,DDSP: Differentiable Digital Signal Processing.,32.0,24,True,2023-05-25 02:30:41.654,3.7.0,55.0,ddsp,conda-forge/ddsp,,,['tensorflow'],61.0,60.0,https://pypi.org/project/ddsp,2022-05-25 17:42:19.000,1.0,5899.0,6255.0,https://anaconda.org/conda-forge/ddsp,2023-06-16 19:19:34.916,18523.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +558,tensorflow-graphics,tensorflow/graphics,image,,https://github.com/tensorflow/graphics,https://github.com/tensorflow/graphics,Apache-2.0,2019-01-08 10:39:44.000,2024-10-19 04:55:44.000000,2024-08-01 02:26:24,769.0,1.0,361.0,90.0,554.0,143.0,95.0,2749.0,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'],11.0,,https://pypi.org/project/tensorflow-graphics,2021-12-03 22:33:39.000,11.0,57266.0,57266.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +559,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,,325.0,92.0,2158.0,214.0,982.0,2703.0,"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,,,,,2.0,,https://pypi.org/project/pymars,2022-06-12 11:43:21.000,2.0,43602.0,43602.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +560,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,,345.0,33.0,695.0,43.0,151.0,2674.0,"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,,,,,116.0,112.0,https://pypi.org/project/promptsource,2022-04-18 22:31:03.000,4.0,443.0,443.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +561,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,,618.0,87.0,29.0,25.0,52.0,2368.0,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,,,,,782.0,728.0,https://pypi.org/project/python_speech_features,2017-08-16 01:46:13.000,54.0,22811.0,22811.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +562,kubric,google-research/kubric,image,,https://github.com/google-research/kubric,https://github.com/google-research/kubric,Apache-2.0,2020-07-22 19:56:38.000,2024-10-07 11:45:57.000000,2024-10-07 11:45:57,547.0,1.0,223.0,41.0,134.0,63.0,127.0,2315.0,A data generation pipeline for creating semi-realistic synthetic multi-object videos with rich annotations such as..,30.0,24,True,2023-12-27 00:46:01.000,2023.12.27,773.0,kubric-nightly,,,,,7.0,7.0,https://pypi.org/project/kubric-nightly,2023-12-27 00:46:01.000,,68480.0,68480.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +563,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,,236.0,62.0,32.0,60.0,96.0,2275.0,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,,,,,116.0,115.0,https://pypi.org/project/neural-tangents,2023-12-11 14:00:20.000,1.0,3716.0,3725.0,,,,,,,,3.0,499.0,,,,,,,,,,,,,,,,,,, +564,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,,244.0,38.0,39.0,7.0,114.0,2152.0,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,,,,285.0,272.0,https://pypi.org/project/karateclub,2022-10-22 13:31:38.000,13.0,8976.0,9508.0,https://anaconda.org/conda-forge/karateclub,2023-06-16 19:21:04.092,27149.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +565,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,,685.0,85.0,48.0,24.0,64.0,2132.0,Common financial technical indicators implemented in Pandas.,28.0,24,False,2021-04-03 08:51:49.000,1.3,19.0,finta,,,,,558.0,546.0,https://pypi.org/project/finta,2020-10-21 11:39:44.000,12.0,15563.0,15563.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +566,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 13:50:19.000,2024-10-21 08:58:39.000000,2024-10-21 08:58:36,579.0,1.0,159.0,56.0,470.0,74.0,104.0,2032.0,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,,,,,123.0,113.0,https://pypi.org/project/hivemind,2023-08-31 20:07:10.000,10.0,3604.0,3604.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +567,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,,203.0,29.0,65.0,11.0,83.0,2009.0,Beyond Accuracy: Behavioral Testing of NLP models with CheckList.,15.0,24,False,2021-05-24 16:45:59.000,0.0.11,10.0,checklist,conda-forge/checklist,,,['jupyter'],373.0,365.0,https://pypi.org/project/checklist,2021-05-24 16:45:59.000,8.0,1669.0,1849.0,https://anaconda.org/conda-forge/checklist,2023-06-16 19:24:18.549,8110.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +568,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 19:10:08,367.0,1.0,272.0,49.0,320.0,262.0,184.0,1832.0,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'],2.0,,https://pypi.org/project/tensorflow-recommenders,2023-02-03 02:17:00.422,2.0,402573.0,402573.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +569,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,,311.0,97.0,45.0,187.0,217.0,1643.0,[UNMAINTAINED] Automated machine learning for analytics & production.,14.0,24,False,2018-02-22 01:13:03.000,2.9.10,78.0,auto_ml,,,,,9.0,,https://pypi.org/project/auto_ml,2018-02-22 01:13:03.000,9.0,18211.0,18211.0,,,,,,,,3.0,67.0,,,,,,,,,,,,,,,,,,, +570,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,,303.0,56.0,118.0,54.0,31.0,1622.0,Interpretability and explainability of data and machine learning models.,41.0,24,True,2023-07-31 18:54:38.000,0.3.0,5.0,aix360,,,,,105.0,104.0,https://pypi.org/project/aix360,2023-07-31 18:54:38.000,1.0,2643.0,2643.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +571,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,,238.0,50.0,49.0,23.0,91.0,1621.0,Contextually-keyed word vectors.,19.0,24,False,2023-04-17 14:14:02.218,2.0.2,24.0,sense2vec,conda-forge/sense2vec,,,,423.0,410.0,https://pypi.org/project/sense2vec,2021-04-19 07:05:28.000,13.0,3013.0,5127.0,https://anaconda.org/conda-forge/sense2vec,2023-09-22 07:25:32.800,48416.0,,,,,3.0,68128.0,,,,,,,,,,,,,,,,,,, +572,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,,122.0,28.0,31.0,63.0,50.0,1587.0,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'],547.0,540.0,https://pypi.org/project/higher,2020-07-14 12:20:32.000,7.0,248539.0,248539.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +573,CrypTen,facebookresearch/CrypTen,privacy-ml,,https://github.com/facebookresearch/CrypTen,https://github.com/facebookresearch/CrypTen,MIT,2019-08-15 00:00:31.000,2024-10-19 03:44:21.000000,2024-10-19 03:22:50,358.0,1.0,272.0,43.0,257.0,77.0,198.0,1536.0,A framework for Privacy Preserving Machine Learning.,38.0,24,True,2022-12-08 22:11:59.883,0.4.1,3.0,crypten,,,,['pytorch'],46.0,45.0,https://pypi.org/project/crypten,2022-12-08 22:11:59.883,1.0,854.0,854.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +574,Pytorch Toolbelt,BloodAxe/pytorch-toolbelt,pytorch-utils,,https://github.com/BloodAxe/pytorch-toolbelt,https://github.com/BloodAxe/pytorch-toolbelt,MIT,2019-03-15 16:02:49.000,2024-10-14 20:21:00.000000,2024-10-14 20:04:47,1217.0,14.0,118.0,29.0,69.0,4.0,29.0,1517.0,PyTorch extensions for fast R&D prototyping and Kaggle farming.,8.0,24,True,2023-08-19 14:26:10.000,0.7.0,29.0,pytorch_toolbelt,,,,['pytorch'],7.0,,https://pypi.org/project/pytorch_toolbelt,2022-06-27 19:59:57.000,7.0,9059.0,9059.0,,,,,,,,3.0,45.0,2.0,,,,,,,,,,,,,,,,,, +575,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 20:38:00,159.0,2.0,163.0,104.0,189.0,40.0,25.0,1508.0,fklearn: Functional Machine Learning.,56.0,24,True,2024-08-14 21:07:18.000,4.0.0,34.0,fklearn,,,,,15.0,15.0,https://pypi.org/project/fklearn,2024-08-14 21:07:18.000,,4400.0,4400.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +576,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,,164.0,32.0,24.0,42.0,34.0,1291.0,"Transpile trained scikit-learn estimators to C, Java, JavaScript and others.",13.0,24,False,2019-12-18 13:39:19.000,0.7.4,20.0,sklearn-porter,,,,['sklearn'],68.0,68.0,https://pypi.org/project/sklearn-porter,2019-12-18 13:39:19.000,,2279.0,2279.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +577,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 11:14:21,90.0,2.0,245.0,20.0,23.0,5.0,88.0,1230.0,Implementation of the node2vec algorithm.,16.0,24,True,2024-08-02 11:13:59.000,0.5.0,19.0,node2vec,conda-forge/node2vec,,,,737.0,706.0,https://pypi.org/project/node2vec,2024-08-02 11:12:23.000,31.0,17744.0,18149.0,https://anaconda.org/conda-forge/node2vec,2023-06-16 16:13:35.056,31189.0,,,,,2.0,,,,,,,,,,,,,,,,,,,, +578,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,,221.0,70.0,415.0,75.0,147.0,1170.0,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,,,,,180.0,175.0,https://pypi.org/project/chainerrl,2020-02-14 05:35:56.000,5.0,959.0,959.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +579,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 10:51:56.000,2024-10-23 02:38:14.000000,2024-08-24 15:16:00,781.0,1.0,68.0,15.0,131.0,51.0,117.0,1025.0,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,,,,1484.0,1460.0,https://pypi.org/project/plotly-resampler,2024-03-27 07:54:02.000,24.0,364139.0,366326.0,https://anaconda.org/conda-forge/plotly-resampler,2024-03-29 13:25:52.761,72203.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +580,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,,174.0,49.0,114.0,53.0,170.0,987.0,Python interface to GPU-powered libraries.,44.0,24,True,2019-05-27 00:29:00.000,0.5.3,7.0,scikit-cuda,,,,,330.0,307.0,https://pypi.org/project/scikit-cuda,2019-05-27 00:29:00.000,23.0,729.0,729.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +581,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,,191.0,48.0,61.0,1.0,68.0,982.0,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'],489.0,486.0,https://pypi.org/project/neural-structured-learning,2022-07-29 21:05:16.715,3.0,7078.0,7078.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +582,Runhouse,run-house/runhouse,ml-frameworks,,https://github.com/run-house/runhouse,https://github.com/run-house/runhouse,Apache-2.0,2022-05-10 14:10:51.000,2024-10-24 14:41:41.000000,2024-10-23 19:40:23,1808.0,214.0,35.0,9.0,1291.0,9.0,42.0,969.0,"Dispatch and distribute your ML training to serverless clusters in Python, like PyTorch for ML infra. Iterable,..",15.0,24,True,2024-09-18 03:52:33.000,0.0.35,43.0,runhouse,,,,,1.0,,https://pypi.org/project/runhouse,2024-09-18 03:50:09.000,1.0,8391.0,8393.0,,,,,,,,3.0,52.0,,,,,,,,,,,,,,,,,,, +583,TSFEL,fraunhoferportugal/tsfel,time-series-data,,https://github.com/fraunhoferportugal/tsfel,https://github.com/fraunhoferportugal/tsfel,BSD-3-Clause,2019-01-09 16:41:30.000,2024-10-17 08:47:41.000000,2024-10-17 08:43:32,431.0,33.0,143.0,20.0,87.0,7.0,71.0,926.0,An intuitive library to extract features from time series.,20.0,24,True,2024-09-12 10:50:23.000,0.1.9,13.0,tsfel,,,,,164.0,157.0,https://pypi.org/project/tsfel,2024-09-12 10:43:35.000,7.0,16293.0,16293.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +584,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,,86.0,14.0,77.0,221.0,218.0,869.0,"Experiment tracking, ML developer tools.",29.0,24,False,2023-02-25 17:16:57.621,0.9.0,186.0,guildai,,,,,100.0,100.0,https://pypi.org/project/guildai,2022-05-11 01:13:31.000,,9692.0,9692.0,,,,,,,,3.0,25.0,,,,,,,,,,,,,,,,,,, +585,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,,158.0,33.0,25.0,35.0,236.0,741.0,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,,,,,182.0,178.0,https://pypi.org/project/neupy,2019-04-04 19:43:06.000,4.0,4174.0,4174.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +586,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,,155.0,17.0,73.0,35.0,110.0,728.0,Ternary plotting library for python with matplotlib.,28.0,24,True,2021-02-17 18:38:15.000,1.0.8,11.0,python-ternary,conda-forge/python-ternary,,,,223.0,191.0,https://pypi.org/project/python-ternary,2021-02-17 18:38:15.000,32.0,23229.0,24116.0,https://anaconda.org/conda-forge/python-ternary,2023-06-16 13:17:10.682,90506.0,,,,,3.0,32.0,,,,,,,,,,,,,,,,,,, +587,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,,136.0,133.0,91.0,42.0,67.0,664.0,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'],231.0,219.0,https://pypi.org/project/mapboxgl,2019-06-02 16:02:54.380,12.0,15919.0,15919.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +588,MONAILabel,Project-MONAI/MONAILabel,others,,https://github.com/Project-MONAI/MONAILabel,https://github.com/Project-MONAI/MONAILabel,Apache-2.0,2021-03-26 15:25:10.000,2024-10-23 20:26:12.000000,2024-10-22 15:00:10,994.0,12.0,193.0,23.0,864.0,131.0,397.0,602.0,MONAI Label is an intelligent open source image labeling and learning tool.,62.0,24,True,2024-10-17 22:32:00.000,0.8.4,114.0,monailabel-weekly,,,,,,,https://pypi.org/project/monailabel-weekly,2023-10-01 02:24:07.000,,5099.0,7600.0,,,,,,,,3.0,97566.0,,,,,,,,,,,,,,,,,,, +589,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,,70.0,15.0,13.0,35.0,7.0,576.0,Pure-Python full-text search library.,42.0,24,False,2016-04-04 01:19:40.000,2.7.4,141.0,whoosh,conda-forge/whoosh,,,,232.0,,https://pypi.org/project/whoosh,2016-04-04 01:19:40.000,232.0,399516.0,407679.0,https://anaconda.org/conda-forge/whoosh,2024-09-03 08:52:17.073,334710.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +590,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,,72.0,8.0,17.0,11.0,12.0,511.0,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'],4948.0,4845.0,https://pypi.org/project/findspark,2022-02-11 08:02:06.000,103.0,2350120.0,2359382.0,https://anaconda.org/conda-forge/findspark,2023-06-16 13:16:45.065,926257.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +591,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,,94.0,19.0,764.0,16.0,446.0,445.0,Lightwood is Legos for Machine Learning.,46.0,24,False,2024-05-15 13:29:47.000,24.5.2.0,204.0,lightwood,,,,['pytorch'],75.0,73.0,https://pypi.org/project/lightwood,2024-05-15 13:37:20.000,2.0,11879.0,11879.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +592,vega,vega/ipyvega,data-viz,,https://github.com/vega/ipyvega,https://github.com/vega/ipyvega,BSD-3-Clause,2015-08-04 03:22:47.000,2024-10-01 02:29:20.000000,2024-10-01 02:29:19,677.0,15.0,65.0,29.0,486.0,16.0,91.0,372.0,IPython/Jupyter notebook module for Vega and Vega-Lite.,15.0,24,True,2024-09-25 14:29:32.000,4.1.0,41.0,vega,conda-forge/vega,,,['jupyter'],21.0,4.0,https://pypi.org/project/vega,2024-09-25 14:29:32.000,17.0,12062.0,24453.0,https://anaconda.org/conda-forge/vega,2024-09-25 20:44:27.334,656727.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +593,ivis,beringresearch/ivis,data-viz,,https://github.com/beringresearch/ivis,https://github.com/beringresearch/ivis,Apache-2.0,2018-08-13 08:31:01.000,2024-09-29 23:44:29.000000,2024-09-29 23:43:33,584.0,453.0,43.0,13.0,64.0,3.0,57.0,330.0,Dimensionality reduction in very large datasets using Siamese Networks.,10.0,24,True,2024-06-13 05:28:35.000,2.0.11,36.0,ivis,,,,['tensorflow'],38.0,36.0,https://pypi.org/project/ivis,2024-06-13 05:28:35.000,2.0,2586.0,2586.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +594,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,,1470.0,149.0,50.0,46.0,12.0,10263.0,A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API.,2.0,23,False,2020-04-18 19:06:59.000,0.1.0,1.0,micrograd,,,,['pytorch'],69.0,66.0,https://pypi.org/project/micrograd,2020-04-18 19:06:59.000,3.0,1450.0,1450.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +595,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,,609.0,145.0,1362.0,129.0,987.0,8018.0,Production infrastructure for machine learning at scale.,25.0,23,False,2022-09-23 18:01:31.000,0.42.1,63.0,cortex,,,,,2.0,,https://pypi.org/project/cortex,2022-09-23 17:40:01.770,2.0,1741.0,1741.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +596,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,,1434.0,263.0,69.0,133.0,136.0,6421.0,Audio fingerprinting and recognition in Python.,23.0,23,False,2015-04-19 21:20:16.000,0.1.3,4.0,PyDejavu,,,,,21.0,21.0,https://pypi.org/project/PyDejavu,2015-04-19 21:20:16.000,,808.0,808.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +597,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,,1049.0,121.0,109.0,172.0,356.0,5457.0,Backtest trading strategies in Python.,19.0,23,False,2021-12-13 01:36:44.000,0.3.3,21.0,backtesting,,,,,6.0,,https://pypi.org/project/backtesting,2021-12-13 01:36:44.000,6.0,19025.0,19025.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +598,MMLSpark,microsoft/SynapseML,distributed-ml,,https://github.com/microsoft/SynapseML,https://github.com/microsoft/SynapseML,MIT,2017-06-05 08:23:44.000,2024-10-16 04:25:11.000000,2024-10-16 04:12:35,1641.0,24.0,830.0,145.0,1571.0,376.0,403.0,5061.0,Simple and Distributed Machine Learning.,120.0,23,True,2024-10-16 04:14:37.000,1.0.8,58.0,mmlspark,,,,['spark'],,,https://pypi.org/project/mmlspark,2020-03-18 01:27:31.000,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +599,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,,321.0,75.0,37.0,95.0,76.0,4374.0,Simple command line tool for text to image generation using OpenAIs CLIP and Siren (Implicit neural representation..,14.0,23,False,2022-03-13 19:09:50.000,0.11.1,67.0,deep-daze,,,,,54.0,54.0,https://pypi.org/project/deep-daze,2022-03-13 19:09:50.000,,5671.0,5671.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +600,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,,489.0,215.0,16.0,24.0,4.0,3439.0,Python library for backtesting trading strategies & analyzing financial markets (formerly pythalesians).,14.0,23,True,2024-05-19 22:21:30.000,0.11.14,15.0,finmarketpy,,,,,16.0,16.0,https://pypi.org/project/finmarketpy,2024-05-19 22:21:30.000,,1509.0,1509.0,,,,,,,,3.0,56.0,,,,,,,,,,,,,,,,,,, +601,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,,329.0,54.0,414.0,82.0,106.0,3256.0,"VISSL is FAIRs library of extensible, modular and scalable components for SOTA Self-Supervised Learning with images.",38.0,23,True,2021-11-02 17:21:02.000,0.1.6,6.0,vissl,,,,['pytorch'],54.0,53.0,https://pypi.org/project/vissl,2021-11-02 15:36:07.000,1.0,244.0,244.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +602,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,,233.0,53.0,36.0,75.0,125.0,3188.0,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'],445.0,431.0,https://pypi.org/project/pandasgui,2021-08-14 09:14:51.000,14.0,5149.0,5770.0,https://anaconda.org/conda-forge/pandasgui,2023-06-16 19:24:31.206,27949.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +603,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 03:41:26.000,2024-09-20 01:28:48.000000,2024-09-20 01:28:13,3461.0,2.0,727.0,7.0,33.0,406.0,855.0,2607.0,"Distributed Tensorflow, Keras and PyTorch on Apache Spark/Flink & Ray.",109.0,23,True,2024-03-05 10:02:36.000,0.1.0,418.0,analytics-zoo,,,,['spark'],1.0,,https://pypi.org/project/analytics-zoo,2022-08-22 20:19:01.213,1.0,10930.0,10930.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +604,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,,413.0,131.0,136.0,60.0,128.0,2405.0,Deep Learning toolkit for Computer Vision.,15.0,23,False,2018-11-09 21:35:17.000,0.2.3,10.0,luminoth,,,,['tensorflow'],68.0,66.0,https://pypi.org/project/luminoth,2018-11-09 21:35:17.000,2.0,2057.0,2210.0,,,,,,,,3.0,12875.0,,,,,,,,,,,,,,,,,,, +605,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,,381.0,79.0,144.0,36.0,126.0,2390.0,"Toolkit for Machine Learning, Natural Language Processing, and Text Generation, in TensorFlow. This is part of the..",43.0,23,False,2019-11-19 04:11:18.000,0.2.4,6.0,texar,,,,['tensorflow'],31.0,29.0,https://pypi.org/project/texar,2019-11-19 04:11:18.000,2.0,198.0,198.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +606,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,,298.0,64.0,78.0,65.0,68.0,2104.0,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'],35.0,32.0,https://pypi.org/project/sru,2021-06-17 23:33:37.000,3.0,2748.0,2748.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +607,Vulkan Kompute,KomputeProject/kompute,gpu-utilities,,https://github.com/KomputeProject/kompute,https://github.com/KomputeProject/kompute,Apache-2.0,2020-07-29 05:23:33.000,2024-10-18 12:12:48.000000,2024-10-18 12:12:48,1289.0,26.0,144.0,33.0,180.0,71.0,149.0,1981.0,"General purpose GPU compute framework built on Vulkan to support 1000s of cross vendor graphics cards (AMD, Qualcomm,..",29.0,23,True,2024-01-20 15:39:17.000,0.9.0,14.0,kp,,,,,,,https://pypi.org/project/kp,2024-01-20 15:33:09.000,,924.0,935.0,,,,,,,,3.0,595.0,,,,,,,,,,,,,,,,,,, +608,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,,247.0,44.0,33.0,51.0,90.0,1979.0,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'],181.0,181.0,https://pypi.org/project/torchmeta,2021-09-20 16:06:33.000,,6744.0,6744.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +609,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,,228.0,42.0,36.0,45.0,24.0,1888.0,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'],493.0,471.0,https://pypi.org/project/MulticoreTSNE,2019-01-09 07:23:04.000,22.0,1957.0,3207.0,https://anaconda.org/conda-forge/multicore-tsne,2023-10-11 19:12:48.654,52511.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +610,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,,135.0,35.0,446.0,50.0,354.0,1871.0,A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.,20.0,23,True,2024-04-01 00:44:51.000,1.1.4.9,36.0,orbit-ml,,,,,65.0,64.0,https://pypi.org/project/orbit-ml,2024-04-01 00:45:19.000,1.0,18779.0,18779.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +611,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,,135.0,35.0,446.0,50.0,354.0,1871.0,A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.,20.0,23,True,2024-04-01 00:44:51.000,1.1.4.9,36.0,orbit-ml,conda-forge/orbit-ml,,,,65.0,64.0,https://pypi.org/project/orbit-ml,2024-04-01 00:45:19.000,1.0,18779.0,19242.0,https://anaconda.org/conda-forge/orbit-ml,2024-04-01 02:54:47.033,15285.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +612,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,,295.0,44.0,801.0,72.0,485.0,1642.0,jiant is an nlp toolkit.,60.0,23,False,2021-05-10 18:56:39.000,2.2.0,19.0,jiant,,,,,6.0,6.0,https://pypi.org/project/jiant,2021-05-10 18:56:39.000,,534.0,534.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +613,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,,189.0,32.0,86.0,16.0,33.0,1424.0,"A program for financial portfolio management, analysis and optimisation.",11.0,23,False,2023-09-04 06:57:56.000,0.7.0,15.0,FinQuant,,,,,96.0,95.0,https://pypi.org/project/FinQuant,2023-09-04 06:57:56.000,1.0,1812.0,1812.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +614,pytorch_tabular,manujosephv/pytorch_tabular,tabular,,https://github.com/manujosephv/pytorch_tabular,https://github.com/manujosephv/pytorch_tabular,MIT,2020-12-15 07:17:03.000,2024-10-22 00:04:19.000000,2024-09-17 07:49:48,563.0,13.0,135.0,21.0,307.0,21.0,142.0,1362.0,A standard framework for modelling Deep Learning Models for tabular data.,23.0,23,True,2024-01-15 12:17:19.000,1.1.0,12.0,pytorch_tabular,,,,['pytorch'],3.0,,https://pypi.org/project/pytorch_tabular,2024-01-15 02:46:25.000,3.0,4137.0,4138.0,,,,,,,,2.0,43.0,,,,,,,,,,,,,,,,,,, +615,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,,197.0,27.0,57.0,27.0,36.0,1301.0,A Toolbox for Adversarial Robustness Research.,21.0,23,False,2020-06-15 01:20:07.000,0.2.3,10.0,advertorch,,,,['pytorch'],181.0,176.0,https://pypi.org/project/advertorch,2020-06-15 01:20:07.000,5.0,3264.0,3264.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +616,calamari,Calamari-OCR/calamari,ocr,,https://github.com/Calamari-OCR/calamari,https://github.com/Calamari-OCR/calamari,GPL-3.0,2018-03-20 15:22:29.000,2024-10-01 23:42:11.000000,2024-10-01 23:38:02,473.0,27.0,209.0,53.0,94.0,66.0,219.0,1044.0,Line based ATR Engine based on OCRopy.,21.0,23,False,2024-10-01 23:41:06.000,2.3.0.post1,44.0,calamari_ocr,,,,,8.0,,https://pypi.org/project/calamari_ocr,2024-10-01 23:42:11.000,8.0,7901.0,7901.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +617,PyTorch Sparse,rusty1s/pytorch_sparse,pytorch-utils,,https://github.com/rusty1s/pytorch_sparse,https://github.com/rusty1s/pytorch_sparse,MIT,2018-07-28 18:46:53.000,2024-10-08 21:24:59.446000,2024-08-15 16:03:59,733.0,1.0,147.0,15.0,107.0,29.0,250.0,1005.0,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'],122.0,,https://pypi.org/project/torch-sparse,2023-10-06 08:51:55.000,122.0,31917.0,41169.0,https://anaconda.org/conda-forge/pytorch_sparse,2024-10-08 21:24:59.446,481147.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +618,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,,87.0,26.0,55.0,36.0,28.0,954.0,Unsupervised text tokenizer focused on computational efficiency.,8.0,23,False,2020-02-13 09:57:47.000,1.0.6,14.0,youtokentome,conda-forge/youtokentome,,,,779.0,756.0,https://pypi.org/project/youtokentome,2020-02-12 18:24:46.000,23.0,84797.0,86648.0,https://anaconda.org/conda-forge/youtokentome,2023-09-27 19:23:04.851,68487.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +619,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,,190.0,24.0,58.0,12.0,27.0,951.0,"Framework-agnostic implementation for state-of-the-art saliency methods (XRAI, BlurIG, SmoothGrad, and more).",18.0,23,True,2024-03-20 19:51:28.000,0.2.1,12.0,saliency,,,,['tensorflow'],114.0,106.0,https://pypi.org/project/saliency,2024-03-20 19:51:28.000,8.0,60006.0,60006.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +620,detoxify,unitaryai/detoxify,nlp,,https://github.com/unitaryai/detoxify,https://github.com/unitaryai/detoxify,Apache-2.0,2020-09-23 15:24:21.000,2024-09-19 13:26:10.000000,2024-09-19 13:26:10,252.0,2.0,115.0,15.0,48.0,38.0,29.0,945.0,Trained models & code to predict toxic comments on all 3 Jigsaw Toxic Comment Challenges. Built using Pytorch..,12.0,23,True,2024-02-01 14:51:21.000,0.5.2,13.0,detoxify,,,,,738.0,708.0,https://pypi.org/project/detoxify,2024-02-01 14:51:21.000,30.0,54953.0,70006.0,,,,,,,,3.0,707493.0,,,,,,,,,,,,,,,,,,, +621,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 20:26:10.000,2024-09-11 20:07:00.000000,2024-02-01 21:38:56,330.0,,170.0,29.0,113.0,88.0,56.0,911.0,Source code/webpage/demos for the What-If Tool.,20.0,23,True,2021-10-12 17:42:50.869,1.8.1,40.0,witwidget,conda-forge/tensorboard-plugin-wit,,,,11.0,2.0,https://pypi.org/project/witwidget,2021-10-12 17:42:30.000,6.0,10267.0,55010.0,https://anaconda.org/conda-forge/tensorboard-plugin-wit,2023-06-16 19:20:28.498,2296211.0,,,,,3.0,,,,,wit-widget,https://www.npmjs.com/package/wit-widget,2021-10-12 17:42:50.869,3.0,586.0,,,,,,,,,,, +622,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,,111.0,26.0,36.0,34.0,69.0,879.0,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'],681.0,669.0,https://pypi.org/project/pandas-bokeh,2021-04-11 17:43:13.000,12.0,19841.0,19841.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +623,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 00:32:10.000,2024-10-12 16:41:54.000000,2024-10-12 16:34:55,60.0,3.0,75.0,6.0,5.0,3.0,25.0,849.0,scikit-learn cross validators for iterative stratification of multilabel data.,7.0,23,True,2024-10-12 16:41:54.000,0.1.9,8.0,iterative-stratification,,,,['sklearn'],510.0,495.0,https://pypi.org/project/iterative-stratification,2024-10-12 16:41:54.000,15.0,38111.0,38111.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +624,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 17:33:11,360.0,1.0,119.0,17.0,84.0,21.0,38.0,710.0,Working with molecular structures in pandas DataFrames.,18.0,23,True,2024-08-01 17:35:04.000,0.5.1,21.0,biopandas,conda-forge/biopandas,,,['pandas'],330.0,292.0,https://pypi.org/project/biopandas,2024-08-01 17:35:04.000,38.0,12164.0,15458.0,https://anaconda.org/conda-forge/biopandas,2024-08-02 05:29:18.056,164720.0,,,,,3.0,,,,BioPandas/biopandas,,,,,,,,,,,,,,,, +625,finetune,IndicoDataSolutions/finetune,nlp,,https://github.com/IndicoDataSolutions/finetune,https://github.com/IndicoDataSolutions/finetune,MPL-2.0,2018-06-12 17:02:16.000,2024-10-18 19:28:13.000000,2024-07-23 12:43:38,1508.0,,80.0,34.0,684.0,22.0,118.0,701.0,Scikit-learn style model finetuning for NLP.,23.0,23,True,2023-09-29 10:19:51.000,0.10.0,39.0,finetune,,,,"['tensorflow', 'sklearn']",15.0,13.0,https://pypi.org/project/finetune,2023-09-29 10:19:51.000,2.0,2282.0,2282.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +626,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,,81.0,21.0,12.0,,39.0,685.0,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,,,,521.0,516.0,https://pypi.org/project/vecstack,2019-08-12 16:01:22.000,5.0,12645.0,12701.0,https://anaconda.org/conda-forge/vecstack,2023-06-16 19:26:00.374,2297.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +627,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'],294.0,289.0,https://pypi.org/project/happytransformer,2023-08-05 22:54:02.000,5.0,4058.0,4058.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +628,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,,87.0,13.0,31.0,9.0,49.0,390.0,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,,,,492.0,448.0,https://pypi.org/project/pymap3d,2024-02-11 00:59:05.000,44.0,223277.0,224980.0,https://anaconda.org/conda-forge/pymap3d,2024-02-11 07:50:28.337,83493.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +629,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.,24.0,23,False,2021-09-14 22:55:51.000,0.0.49,208.0,studioml,,,,,7.0,7.0,https://pypi.org/project/studioml,2021-09-14 22:55:51.000,,8134.0,8134.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +630,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,,49.0,14.0,712.0,217.0,204.0,283.0,Asynchronous Distributed Hyperparameter Optimization.,32.0,23,False,2023-03-02 22:26:01.035,0.2.7,26.0,orion,,,,,118.0,110.0,https://pypi.org/project/orion,2022-08-22 17:10:40.826,8.0,1507.0,1507.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +631,pandas-ai,gventuri/pandas-ai,others,,https://github.com/Sinaptik-AI/pandas-ai,https://github.com/Sinaptik-AI/pandas-ai,,2023-04-22 12:58:01.000,2024-10-22 14:14:53.000000,2024-10-22 14:14:53,1076.0,38.0,1250.0,109.0,516.0,81.0,640.0,13099.0,"Chat with your database (SQL, CSV, pandas, polars, mongodb, noSQL, etc). PandasAI makes data analysis conversational..",99.0,22,False,2024-10-16 10:19:29.000,2.3.0,100.0,pandas-ai,,,,,,,https://pypi.org/project/pandas-ai,,,,,,,,,,,,3.0,,,,Sinaptik-AI/pandas-ai,,,,,,,,,,,,,,,, +632,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,,638.0,93.0,152.0,99.0,102.0,8373.0,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,,,,,2.0,,https://pypi.org/project/nebullvm,2023-06-18 11:03:00.511,2.0,1677.0,1677.0,,,,,,,,3.0,,,,nebuly-ai/optimate,,,,,,,,,,,,,,,, +633,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,,782.0,224.0,25.0,8.0,122.0,5357.0,Build Graph Nets in Tensorflow.,11.0,22,False,2020-01-29 16:00:25.000,1.1.0,7.0,graph-nets,,,,['tensorflow'],22.0,20.0,https://pypi.org/project/graph-nets,2020-01-29 16:00:25.000,2.0,3952.0,3952.0,,,,,,,,3.0,,,,google-deepmind/graph_nets,,,,,,,,,,,,,,,, +634,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,,1253.0,305.0,210.0,66.0,220.0,4895.0,"Github.com/CryptoSignal - Trading & Technical Analysis Bot - 4,100+ stars, 1,100+ forks.",28.0,22,False,,,,,,shadowreaver/crypto-signal,,,,,,,,,1690.0,,,,https://hub.docker.com/r/shadowreaver/crypto-signal,2020-09-03 13:00:35.801133,8.0,143654.0,3.0,,,,,,,,,,,,,,,,,,,, +635,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,,567.0,169.0,47.0,35.0,28.0,4526.0,High-performance TensorFlow library for quantitative finance.,47.0,22,False,,,30.0,tf-quant-finance,,,,['tensorflow'],3.0,,https://pypi.org/project/tf-quant-finance,2022-08-19 12:40:54.257,3.0,1280.0,1280.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +636,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,,476.0,84.0,180.0,108.0,161.0,3629.0,A high performance and generic framework for distributed DNN training.,21.0,22,False,2020-08-27 15:42:13.000,0.2.4,8.0,byteps,,bytepsimage/tensorflow,,,3.0,3.0,https://pypi.org/project/byteps,2021-08-02 17:37:42.000,,467.0,488.0,,,,https://hub.docker.com/r/bytepsimage/tensorflow,2020-03-03 02:33:23.358610,,1349.0,3.0,,,,,,,,,,,,,,,,,,,, +637,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 15:45:58,1602.0,3.0,514.0,148.0,610.0,86.0,75.0,3564.0,"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'],,,https://pypi.org/project/reagent,2020-05-27 20:58:01.000,,85.0,85.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +638,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,,677.0,74.0,53.0,179.0,101.0,3399.0,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'],8.0,,https://pypi.org/project/gpt-2-simple,2021-10-18 01:47:20.000,8.0,2514.0,2523.0,,,,,,,,3.0,626.0,,,,,,,,,,,,,,,,,,, +639,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'],161.0,159.0,https://pypi.org/project/trfl,2021-08-16 12:19:16.000,2.0,2446.0,2446.0,,,,,,,,3.0,,,,google-deepmind/trfl,,,,,,,,,,,,,,,, +640,opyrator,ml-tooling/opyrator,others,,https://github.com/ml-tooling/opyrator,https://github.com/ml-tooling/opyrator,MIT,2021-04-06 08:09:06.000,2024-10-23 02:35:25.000000,2021-05-06 12:10:38,127.0,,156.0,48.0,71.0,2.0,30.0,3078.0,"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,,,,54.0,54.0,https://pypi.org/project/opyrator,2021-05-04 18:48:03.000,,789.0,844.0,https://anaconda.org/conda-forge/opyrator,2023-06-18 08:40:31.958,1820.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +641,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,,454.0,164.0,120.0,22.0,112.0,2937.0,A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language..,40.0,22,False,2020-11-17 12:32:37.000,0.5.5.1,13.0,nlp-architect,,,,,11.0,11.0,https://pypi.org/project/nlp-architect,2020-04-12 11:34:38.000,,879.0,879.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +642,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,,238.0,42.0,110.0,80.0,64.0,2883.0,"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,,,,,6.0,,https://pypi.org/project/texthero,2021-07-01 17:11:02.000,6.0,3865.0,3867.0,,,,,,,,3.0,153.0,,,,,,,,,,,,,,,,,,, +643,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 19:08:06,312.0,1.0,163.0,24.0,34.0,33.0,31.0,1980.0,"Explain, analyze, and visualize NLP language models. Ecco creates interactive visualizations directly in Jupyter..",12.0,22,True,2022-01-09 21:17:53.000,0.1.2,18.0,ecco,conda-forge/ecco,,,['pytorch'],32.0,31.0,https://pypi.org/project/ecco,2022-01-09 21:14:50.000,1.0,1628.0,1793.0,https://anaconda.org/conda-forge/ecco,2023-06-16 19:28:19.211,5551.0,,,,,3.0,118.0,,,,,,,,,,,,,,,,,,, +644,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 09:41:36,346.0,1.0,341.0,42.0,68.0,163.0,95.0,1861.0,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,,,,,,,https://pypi.org/project/fast-bert,2024-08-19 09:45:05.000,,7166.0,7166.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +645,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,,255.0,44.0,14.0,57.0,35.0,1793.0,"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']",320.0,309.0,https://pypi.org/project/hiddenlayer,2020-04-24 07:32:11.000,11.0,2451.0,2451.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +646,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,,213.0,38.0,111.0,56.0,42.0,1726.0,"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'],169.0,163.0,https://pypi.org/project/sklearn-contrib-lightning,2022-01-30 00:43:43.000,6.0,4372.0,6778.0,https://anaconda.org/conda-forge/sklearn-contrib-lightning,2023-06-16 13:18:02.734,236577.0,,,,,3.0,680.0,,,,,,,,,,,,,,,,,,, +647,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,,197.0,30.0,424.0,11.0,163.0,1670.0,Graph4nlp is the library for the easy use of Graph Neural Networks for NLP. Welcome to visit our DLG4NLP website..,29.0,22,False,2022-01-20 18:07:32.000,0.5.5,12.0,graph4nlp,,,,['pytorch'],,,https://pypi.org/project/graph4nlp,2022-01-20 15:18:44.000,,1035.0,1035.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +648,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,,278.0,70.0,730.0,51.0,64.0,1591.0,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'],4.0,,https://pypi.org/project/classy_vision,2023-03-21 05:15:00.935,4.0,2654.0,3103.0,https://anaconda.org/conda-forge/classy_vision,2023-06-16 19:17:34.578,25604.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +649,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,,254.0,51.0,312.0,98.0,18.0,1588.0,Mesh TensorFlow: Model Parallelism Made Easier.,50.0,22,True,2022-05-15 21:06:13.000,0.1.21,27.0,mesh-tensorflow,,,,['tensorflow'],3.0,,https://pypi.org/project/mesh-tensorflow,2022-05-15 21:06:13.000,3.0,50720.0,50720.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +650,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,,217.0,57.0,52.0,82.0,149.0,1568.0,ThunderSVM: A Fast SVM Library on GPUs and CPUs.,37.0,22,True,2020-03-13 12:36:30.000,0.3.12,9.0,thundersvm,,,,,,,https://pypi.org/project/thundersvm,2020-03-13 12:36:30.000,,1374.0,1404.0,,,,,,,,3.0,2874.0,,,,,,,,,,,,,,,,,,, +651,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,,135.0,100.0,150.0,21.0,20.0,1550.0,Lore makes machine learning approachable for Software Engineers and maintainable for Machine Learning Researchers.,29.0,22,False,2022-02-18 18:01:38.000,0.8.6,233.0,lore,,,,,24.0,24.0,https://pypi.org/project/lore,2022-02-18 18:01:38.000,,13500.0,13500.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +652,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,,271.0,65.0,51.0,23.0,75.0,1497.0,MLBox is a powerful Automated Machine Learning python library.,9.0,22,False,2020-08-25 09:32:37.000,0.8.5,21.0,mlbox,,,,,37.0,37.0,https://pypi.org/project/mlbox,2020-08-25 09:32:37.000,,1610.0,1610.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +653,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,,352.0,61.0,47.0,37.0,71.0,1482.0,"Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition, Part-of-Speech Tagging and so on.",11.0,22,False,2018-07-17 01:59:21.000,1.0.8,14.0,anago,,,,['tensorflow'],40.0,34.0,https://pypi.org/project/anago,2018-07-17 01:59:21.000,6.0,2814.0,2814.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +654,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,,89.0,39.0,15.0,11.0,27.0,1367.0,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'],245.0,223.0,https://pypi.org/project/jraph,2022-08-12 15:25:29.659,22.0,48960.0,49139.0,https://anaconda.org/conda-forge/jraph,2023-06-16 19:27:46.249,6466.0,,,,,3.0,,,,google-deepmind/jraph,,,,,,,,,,,,,,,, +655,Sockeye,awslabs/sockeye,nlp,,https://github.com/awslabs/sockeye,https://github.com/awslabs/sockeye,Apache-2.0,2017-06-08 07:44:30.000,2024-10-24 08:18:17.000000,2024-10-24 08:17:36,836.0,1.0,324.0,50.0,798.0,11.0,300.0,1210.0,Sequence-to-sequence framework with a focus on Neural Machine Translation based on PyTorch.,60.0,22,True,2023-03-03 07:51:00.411,3.1.34,85.0,sockeye,,,,['mxnet'],,,https://pypi.org/project/sockeye,2023-03-03 07:51:00.411,,5448.0,5448.0,,,,,,,,3.0,21.0,,,,,,,,,,,,,,,,,,, +656,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 17:00:39,437.0,1.0,151.0,91.0,122.0,33.0,46.0,1185.0,PFRL: a PyTorch-based deep reinforcement learning library.,20.0,22,True,2023-07-16 15:34:00.704,0.4.0,6.0,pfrl,,,,,116.0,115.0,https://pypi.org/project/pfrl,2023-07-16 15:34:00.704,1.0,809.0,809.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +657,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,,214.0,65.0,29.0,31.0,12.0,1184.0,Anomaly Detection and Correlation library.,9.0,22,False,2016-01-20 01:01:44.000,0.3.1,5.0,luminol,,,,,82.0,80.0,https://pypi.org/project/luminol,2017-12-11 06:04:15.000,2.0,9021.0,9021.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +658,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.,20.0,22,False,2017-11-23 06:59:56.000,0.2.11,10.0,fastfm,,,,,127.0,124.0,https://pypi.org/project/fastfm,2017-11-23 06:59:56.000,3.0,1706.0,1712.0,,,,,,,,3.0,766.0,,,,,,,,,,,,,,,,,,, +659,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,,251.0,48.0,46.0,26.0,127.0,1073.0,A Tensorflow model for text recognition (CNN + seq2seq with visual attention) available as a Python package and..,28.0,22,True,2020-10-12 06:56:40.000,0.7.6,21.0,aocr,,,,['tensorflow'],30.0,30.0,https://pypi.org/project/aocr,2019-04-19 05:28:27.000,,3502.0,3502.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +660,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,,295.0,96.0,123.0,62.0,97.0,1052.0,"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'],16.0,,https://pypi.org/project/astroML,2022-03-01 20:02:01.000,16.0,3550.0,4109.0,https://anaconda.org/conda-forge/astroml,2023-06-16 13:21:24.079,48134.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +661,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,,89.0,18.0,73.0,18.0,45.0,1024.0,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,,,,,231.0,227.0,https://pypi.org/project/nnAudio,2024-02-13 05:58:29.000,4.0,15149.0,15149.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +662,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,,112.0,51.0,99.0,44.0,51.0,1018.0,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'],262.0,251.0,https://pypi.org/project/tf-explain,2021-11-18 20:57:29.000,11.0,3142.0,3142.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +663,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,,146.0,23.0,46.0,16.0,82.0,922.0,kapre: Keras Audio Preprocessors.,13.0,22,False,2022-01-21 20:10:47.000,Kapre-0.3.7,24.0,kapre,,,,['tensorflow'],2450.0,2441.0,https://pypi.org/project/kapre,2022-01-21 20:09:21.000,9.0,1952.0,1952.0,,,,,,,,3.0,29.0,,,,,,,,,,,,,,,,,,, +664,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,,86.0,18.0,160.0,20.0,94.0,863.0,Bayesian active learning library for research and industrial usecases.,23.0,22,True,2024-06-11 15:50:56.000,2.0.0,21.0,baal,conda-forge/baal,,,,64.0,62.0,https://pypi.org/project/baal,2024-06-11 15:50:56.000,2.0,5315.0,5542.0,https://anaconda.org/conda-forge/baal,2023-06-12 15:14:19.747,10257.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +665,TF Compression,tensorflow/compression,tensorflow-utils,,https://github.com/tensorflow/compression,https://github.com/tensorflow/compression,Apache-2.0,2018-05-15 23:32:19.000,2024-10-10 11:23:15.000000,2024-10-10 11:22:10,296.0,3.0,248.0,46.0,18.0,11.0,91.0,858.0,Data compression in TensorFlow.,21.0,22,True,2024-08-07 20:25:13.000,2.17.0,26.0,tensorflow-compression,,,,['tensorflow'],2.0,,https://pypi.org/project/tensorflow-compression,2024-02-02 01:38:32.000,2.0,5332.0,5332.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +666,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,,134.0,24.0,594.0,63.0,511.0,848.0,"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,,,,,6.0,,https://pypi.org/project/icevision,2022-02-10 15:55:46.374,6.0,5890.0,5890.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +667,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,,107.0,28.0,60.0,27.0,74.0,846.0,ML-Ensemble high performance ensemble learning.,7.0,22,False,2018-10-30 22:34:35.000,0.2.3,14.0,mlens,,,,,494.0,493.0,https://pypi.org/project/mlens,2018-10-30 22:30:43.000,1.0,2789.0,2789.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +668,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,,160.0,37.0,46.0,43.0,49.0,821.0,Public facing deeplift repo.,11.0,22,False,2018-07-13 21:11:52.000,0.6.6,21.0,deeplift,,,,,109.0,100.0,https://pypi.org/project/deeplift,2020-11-11 09:32:57.000,9.0,1370.0,1370.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +669,torch-cluster,rusty1s/pytorch_cluster,graph,,https://github.com/rusty1s/pytorch_cluster,https://github.com/rusty1s/pytorch_cluster,MIT,2018-01-12 20:56:06.000,2024-09-10 02:55:22.000000,2024-09-10 02:55:22,602.0,2.0,142.0,15.0,63.0,37.0,139.0,817.0,PyTorch Extension Library of Optimized Graph Cluster Algorithms.,35.0,22,True,2023-10-12 06:54:28.000,1.6.3,43.0,torch-cluster,conda-forge/pytorch_cluster,,,['pytorch'],62.0,,https://pypi.org/project/torch-cluster,2023-10-12 06:52:43.000,62.0,18059.0,22039.0,https://anaconda.org/conda-forge/pytorch_cluster,2024-08-28 13:26:28.147,210963.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +670,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,,78.0,25.0,162.0,51.0,62.0,769.0,Objax is a machine learning framework that provides an Object Oriented layer for JAX.,26.0,22,True,2023-11-06 22:17:30.000,1.8.0,11.0,objax,,,,['jax'],63.0,59.0,https://pypi.org/project/objax,2023-11-06 22:03:10.000,4.0,1424.0,1424.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +671,NeoML,neoml-lib/neoml,ml-frameworks,,https://github.com/neoml-lib/neoml,https://github.com/neoml-lib/neoml,Apache-2.0,2020-06-14 17:37:36.000,2024-10-23 17:51:18.000000,2024-09-30 12:29:20,1251.0,38.0,126.0,30.0,1059.0,37.0,54.0,765.0,Machine learning framework for both deep learning and traditional algorithms.,40.0,22,True,2023-12-26 02:42:15.000,2.0.210,15.0,neoml,,,,,2.0,2.0,https://pypi.org/project/neoml,2023-12-26 02:42:15.000,,3173.0,3173.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +672,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'],18.0,,https://pypi.org/project/gmaps,2021-12-15 15:42:57.506,13.0,9347.0,13713.0,https://anaconda.org/conda-forge/gmaps,2023-06-16 13:23:14.332,341941.0,,,,,3.0,,,,,jupyter-gmaps,https://www.npmjs.com/package/jupyter-gmaps,2019-07-21 08:49:48.715,5.0,524.0,,,,,,,,,,, +673,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,,88.0,21.0,9.0,25.0,41.0,689.0,"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'],480.0,470.0,https://pypi.org/project/pivottablejs,2018-01-15 18:14:37.000,10.0,34247.0,34275.0,https://anaconda.org/anaconda/pivottablejs,2023-12-06 04:45:55.894,2998.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +674,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,,68.0,25.0,433.0,10.0,237.0,635.0,torchbearer: A model fitting library for PyTorch.,14.0,22,True,2023-12-01 18:48:07.000,0.5.5,26.0,torchbearer,,,,['pytorch'],96.0,92.0,https://pypi.org/project/torchbearer,2023-12-01 18:48:07.000,4.0,1662.0,1662.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +675,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,,57.0,19.0,216.0,49.0,315.0,606.0,The worlds cleanest AutoML library - Do hyperparameter tuning with the right pipeline abstractions to write clean deep..,9.0,22,False,2022-08-16 19:54:29.000,0.8.1,27.0,neuraxle,,,,,66.0,65.0,https://pypi.org/project/neuraxle,2022-08-16 19:50:37.507,1.0,1199.0,1199.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +676,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 19:20:13.000,2024-09-29 18:55:40.000000,2024-09-29 18:55:40,251.0,2.0,130.0,22.0,20.0,8.0,31.0,599.0,Code to compute permutation and drop-column importances in Python scikit-learn models.,15.0,22,True,2021-01-28 23:23:17.000,1.3.7,22.0,rfpimp,,,,['sklearn'],173.0,168.0,https://pypi.org/project/rfpimp,2021-01-28 23:19:33.000,5.0,13078.0,13078.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +677,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,,105.0,9.0,15.0,6.0,16.0,582.0,Make Waffle Charts in Python.,6.0,22,True,2024-06-16 04:18:08.000,1.1.1,28.0,pywaffle,conda-forge/pywaffle,,,,418.0,412.0,https://pypi.org/project/pywaffle,2024-06-16 04:18:08.000,6.0,10256.0,10449.0,https://anaconda.org/conda-forge/pywaffle,2023-06-16 16:12:33.889,13571.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +678,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 08:06:41.000,2024-10-12 19:33:11.000000,2024-08-18 15:52:42,512.0,7.0,60.0,25.0,10.0,14.0,44.0,552.0,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']",32.0,32.0,https://pypi.org/project/small-text,2024-08-18 16:00:34.000,,2196.0,2559.0,https://anaconda.org/conda-forge/small-text,2024-08-18 16:37:29.577,9825.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +679,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,,101.0,26.0,8.0,1.0,33.0,520.0,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,,,,,30.0,27.0,https://pypi.org/project/autoviml,2024-05-11 10:46:51.000,3.0,34257.0,34257.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +680,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,,48.0,9.0,10.0,13.0,21.0,498.0,apricot implements submodular optimization for the purpose of selecting subsets of massive data sets to train machine..,4.0,22,False,2023-11-17 16:33:58.000,0.6.1,14.0,apricot-select,,,,,153.0,145.0,https://pypi.org/project/apricot-select,2021-02-18 06:55:02.000,8.0,8350.0,8350.0,,,,,,,,3.0,29.0,,,,,,,,,,,,,,,,,,, +681,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,,103.0,36.0,276.0,76.0,174.0,488.0,"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,,,,,87.0,85.0,https://pypi.org/project/tick,2020-05-24 22:01:17.000,2.0,2773.0,2777.0,,,,,,,,3.0,383.0,,,,,,,,,,,,,,,,,,, +682,pydlm,wwrechard/pydlm,time-series-data,,https://github.com/wwrechard/pydlm,https://github.com/wwrechard/pydlm,BSD-3-Clause,2016-06-29 07:58:53.000,2024-09-07 07:05:09.000000,2024-09-07 07:05:06,387.0,15.0,98.0,28.0,34.0,41.0,15.0,475.0,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,,,,,39.0,37.0,https://pypi.org/project/pydlm,2024-08-13 04:20:45.000,2.0,27874.0,27874.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +683,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 09:24:26,399.0,3.0,102.0,18.0,9.0,7.0,49.0,455.0,"A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4.5, CART, CHAID and Regression Trees; some..",7.0,22,True,2024-06-08 21:33:50.000,0.0.18,18.0,chefboost,,,,,61.0,61.0,https://pypi.org/project/chefboost,2024-06-08 21:33:50.000,,5700.0,5700.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +684,TimeSide,Parisson/TimeSide,audio,,https://github.com/Parisson/TimeSide,https://github.com/Parisson/TimeSide,AGPL-3.0,2011-11-21 21:48:08.000,2024-10-14 17:26:35.000000,2024-10-14 15:20:39,3847.0,8.0,60.0,28.0,110.0,33.0,184.0,369.0,scalable audio processing framework and server written in Python.,23.0,22,False,2023-01-03 17:34:09.000,1.1.3,28.0,TimeSide,,,,,19.0,19.0,https://pypi.org/project/TimeSide,2020-11-27 09:33:19.000,,807.0,807.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +685,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,,33.0,12.0,9.0,4.0,12.0,238.0,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,,,,1274.0,1217.0,https://pypi.org/project/py3nvml,2021-11-22 14:30:25.000,57.0,90804.0,92523.0,https://anaconda.org/conda-forge/py3nvml,2023-09-25 06:14:21.168,82512.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +686,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,,29.0,7.0,20.0,5.0,9.0,155.0,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,,,,,2418.0,2374.0,https://pypi.org/project/stop-words,2018-07-23 20:55:55.000,44.0,104134.0,104134.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +687,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,,2441.0,149.0,89.0,255.0,286.0,13510.0,End-to-End Object Detection with Transformers.,27.0,21,True,2020-06-29 16:41:01.000,0.2,1.0,,,,,['pytorch'],21.0,21.0,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +688,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 19:09:33,193.0,2.0,1210.0,95.0,51.0,409.0,287.0,6587.0,PySlowFast: video understanding codebase from FAIR for reproducing state-of-the-art video models.,33.0,21,True,,,1.0,pyslowfast,,,,['pytorch'],20.0,20.0,https://pypi.org/project/pyslowfast,2020-01-15 23:51:07.000,,111.0,111.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +689,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,,820.0,229.0,111.0,57.0,622.0,4928.0,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,,,,,,,,,,,,20.0,,,,,,,,3.0,1534.0,,,,,,,,,,,,,,,,,,, +690,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,,742.0,102.0,35.0,107.0,113.0,4639.0,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,,idealo/image-super-resolution-gpu,,['tensorflow'],5.0,,https://pypi.org/project/ISR,2020-01-08 15:37:35.000,5.0,5583.0,5586.0,,,,https://hub.docker.com/r/idealo/image-super-resolution-gpu,2019-04-01 13:48:45.697251,1.0,245.0,3.0,,,,,,,,,,,,,,,,,,,, +691,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,,357.0,102.0,16.0,53.0,17.0,3414.0,"Debugging, monitoring and visualization for Python Machine Learning and Data Science.",15.0,21,False,2020-03-04 07:26:22.000,0.9.1,14.0,tensorwatch,,,,,161.0,154.0,https://pypi.org/project/tensorwatch,2020-03-04 07:26:22.000,7.0,1112.0,1112.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +692,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,,172.0,66.0,54.0,6.0,44.0,3085.0,"a delightful machine learning tool that allows you to train, test, and use models without writing code.",20.0,21,False,2021-11-19 16:51:47.000,1.0.0,34.0,igel,,,,,6.0,6.0,https://pypi.org/project/igel,2021-11-19 16:45:29.543,,2562.0,2562.0,,,,,,,,3.0,49.0,,,,,,,,,,,,,,,,,,, +693,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,,398.0,101.0,54.0,64.0,48.0,2940.0,Quickly search over billions of images.,19.0,21,False,2017-02-13 14:54:48.000,1.1.2,10.0,image_match,,,,,4.0,,https://pypi.org/project/image_match,2017-02-13 14:54:48.000,4.0,1240.0,1240.0,,,,,,,,3.0,,,,rhsimplex/image-match,,,,,,,,,,,,,,,, +694,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,,330.0,72.0,2.0,20.0,7.0,2905.0,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'],214.0,211.0,https://pypi.org/project/adabound,2019-02-26 04:23:45.000,3.0,5433.0,5433.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +695,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,,462.0,126.0,225.0,90.0,183.0,2328.0,Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning..,38.0,21,False,2019-10-10 14:17:10.000,1.0.1,13.0,rl_coach,,,,,2.0,,https://pypi.org/project/rl_coach,2019-10-10 14:17:10.000,2.0,329.0,329.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +696,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,,370.0,84.0,4.0,5.0,18.0,2214.0,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,,,,,51.0,51.0,https://pypi.org/project/pdftabextract,2018-01-09 08:00:24.000,,593.0,593.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +697,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,,251.0,54.0,35.0,16.0,105.0,2112.0,"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'],,,https://pypi.org/project/reformer-pytorch,2021-11-06 23:09:00.000,,12270.0,12270.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +698,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,,159.0,19.0,74.0,24.0,42.0,1805.0,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'],33.0,33.0,https://pypi.org/project/pythae,2023-09-06 15:46:59.000,,2248.0,2248.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +699,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,,200.0,38.0,7.0,15.0,33.0,1655.0,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'],70.0,64.0,https://pypi.org/project/antialiased-cnns,2020-10-23 22:42:49.000,6.0,7635.0,7635.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +700,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,,405.0,101.0,36.0,13.0,24.0,1429.0,Deep Learning Toolkit for Medical Image Analysis.,9.0,21,False,2018-02-26 17:43:57.000,0.2.1,5.0,dltk,,,,['tensorflow'],33.0,33.0,https://pypi.org/project/dltk,2018-02-26 17:43:57.000,,313.0,313.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +701,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,,222.0,64.0,48.0,40.0,90.0,1277.0,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'],37.0,37.0,https://pypi.org/project/tensorrec,2019-04-02 00:53:47.000,,849.0,849.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +702,NGT,yahoojapan/NGT,nn-search,,https://github.com/yahoojapan/NGT,https://github.com/yahoojapan/NGT,Apache-2.0,2016-09-01 07:36:57.000,2024-09-18 00:15:10.000000,2024-09-18 00:14:54,196.0,1.0,113.0,39.0,30.0,20.0,119.0,1249.0,Nearest Neighbor Search with Neighborhood Graph and Tree for High-dimensional Data.,15.0,21,True,2024-07-26 00:44:37.000,2.2.4,84.0,ngt,,,,,8.0,,https://pypi.org/project/ngt,2023-12-06 05:33:15.000,8.0,6216.0,6216.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +703,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,,202.0,64.0,7.0,13.0,29.0,1148.0,Python AutoML for Trading Systems and Sports Betting.,5.0,21,True,2020-08-29 18:48:20.000,2.5.0,25.0,alphapy,,,,,6.0,6.0,https://pypi.org/project/alphapy,2020-08-29 18:44:15.000,,6655.0,6655.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +704,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,,144.0,25.0,77.0,51.0,37.0,1090.0,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,,,,5.0,,https://pypi.org/project/adtk,2020-04-17 02:18:00.000,5.0,280316.0,280479.0,https://anaconda.org/conda-forge/adtk,2023-06-16 19:18:16.533,8977.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +705,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,,184.0,52.0,12.0,16.0,42.0,1003.0,High level network definitions with pre-trained weights in TensorFlow.,6.0,21,False,2020-03-31 04:38:27.000,0.4.6,12.0,tensornets,,,,['tensorflow'],88.0,84.0,https://pypi.org/project/tensornets,2020-03-31 04:35:15.000,4.0,377.0,377.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +706,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,,129.0,18.0,25.0,28.0,39.0,844.0,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,,,,26.0,,https://pypi.org/project/pdpbox,2021-03-14 16:21:17.000,26.0,17249.0,17595.0,https://anaconda.org/conda-forge/pdpbox,2023-06-10 14:57:37.569,21813.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +707,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,,114.0,34.0,561.0,211.0,246.0,764.0,"NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems, from feature..",32.0,21,True,2024-06-14 12:19:07.000,24.06.00,16.0,merlin-core,,,,,1.0,,https://pypi.org/project/merlin-core,2023-08-29 16:27:32.000,1.0,10532.0,10532.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +708,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,,141.0,25.0,19.0,26.0,5.0,745.0,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'],671.0,663.0,https://pypi.org/project/treeinterpreter,2021-01-10 20:12:39.000,8.0,42487.0,42665.0,https://anaconda.org/conda-forge/treeinterpreter,2023-06-16 19:22:55.011,8558.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +709,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,,,,,35.0,,https://pypi.org/project/test_tube,2019-12-01 01:19:50.000,35.0,41408.0,41408.0,,,,,,,,3.0,26.0,,,,,,,,,,,,,,,,,,, +710,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,,107.0,30.0,1.0,15.0,3.0,642.0,(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']",681.0,664.0,https://pypi.org/project/combo,2022-04-02 16:20:07.000,17.0,18521.0,18521.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +711,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,,,,,228.0,220.0,https://pypi.org/project/tensorboard_logger,2018-02-08 07:28:51.000,8.0,17264.0,17264.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +712,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,,96.0,26.0,32.0,35.0,6.0,618.0,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'],409.0,401.0,https://pypi.org/project/skope-rules,2020-01-25 12:01:37.000,8.0,21574.0,21574.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +713,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.,11.0,21,False,2019-07-30 12:47:43.000,1.0,8.0,hpbandster,conda-forge/hpbandster,,,,499.0,474.0,https://pypi.org/project/hpbandster,2018-11-06 12:56:55.000,25.0,7331.0,7757.0,https://anaconda.org/conda-forge/hpbandster,2023-06-16 19:24:00.330,19598.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +714,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,,87.0,7.0,20.0,4.0,92.0,588.0,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,,,,,76.0,74.0,https://pypi.org/project/featurewiz,2024-02-10 13:12:00.000,2.0,54220.0,54220.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +715,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,,64.0,26.0,31.0,5.0,24.0,570.0,Python module for machine learning time series:.,14.0,21,False,2022-08-27 09:04:02.113,1.2.5,24.0,seglearn,,,,,53.0,51.0,https://pypi.org/project/seglearn,2021-03-13 16:18:30.000,2.0,2687.0,2687.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +716,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,,63.0,17.0,114.0,8.0,48.0,569.0,A simplified framework and utilities for PyTorch.,23.0,21,False,2024-07-08 19:12:54.000,1.17.2,38.0,poutyne,,,,['pytorch'],148.0,143.0,https://pypi.org/project/poutyne,2024-07-08 19:15:42.000,5.0,4929.0,4929.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +717,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,,58.0,10.0,21.0,16.0,37.0,558.0,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,,,,458.0,449.0,https://pypi.org/project/joypy,2021-12-19 09:42:50.000,9.0,13101.0,13521.0,https://anaconda.org/conda-forge/joypy,2023-06-16 16:14:43.440,28172.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +718,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,,167.0,56.0,20.0,39.0,60.0,548.0,Bayesian inference in HSMMs and HMMs.,13.0,21,False,2017-05-10 17:14:37.000,0.1.7,8.0,pyhsmm,,,,,34.0,33.0,https://pypi.org/project/pyhsmm,2017-05-10 17:14:37.000,1.0,405.0,405.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +719,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 15:04:58.000,2024-10-24 10:08:52.000000,2024-10-24 10:08:52,1777.0,6.0,77.0,10.0,219.0,50.0,82.0,546.0,Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations.,21.0,21,False,2023-12-05 11:42:47.000,0.5.3,27.0,quantus,,,,,36.0,35.0,https://pypi.org/project/quantus,2023-12-05 11:42:47.000,1.0,2414.0,2421.0,,,,,,,,3.0,241.0,,,,,,,,,,,,,,,,,,, +720,Popmon,ing-bank/popmon,data-viz,,https://github.com/ing-bank/popmon,https://github.com/ing-bank/popmon,MIT,2020-04-23 11:21:14.000,2024-09-23 04:22:16.000000,2023-07-18 10:24:07,542.0,,35.0,14.0,225.0,15.0,40.0,497.0,Monitor the stability of a Pandas or Spark dataframe.,17.0,21,False,2023-07-18 10:32:00.587,1.4.6,36.0,popmon,,,,"['pandas', 'spark']",24.0,22.0,https://pypi.org/project/popmon,2023-07-18 10:32:00.587,2.0,25285.0,25289.0,,,,,,,,3.0,243.0,,,,,,,,,,,,,,,,,,, +721,pykale,pykale/pykale,others,,https://github.com/pykale/pykale,https://github.com/pykale/pykale,MIT,2020-06-30 08:06:10.000,2024-10-04 17:41:19.000000,2024-09-24 15:52:47,3054.0,20.0,64.0,12.0,268.0,11.0,112.0,439.0,Knowledge-Aware machine LEarning (KALE): accessible machine learning from multiple sources for interdisciplinary..,25.0,21,True,2023-07-13 11:41:03.541,0.1.2,12.0,pykale,,,,['pytorch'],4.0,4.0,https://pypi.org/project/pykale,2022-04-12 08:56:50.000,,782.0,782.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +722,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,,25.0,9.0,9.0,2.0,9.0,424.0,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'],1948.0,1942.0,https://pypi.org/project/julius,2022-09-20 06:43:57.063,6.0,440102.0,440102.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +723,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,,79.0,24.0,12.0,48.0,49.0,415.0,optimization routines for hyperparameter tuning.,9.0,21,False,2015-09-30 05:02:00.000,1.1.1,6.0,optunity,,,,,136.0,133.0,https://pypi.org/project/optunity,2015-09-30 05:02:00.000,3.0,4899.0,4899.0,,,,,,,,3.0,104.0,,,,,,,,,,,,,,,,,,, +724,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 18:18:33,183.0,5.0,38.0,9.0,32.0,17.0,20.0,410.0,A python package for animating plots build on matplotlib.,7.0,21,True,2024-08-29 18:26:55.000,0.4.3,11.0,animatplot,conda-forge/animatplot,,,,64.0,60.0,https://pypi.org/project/animatplot,2024-08-29 17:08:23.000,4.0,2307.0,2614.0,https://anaconda.org/conda-forge/animatplot,2024-09-01 04:12:59.669,14767.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +725,tsflex,predict-idlab/tsflex,time-series-data,,https://github.com/predict-idlab/tsflex,https://github.com/predict-idlab/tsflex,MIT,2021-07-06 15:16:45.577,2024-09-06 09:28:23.000000,2024-09-06 09:27:10,824.0,3.0,26.0,8.0,78.0,33.0,23.0,399.0,Flexible time series feature extraction & processing.,6.0,21,True,2024-09-06 09:28:53.000,0.4.1,38.0,tsflex,conda-forge/tsflex,,,,19.0,17.0,https://pypi.org/project/tsflex,2024-09-06 09:26:32.000,2.0,2141.0,2819.0,https://anaconda.org/conda-forge/tsflex,2024-04-08 09:54:58.786,26475.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +726,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,,49.0,17.0,2.0,12.0,3.0,378.0,(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,,,,,542.0,534.0,https://pypi.org/project/suod,2024-02-08 01:53:44.000,8.0,9210.0,9210.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +727,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,,88.0,29.0,319.0,75.0,27.0,375.0,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'],7.0,,https://pypi.org/project/tensorflow-cloud,2021-06-17 01:15:10.000,7.0,33552.0,33552.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +728,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,,49.0,11.0,37.0,29.0,37.0,353.0,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,,,,,257.0,241.0,https://pypi.org/project/impyute,2017-05-31 08:31:47.000,16.0,4297.0,4297.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +729,upgini,upgini/upgini,tabular,,https://github.com/upgini/upgini,https://github.com/upgini/upgini,BSD-3-Clause,2021-12-08 21:53:58.000,2024-10-21 12:21:39.000000,2024-10-21 12:21:10,796.0,41.0,25.0,5.0,300.0,5.0,,314.0,Data search & enrichment library for Machine Learning Easily find and add relevant features to your ML & AI pipeline..,13.0,21,True,2024-10-21 12:21:39.000,1.2.15,836.0,upgini,,,,,9.0,9.0,https://pypi.org/project/upgini,2024-10-21 12:21:39.000,,40032.0,40032.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +730,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,,36.0,18.0,6.0,19.0,21.0,310.0,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'],119.0,116.0,https://pypi.org/project/dm-launchpad,2022-04-28 06:23:38.000,3.0,2792.0,2792.0,,,,,,,,3.0,,,,google-deepmind/launchpad,,,,,,,,,,,,,,,, +731,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.,29.0,21,False,2021-01-25 14:05:21.000,0.12.2,39.0,textpipe,,,,,11.0,10.0,https://pypi.org/project/textpipe,2021-01-25 14:05:21.000,1.0,1393.0,1393.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +732,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']",20.0,18.0,https://pypi.org/project/sk-dist,2020-05-14 22:20:14.000,2.0,504839.0,504839.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +733,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 17:15:47,524.0,4.0,57.0,14.0,90.0,26.0,39.0,274.0,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,,,,,24.0,21.0,https://pypi.org/project/omlt,2024-08-26 15:06:41.000,3.0,13941.0,13941.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +734,Glow,projectglow/glow,medical-data,,https://github.com/projectglow/glow,https://github.com/projectglow/glow,Apache-2.0,2019-10-04 21:26:47.000,2024-10-20 03:18:37.000000,2024-10-20 03:18:35,495.0,6.0,109.0,20.0,560.0,58.0,126.0,269.0,An open-source toolkit for large-scale genomic analysis.,28.0,21,False,2024-10-20 03:22:37.000,2.0.3,17.0,glow.py,conda-forge/glow,,,,,,https://pypi.org/project/glow.py,2024-03-12 08:52:09.000,,59621.0,59739.0,https://anaconda.org/conda-forge/glow,2024-03-13 03:00:18.463,5179.0,,,,,3.0,113.0,,,,,,,,,,,,,,,,,,, +735,somoclu,peterwittek/somoclu,distributed-ml,,https://github.com/peterwittek/somoclu,https://github.com/peterwittek/somoclu,MIT,2013-01-16 06:33:16.000,2024-09-13 04:58:28.982000,2024-01-18 11:58:51,626.0,,69.0,28.0,32.0,33.0,113.0,268.0,"Massively parallel self-organizing maps: accelerate training on multicore CPUs, GPUs, and clusters.",20.0,21,False,2023-02-18 02:51:08.166,1.7.6,18.0,somoclu,conda-forge/somoclu,,,,18.0,,https://pypi.org/project/somoclu,2023-02-18 02:51:08.166,18.0,4828.0,7433.0,https://anaconda.org/conda-forge/somoclu,2024-09-13 04:58:28.982,124242.0,,,,,3.0,2057.0,,,,,,,,,,,,,,,,,,, +736,pyRDF2Vec,IBCNServices/pyRDF2Vec,graph,,https://github.com/predict-idlab/pyRDF2Vec,https://github.com/predict-idlab/pyRDF2Vec,MIT,2019-06-13 11:36:12.000,2024-10-14 06:26:53.000000,2023-07-02 18:02:16,1462.0,,50.0,15.0,213.0,21.0,64.0,246.0,Python Implementation and Extension of RDF2Vec.,7.0,21,False,2021-06-09 10:56:14.000,0.2.3,11.0,pyrdf2vec,,,,,51.0,45.0,https://pypi.org/project/pyrdf2vec,2021-06-09 10:56:14.000,6.0,801.0,801.0,,,,,,,,3.0,,,,predict-idlab/pyRDF2Vec,,,,,,,,,,,,,,,, +737,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 06:53:17,591.0,1.0,35.0,24.0,644.0,21.0,129.0,243.0,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,,,,,10.0,10.0,https://pypi.org/project/larq-compute-engine,2024-06-21 07:18:03.000,,5906.0,5927.0,,,,,,,,3.0,1219.0,,,,,,,,,,,,,,,,,,, +738,numerizer,jaidevd/numerizer,nlp,,https://github.com/jaidevd/numerizer,https://github.com/jaidevd/numerizer,MIT,2019-12-02 07:00:34.000,2024-09-26 08:36:59.000000,2024-09-26 08:31:01,28.0,4.0,23.0,8.0,13.0,4.0,11.0,219.0,A Python module to convert natural language numerics into ints and floats.,4.0,21,False,2024-09-26 08:36:59.000,0.2.4,12.0,numerizer,,,,,95.0,92.0,https://pypi.org/project/numerizer,2024-09-26 08:36:59.000,3.0,24928.0,24928.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +739,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,,1717.0,19.0,19.0,72.0,24.0,5106.0,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,,,,,,,https://pypi.org/project/deepmatcher,2021-06-13 01:13:24.000,,5251.0,5251.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +740,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,,322.0,58.0,242.0,175.0,111.0,3194.0,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,,,,,2.0,,https://pypi.org/project/lightseq,2022-11-03 06:46:55.989,2.0,6033.0,6044.0,,,,,,,,3.0,694.0,,,,,,,,,,,,,,,,,,, +741,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,,332.0,101.0,1000.0,94.0,263.0,2856.0,"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,,,,,,,,,,,,,,,,,,,, +742,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,,831.0,84.0,30.0,46.0,80.0,2674.0,DeepWalk - Deep Learning for Graphs.,10.0,20,False,2018-04-29 21:05:18.000,1.0.3,4.0,deepwalk,,,,,74.0,74.0,https://pypi.org/project/deepwalk,2018-04-29 21:05:18.000,,769.0,769.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +743,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,,237.0,61.0,106.0,27.0,56.0,2136.0,"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'],20.0,20.0,https://pypi.org/project/pycls,2020-09-05 00:21:00.000,,1532.0,1532.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +744,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,,181.0,55.0,895.0,129.0,586.0,1932.0,"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 16:17:31.557,1057.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +745,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,,281.0,31.0,41.0,34.0,176.0,1865.0,A library for graph deep learning research.,50.0,20,False,2023-04-07 20:33:15.000,1.1.0,10.0,dig,,,,,,,https://pypi.org/project/dig,2015-08-23 10:30:20.000,,686.0,686.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +746,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,,104.0,39.0,31.0,30.0,79.0,1814.0,"A flexible, intuitive and fast forecasting library.",10.0,20,True,2024-01-18 18:33:20.000,1.0.0,11.0,greykite,,,,,34.0,34.0,https://pypi.org/project/greykite,2024-01-12 20:13:07.000,,7879.0,7880.0,,,,,,,,3.0,36.0,,,,,,,,,,,,,,,,,,, +747,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,,118.0,38.0,11.0,39.0,51.0,1626.0,"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,,,,,9.0,,https://pypi.org/project/pymagnitude,2020-05-25 11:26:36.000,9.0,4113.0,4113.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +748,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,,292.0,67.0,202.0,5.0,74.0,1592.0,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,,zh794390558/delta,,['tensorflow'],2.0,2.0,https://pypi.org/project/delta-nlp,2020-03-27 04:46:19.000,,204.0,406.0,,,,https://hub.docker.com/r/zh794390558/delta,2021-08-03 14:50:00.516864,,13131.0,3.0,,,,,,,,,,,,,,,,,,,, +749,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,,156.0,46.0,3.0,13.0,15.0,1532.0,"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'],32.0,32.0,https://pypi.org/project/lambda-networks,2020-11-18 08:19:23.000,,2584.0,2584.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +750,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,,258.0,56.0,65.0,8.0,31.0,1382.0,Advbox is a toolbox to generate adversarial examples that fool neural networks in..,19.0,20,False,2018-12-05 02:48:50.000,0.4.1,2.0,advbox,,,,,4.0,4.0,https://pypi.org/project/advbox,2018-12-05 02:48:50.000,,1081.0,1081.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +751,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,,187.0,19.0,262.0,88.0,94.0,1351.0,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']",6.0,,https://pypi.org/project/dice-ml,2023-10-27 03:54:06.000,6.0,30814.0,30814.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +752,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,,,,,171.0,169.0,https://pypi.org/project/doc2text,2016-09-06 21:59:21.000,2.0,3010.0,3010.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +753,UForm,unum-cloud/uform,nlp,,https://github.com/unum-cloud/uform,https://github.com/unum-cloud/uform,Apache-2.0,2023-02-21 10:04:40.000,2024-10-01 18:35:24.000000,2024-10-01 18:33:14,293.0,4.0,62.0,15.0,62.0,9.0,21.0,1040.0,"Pocket-Sized Multimodal AI for content understanding and generation across multilingual texts, images, and video, up..",18.0,20,True,2024-10-01 18:35:24.000,3.0.3,35.0,uform,,,,['pytorch'],8.0,6.0,https://pypi.org/project/uform,2024-10-01 18:35:24.000,2.0,2792.0,2813.0,,,,,,,,3.0,430.0,,,,,,,,,,,,,,,,,,, +754,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,,,,184.0,182.0,https://pypi.org/project/geoplotlib,2016-07-27 14:55:01.000,2.0,699.0,930.0,https://anaconda.org/conda-forge/geoplotlib,2023-06-16 19:26:09.140,9476.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +755,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,,131.0,36.0,16.0,9.0,4.0,926.0,Nudity detection with Python.,12.0,20,False,2020-11-23 13:49:17.000,0.5.1,10.0,nudepy,,,,,3642.0,3637.0,https://pypi.org/project/nudepy,2020-11-23 13:49:17.000,5.0,867.0,867.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +756,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,,179.0,19.0,42.0,23.0,60.0,914.0,"A library for experimenting with, training and evaluating neural networks, with a focus on adversarial robustness.",13.0,20,False,2020-12-01 06:11:12.000,1.2.1.post2,10.0,robustness,conda-forge/robustness,,,,195.0,192.0,https://pypi.org/project/robustness,2020-12-01 06:21:33.000,3.0,1060.0,1258.0,https://anaconda.org/conda-forge/robustness,2023-06-16 19:21:11.893,9928.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +757,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,,85.0,23.0,49.0,16.0,17.0,835.0,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'],33.0,27.0,https://pypi.org/project/evojax,2024-06-18 06:17:13.000,6.0,2791.0,3741.0,https://anaconda.org/conda-forge/evojax,2024-06-18 11:07:15.191,30415.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +758,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'],47.0,47.0,https://pypi.org/project/sklearn-deap,2021-07-30 15:13:54.000,,1075.0,1075.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +759,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,,147.0,36.0,33.0,26.0,39.0,765.0,"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,,,,,116.0,116.0,https://pypi.org/project/NearPy,2016-09-27 13:03:12.000,,800.0,800.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +760,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,,114.0,19.0,26.0,2.0,87.0,729.0,"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,,,,,,,https://pypi.org/project/auto-ts,2024-05-05 11:51:57.000,,18314.0,18314.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +761,dabl,amueller/dabl,sklearn-utils,,https://github.com/amueller/dabl,https://github.com/amueller/dabl,BSD-3-Clause,2020-01-30 18:26:49.000,2024-10-23 21:48:40.000000,2024-08-07 21:38:41,314.0,7.0,106.0,5.0,3.0,1.0,,722.0,Data Analysis Baseline Library.,24.0,20,True,2024-08-07 20:31:21.000,0.3.1,19.0,dabl,,,,['sklearn'],3.0,,https://pypi.org/project/dabl,2024-08-07 20:31:21.000,3.0,7712.0,7712.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +762,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,,103.0,23.0,26.0,45.0,61.0,612.0,Build fully-functioning computer vision models with PyTorch.,12.0,20,False,2022-02-02 00:22:07.000,1.2.2,13.0,detecto,conda-forge/detecto,,,['pytorch'],186.0,184.0,https://pypi.org/project/detecto,2022-02-02 00:12:06.000,2.0,4697.0,4820.0,https://anaconda.org/conda-forge/detecto,2023-06-16 19:26:16.964,4926.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +763,opytimizer,gugarosa/opytimizer,hyperopt,,https://github.com/gugarosa/opytimizer,https://github.com/gugarosa/opytimizer,Apache-2.0,2017-11-01 16:04:01.000,2024-10-22 13:32:17.000000,2024-08-18 17:07:49,821.0,2.0,40.0,15.0,18.0,,22.0,602.0,Opytimizer is a Python library consisting of meta-heuristic optimization algorithms.,4.0,20,True,2024-08-18 17:19:42.000,3.1.4,28.0,opytimizer,,,,,19.0,19.0,https://pypi.org/project/opytimizer,2024-08-18 17:19:42.000,,1435.0,1435.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +764,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,,75.0,39.0,17.0,14.0,22.0,569.0,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,,,,,39.0,35.0,https://pypi.org/project/n2,2020-10-16 03:10:01.000,4.0,449.0,449.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +765,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,,57.0,60.0,9.0,25.0,25.0,546.0,Python library assists deep learning on graphs.,18.0,20,True,2021-09-05 23:08:21.000,0.2.1,5.0,deepsnap,,,,,116.0,114.0,https://pypi.org/project/deepsnap,2021-09-05 22:57:16.000,2.0,912.0,912.0,,,,,,,,3.0,13.0,,,,,,,,,,,,,,,,,,, +766,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,,140.0,56.0,72.0,18.0,71.0,526.0,"Auto Tune Models - A multi-tenant, multi-data system for automated machine learning (model selection and tuning).",17.0,20,False,2019-07-30 09:28:26.000,0.2.2,14.0,atm,,,,,22.0,22.0,https://pypi.org/project/atm,2019-07-30 09:25:11.000,,1845.0,1845.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +767,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,,109.0,19.0,57.0,26.0,21.0,495.0,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,,,,,85.0,77.0,https://pypi.org/project/rrcf,2023-04-30 02:25:49.592,8.0,5018.0,5018.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +768,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,,32.0,16.0,148.0,40.0,66.0,469.0,A High Level API for Deep Learning in JAX.,18.0,20,False,2022-03-23 21:51:07.000,0.8.6,33.0,elegy,,,,"['tensorflow', 'jax']",54.0,54.0,https://pypi.org/project/elegy,2022-04-22 15:42:03.000,,3477.0,3477.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +769,pymdp,infer-actively/pymdp,others,,https://github.com/infer-actively/pymdp,https://github.com/infer-actively/pymdp,MIT,2019-11-27 19:03:35.000,2024-10-03 08:28:42.000000,2024-07-16 08:32:27,987.0,,85.0,31.0,98.0,17.0,27.0,457.0,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,,,,,13.0,13.0,https://pypi.org/project/inferactively-pymdp,2022-12-08 15:25:01.498,,1272.0,1272.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +770,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,,129.0,34.0,325.0,84.0,132.0,335.0,Brain Imaging Analysis Kit.,35.0,20,True,2019-08-27 23:52:29.000,0.9.1,15.0,brainiak,,brainiak/brainiak,,,,,https://pypi.org/project/brainiak,2020-10-15 20:45:08.000,,1079.0,1097.0,,,,https://hub.docker.com/r/brainiak/brainiak,2020-10-15 21:11:03.379549,1.0,1875.0,3.0,,,,,,,,,,,,,,,,,,,, +771,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'],257.0,257.0,https://pypi.org/project/mxboard,2018-05-22 20:25:51.000,,3328.0,3328.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +772,vegafusion,vegafusion/vegafusion,data-viz,,https://github.com/vega/vegafusion,https://github.com/vega/vegafusion,BSD-3-Clause,2021-10-01 09:19:27.000,2024-10-19 19:34:24.000000,2024-08-14 15:39:49,663.0,2.0,18.0,23.0,369.0,50.0,87.0,321.0,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,,,,5.0,,https://pypi.org/project/vegafusion-jupyter,2024-05-09 19:01:07.000,2.0,3868.0,12458.0,https://anaconda.org/conda-forge/vegafusion-python-embed,2024-05-10 13:02:13.580,253742.0,,,,,3.0,7680.0,,,vega/vegafusion,vegafusion-jupyter,https://www.npmjs.com/package/vegafusion-jupyter,2024-05-09 19:11:31.675,3.0,173.0,,,,,,,,,,, +773,PipelineDP,OpenMined/PipelineDP,privacy-ml,,https://github.com/OpenMined/PipelineDP,https://github.com/OpenMined/PipelineDP,Apache-2.0,2021-02-10 18:04:22.000,2024-10-17 15:32:02.000000,2024-10-17 15:32:02,431.0,9.0,76.0,21.0,447.0,27.0,51.0,275.0,PipelineDP is a Python framework for applying differentially private aggregations to large datasets using batch..,32.0,20,False,2023-10-25 10:51:36.000,0.2.1,23.0,pipeline-dp,,,,,4.0,4.0,https://pypi.org/project/pipeline-dp,2023-11-22 19:01:05.000,,789.0,789.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +774,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,,21.0,18.0,464.0,90.0,76.0,236.0,Functional tensors for probabilistic programming.,11.0,20,False,2023-08-31 18:37:22.000,0.4.6,12.0,funsor,,,,['pytorch'],83.0,73.0,https://pypi.org/project/funsor,2023-01-23 08:32:39.757,10.0,7236.0,7236.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +775,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,,,,,448.0,446.0,https://pypi.org/project/pyfasttext,2018-12-08 15:32:09.000,2.0,1621.0,1625.0,,,,,,,,3.0,418.0,,,,,,,,,,,,,,,,,,, +776,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,,785.0,338.0,58.0,2.0,,6764.0,Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!.,7.0,19,False,2018-02-17 00:12:46.000,2018.1.2,18.0,SerpentAI,,,,,,,https://pypi.org/project/SerpentAI,2018-02-17 00:12:46.000,,616.0,623.0,,,,,,,,3.0,377.0,,,,,,,,,,,,,,,,,,, +777,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,,279.0,31.0,22.0,34.0,37.0,3201.0,A small package to create visualizations of PyTorch execution graphs.,6.0,19,False,,,,,,,,,2226.0,2226.0,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +778,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,,178.0,24.0,20.0,18.0,30.0,1708.0,Platform for designing and evaluating Graph Neural Networks (GNN).,6.0,19,False,2022-03-24 23:28:17.000,0.4.0,3.0,graphgym,,,,,8.0,8.0,https://pypi.org/project/graphgym,2022-03-24 23:19:13.000,,329.0,330.0,,,,,,,,3.0,46.0,,,,,,,,,,,,,,,,,,, +779,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,,71.0,27.0,1005.0,127.0,65.0,1650.0,Version control for machine learning.,17.0,19,False,2021-03-11 21:15:01.000,0.4.2,7.0,keepsake,,,,,1.0,,https://pypi.org/project/keepsake,2021-01-25 21:51:16.000,1.0,554.0,554.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +780,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,,254.0,52.0,13.0,20.0,13.0,1546.0,Open-source implementation of Google Vizier for hyper parameters tuning.,11.0,19,False,2018-10-18 02:54:09.000,0.1.6,4.0,advisor,,tobegit3hub/advisor,,,,,https://pypi.org/project/advisor,2018-10-18 02:54:09.000,,1423.0,1442.0,,,,https://hub.docker.com/r/tobegit3hub/advisor,2019-11-11 07:09:57.869705,,1692.0,3.0,,,,,,,,,,,,,,,,,,,, +781,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,,172.0,43.0,6.0,4.0,7.0,1111.0,XAI - An eXplainability toolbox for machine learning.,3.0,19,False,2021-10-30 06:35:19.000,0.1.0,6.0,xai,,,,,32.0,32.0,https://pypi.org/project/xai,2021-10-30 06:33:26.000,,388.0,388.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +782,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,,139.0,17.0,11.0,42.0,43.0,1087.0,"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'],164.0,159.0,https://pypi.org/project/performer-pytorch,2022-02-02 20:34:04.000,5.0,7559.0,7559.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +783,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,,143.0,14.0,24.0,64.0,69.0,857.0,PyTorch to Keras model convertor.,13.0,19,False,2020-05-14 10:03:56.000,0.2.4,23.0,pytorch2keras,,,,,103.0,102.0,https://pypi.org/project/pytorch2keras,2020-05-14 10:03:56.000,1.0,881.0,881.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +784,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,,230.0,30.0,38.0,43.0,21.0,853.0,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,,,,,,,https://pypi.org/project/dragonfly-opt,2022-10-01 22:28:00.848,,3054.0,3054.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +785,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'],15.0,15.0,https://pypi.org/project/tffm,2022-01-17 20:35:57.000,,393.0,393.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +786,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,,101.0,26.0,49.0,15.0,54.0,734.0,A Python library for detecting patterns and anomalies in massive datasets using the Matrix Profile.,15.0,19,False,2019-08-08 01:24:38.000,0.0.9,9.0,matrixprofile-ts,,,,,30.0,28.0,https://pypi.org/project/matrixprofile-ts,2019-08-08 01:24:38.000,2.0,1022.0,1022.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +787,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..",10.0,19,False,2020-06-12 20:05:15.000,0.3.9,26.0,nboost,,,,,5.0,5.0,https://pypi.org/project/nboost,2020-06-12 20:05:15.000,,1144.0,1144.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +788,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,,145.0,34.0,84.0,16.0,55.0,630.0,Code for the TCAV ML interpretability project.,19.0,19,False,2021-02-23 16:17:42.000,0.2.2,4.0,tcav,,,,['tensorflow'],29.0,26.0,https://pypi.org/project/tcav,2021-02-23 16:17:42.000,3.0,425.0,425.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +789,baikal,alegonz/baikal,others,,https://github.com/alegonz/baikal,https://github.com/alegonz/baikal,BSD-3-Clause,2019-01-21 12:59:02.000,2024-10-23 06:29:06.515000,2021-04-11 07:50:00,405.0,,29.0,18.0,42.0,6.0,18.0,593.0,A graph-based functional API for building complex scikit-learn pipelines.,2.0,19,False,2020-11-15 13:40:18.000,0.4.2,16.0,baikal,conda-forge/cython-blis,,,,15.0,14.0,https://pypi.org/project/baikal,2020-11-15 13:40:18.000,1.0,1156.0,48218.0,https://anaconda.org/conda-forge/cython-blis,2024-10-23 06:29:06.515,2306073.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +790,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,,97.0,15.0,53.0,13.0,16.0,565.0,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,,,,,58.0,58.0,https://pypi.org/project/recmetrics,2022-04-26 17:57:01.000,,4741.0,4741.0,,,,,,,,3.0,8.0,,,,,,,,,,,,,,,,,,, +791,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,,71.0,13.0,10.0,24.0,41.0,564.0,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,,,,,54.0,54.0,https://pypi.org/project/fastt5,2022-04-05 03:23:12.000,,1326.0,1326.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +792,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,,54.0,18.0,10.0,4.0,18.0,525.0,Topological Data Analysis for Python.,6.0,19,True,2024-07-19 18:49:00.000,1.1.1,6.0,scikit-tda,,,,['sklearn'],62.0,62.0,https://pypi.org/project/scikit-tda,2024-07-19 18:49:00.000,,1383.0,1383.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +793,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,,92.0,22.0,19.0,6.0,20.0,484.0,Case Recommender: A Flexible and Extensible Python Framework for Recommender Systems.,11.0,19,False,2021-11-25 23:19:05.000,1.1.1,42.0,caserecommender,,,,['sklearn'],14.0,14.0,https://pypi.org/project/caserecommender,2021-11-25 23:19:05.000,,3164.0,3164.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +794,sklearn-evaluation,edublancas/sklearn-evaluation,interpretability,,https://github.com/edublancas/sklearn-evaluation,https://github.com/edublancas/sklearn-evaluation,MIT,2023-01-15 21:18:52.000,2024-09-18 17:05:04.000000,2023-01-13 21:57:34,832.0,,54.0,,,,,455.0,"Machine learning model evaluation made easy: plots, tables, HTML reports, experiment tracking and Jupyter notebook..",19.0,19,False,2024-09-18 17:05:04.000,0.12.2,50.0,sklearn-evaluation,,,,['sklearn'],3.0,,https://pypi.org/project/sklearn-evaluation,2024-09-18 17:05:04.000,3.0,5703.0,5703.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +795,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,,72.0,25.0,48.0,18.0,19.0,408.0,"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'],28.0,,https://pypi.org/project/skrebate,2021-03-20 17:11:52.000,28.0,5053.0,5482.0,https://anaconda.org/conda-forge/skrebate,2023-06-16 16:08:23.527,34824.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +796,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,,30.0,11.0,121.0,31.0,150.0,344.0,Open source production model management tool for data scientists.,6.0,19,False,2018-12-07 06:16:42.000,0.0.40,41.0,datmo,,,,,7.0,7.0,https://pypi.org/project/datmo,2018-12-07 06:16:42.000,,2157.0,2157.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +797,fairness-indicators,tensorflow/fairness-indicators,interpretability,,https://github.com/tensorflow/fairness-indicators,https://github.com/tensorflow/fairness-indicators,Apache-2.0,2019-09-30 22:56:45.000,2024-10-23 17:55:40.000000,2024-04-26 20:31:49,327.0,,78.0,25.0,346.0,26.0,10.0,341.0,Tensorflows Fairness Evaluation and Visualization Toolkit.,36.0,19,True,2024-04-26 21:27:16.000,0.46.0,31.0,fairness-indicators,,,,"['tensorflow', 'jupyter']",,,https://pypi.org/project/fairness-indicators,2024-04-26 21:27:16.000,,3357.0,3357.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +798,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.,8.0,19,False,2023-03-07 22:10:10.175,0.8.9,49.0,camphr,,,,['spacy'],17.0,15.0,https://pypi.org/project/camphr,2023-03-07 22:10:10.175,2.0,6084.0,6084.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +799,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,,53.0,11.0,60.0,17.0,41.0,333.0,"Hyperparameter optimization that enables researchers to experiment, visualize, and scale quickly.",43.0,19,False,2020-07-31 05:29:09.000,1.0.7,8.0,parameter-sherpa,,,,,43.0,39.0,https://pypi.org/project/parameter-sherpa,2019-11-23 21:32:27.000,4.0,498.0,498.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +800,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,,41.0,19.0,4.0,10.0,8.0,285.0,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'],11.0,11.0,https://pypi.org/project/deepgraph,2024-03-27 10:16:33.000,,3216.0,7936.0,https://anaconda.org/conda-forge/deepgraph,2024-07-11 16:39:33.824,226590.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +801,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 08:10:33,265.0,1.0,33.0,11.0,202.0,21.0,76.0,200.0,"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'],42.0,41.0,https://pypi.org/project/celer,2023-07-26 15:36:39.000,1.0,3254.0,3254.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +802,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,,891.0,112.0,51.0,46.0,160.0,6285.0,Model parallel transformers in JAX and Haiku.,23.0,18,False,,,,,,,,['jax'],20.0,20.0,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +803,scenic,google-research/scenic,image,,https://github.com/google-research/scenic,https://github.com/google-research/scenic,Apache-2.0,2021-07-12 14:27:08.000,2024-10-19 22:04:44.000000,2024-10-19 22:04:38,711.0,13.0,430.0,40.0,863.0,149.0,119.0,3307.0,Scenic: A Jax Library for Computer Vision Research and Beyond.,88.0,18,True,,,,,,,,['jax'],,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +804,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,,415.0,106.0,83.0,67.0,48.0,2986.0,Deep recommender models using PyTorch.,11.0,18,False,2019-09-08 10:19:53.000,0.1.6,7.0,,maciejkula/spotlight,,,['pytorch'],,,,,,,99.0,https://anaconda.org/maciejkula/spotlight,2023-06-16 13:22:46.522,8796.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +805,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,,458.0,80.0,36.0,83.0,68.0,1695.0,Named-entity recognition using neural networks. Easy-to-use and state-of-the-art results.,7.0,18,False,2019-10-02 23:30:15.000,1.0.8,7.0,pyneuroner,,,,,,,https://pypi.org/project/pyneuroner,2019-10-02 23:30:15.000,,469.0,469.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +806,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,,109.0,55.0,34.0,22.0,13.0,1267.0,"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,,,,,4.0,3.0,https://pypi.org/project/xcessiv,2017-08-21 00:49:41.000,1.0,876.0,876.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +807,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,,144.0,17.0,11.0,25.0,18.0,1159.0,Tez is a super-simple and lightweight Trainer for PyTorch. It also comes with many utils that you can use to tackle..,2.0,18,False,2022-09-20 02:28:33.973,0.7.2,26.0,tez,,,,['pytorch'],59.0,57.0,https://pypi.org/project/tez,2022-09-20 02:28:33.973,2.0,1630.0,1630.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +808,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,,93.0,33.0,72.0,31.0,30.0,1107.0,"Fast, general, and tested differentiable structured prediction in PyTorch.",16.0,18,False,2021-02-15 20:20:59.000,0.5,2.0,torch-struct,,,,['pytorch'],2.0,,https://pypi.org/project/torch-struct,2021-02-14 02:43:46.000,2.0,6701.0,6701.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +809,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,,110.0,19.0,37.0,20.0,8.0,1043.0,Distributed Computing for AI Made Simple.,5.0,18,False,2020-07-09 03:28:28.000,0.2.1,6.0,fiber,,,,,82.0,81.0,https://pypi.org/project/fiber,2020-07-09 03:28:28.000,1.0,1732.0,1732.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +810,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,,84.0,14.0,35.0,3.0,24.0,818.0,Leave One Feature Out Importance.,6.0,18,True,2024-01-16 09:19:50.000,0.3.4,14.0,lofo-importance,,,,,38.0,34.0,https://pypi.org/project/lofo-importance,2024-01-16 09:19:50.000,4.0,3788.0,3788.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +811,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,,36.0,12.0,13.0,8.0,16.0,777.0,"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'],46.0,46.0,https://pypi.org/project/tensor-sensor,2021-12-11 21:24:35.000,,3559.0,3659.0,https://anaconda.org/conda-forge/tensor-sensor,2023-06-16 19:27:38.210,3607.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +812,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,,102.0,20.0,58.0,2.0,13.0,773.0,"A lightweight Computer Vision library. Scale your models, not boilerplate.",8.0,18,False,2021-10-13 21:04:12.000,2.0.8,119.0,caer,,,https://caer.rtfd.io,,2.0,,https://pypi.org/project/caer,2021-10-13 21:04:12.000,2.0,17587.0,17587.0,,,,,,,,3.0,41.0,,,,,,,,,,,,,,,,,,, +813,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,,103.0,24.0,101.0,37.0,84.0,706.0,Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries.,4.0,18,False,2021-02-16 11:34:12.211,3.0.0,16.0,hyperparameter-hunter,,,,,,,https://pypi.org/project/hyperparameter-hunter,2018-06-14 02:21:57.000,,1242.0,1249.0,,,,,,,,3.0,519.0,,,,,,,,,,,,,,,,,,, +814,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,,87.0,26.0,4.0,39.0,42.0,693.0,ThunderGBM: Fast GBDTs and Random Forests on GPUs.,12.0,18,True,2022-09-19 20:15:07.376,0.3.17,25.0,thundergbm,,,,,4.0,4.0,https://pypi.org/project/thundergbm,2022-09-19 20:15:07.376,,1072.0,1072.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +815,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,,69.0,7.0,6.0,4.0,32.0,564.0,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,,,,,22.0,20.0,https://pypi.org/project/shap-hypetune,2024-02-21 14:34:22.000,2.0,2434.0,2434.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +816,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,,105.0,13.0,130.0,18.0,138.0,480.0,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'],3.0,,https://pypi.org/project/deslib,2024-04-12 03:07:31.000,3.0,1886.0,1886.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +817,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,,106.0,71.0,7.0,15.0,19.0,429.0,semantic similarity framework for knowledge graph.,10.0,18,True,2017-04-17 10:56:52.000,1.0.4,5.0,sematch,,,,,48.0,48.0,https://pypi.org/project/sematch,2017-04-17 10:56:52.000,,511.0,511.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +818,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,,83.0,20.0,248.0,10.0,23.0,422.0,A toolkit that streamlines and automates the generation of model cards.,22.0,18,False,2023-04-03 18:05:05.715,2.0.0,12.0,model-card-toolkit,,,,,1.0,,https://pypi.org/project/model-card-toolkit,2022-04-28 16:34:21.000,1.0,2443.0,2443.0,,,,,,,,3.0,26.0,,,,,,,,,,,,,,,,,,, +819,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,,38.0,12.0,1.0,2.0,80.0,402.0,Deep Learning PyTorch.,1.0,18,True,2024-01-09 05:17:07.000,0.5.0,103.0,carefree-learn,,,,['pytorch'],8.0,8.0,https://pypi.org/project/carefree-learn,2024-01-09 05:17:07.000,,5804.0,5804.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +820,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,,60.0,8.0,12.0,11.0,18.0,398.0,TextAugment: Text Augmentation Library.,8.0,18,True,2023-11-16 20:54:10.000,2.0.0,9.0,textaugment,,,,,134.0,130.0,https://pypi.org/project/textaugment,2023-11-16 20:49:04.000,4.0,5336.0,5337.0,,,,,,,,3.0,112.0,,,,,,,,,,,,,,,,,,, +821,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'],5.0,5.0,https://pypi.org/project/bluefog,2021-05-15 01:39:45.000,,680.0,683.0,,,,,,,,3.0,203.0,,,,,,,,,,,,,,,,,,, +822,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,,19.0,6.0,33.0,20.0,39.0,263.0,Streaming over lightweight data transformations.,6.0,18,False,2020-03-10 14:09:31.000,0.1.9,18.0,solt,,,,,62.0,59.0,https://pypi.org/project/solt,2020-03-10 14:09:31.000,3.0,728.0,728.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +823,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,,43.0,11.0,61.0,31.0,47.0,241.0,Scikit-learn compatible estimation of general graphical models.,7.0,18,False,2018-09-12 01:12:49.000,0.2.8,6.0,skggm,,,,['sklearn'],22.0,18.0,https://pypi.org/project/skggm,2018-09-12 01:12:49.000,4.0,313.0,313.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +824,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,,33.0,14.0,36.0,9.0,44.0,232.0,A library for augmenting annotated audio data.,7.0,18,False,2019-11-15 15:46:21.000,0.4.1,12.0,muda,,,,,32.0,30.0,https://pypi.org/project/muda,2019-11-15 15:46:21.000,2.0,361.0,361.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +825,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,,57.0,5.0,2.0,3.0,1.0,133.0,Python 3 Bindings for the NVIDIA Management Library.,2.0,18,False,2017-06-03 07:43:46.000,7.352.0,1.0,nvidia-ml-py3,anaconda/nvidia-ml,,,,9903.0,9774.0,https://pypi.org/project/nvidia-ml-py3,2017-06-03 07:43:46.000,129.0,328818.0,328850.0,https://anaconda.org/anaconda/nvidia-ml,2023-06-16 19:26:58.970,1263.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +826,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,,1350.0,466.0,21.0,59.0,167.0,7115.0,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,,,,,,,,,,,,,,,, +827,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,,170.0,61.0,10.0,26.0,6.0,1849.0,"Provide an input CSV and a target field to predict, generate a model + code to run it.",7.0,17,False,2019-04-05 06:51:04.000,0.2.1,2.0,automl_gs,,,,,,,https://pypi.org/project/automl_gs,2019-04-05 06:47:54.000,,280.0,280.0,,,,,,,,3.0,50.0,,,,,,,,,,,,,,,,,,, +828,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,,57.0,15.0,10.0,26.0,17.0,779.0,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,,,,,59.0,59.0,https://pypi.org/project/parallelformers,2022-07-27 19:52:00.185,,691.0,691.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +829,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,,94.0,18.0,19.0,4.0,29.0,640.0,Unified Multilingual Robustness Evaluation Toolkit for Natural Language Processing.,18.0,17,False,2022-03-15 07:18:47.000,0.1.0,6.0,textflint,,,,,18.0,18.0,https://pypi.org/project/textflint,2022-03-15 07:18:47.000,,496.0,496.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +830,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,,98.0,38.0,106.0,12.0,51.0,550.0,TypeDB-ML is the Machine Learning integrations library for TypeDB.,13.0,17,True,2022-07-29 11:37:34.000,0.3.0,8.0,grakn-kglib,,,,,,,https://pypi.org/project/grakn-kglib,2020-08-19 15:39:10.000,,555.0,558.0,,,,,,,,3.0,241.0,,,typedb/typedb-ml,,,,,,,,,,,,,,,, +831,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.",10.0,17,True,2023-06-16 17:26:21.434,0.4.2,11.0,caliban,,,,,4.0,4.0,https://pypi.org/project/caliban,2020-09-12 19:41:23.000,,1489.0,1489.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +832,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,,84.0,36.0,47.0,5.0,12.0,412.0,OpenRec is an open-source and modular library for neural network-inspired recommendation algorithms.,11.0,17,False,2020-02-18 06:52:11.000,0.3.0,12.0,openrec,,,,,5.0,4.0,https://pypi.org/project/openrec,2020-02-18 06:52:11.000,1.0,393.0,393.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +833,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.,4.0,17,False,2021-10-22 03:19:11.000,0.6.5,8.0,pywick,,,,['pytorch'],12.0,12.0,https://pypi.org/project/pywick,2021-10-22 03:19:11.000,,215.0,215.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +834,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.,4.0,17,True,2017-03-30 10:51:26.000,0.4.2,22.0,tfdeploy,,,,['tensorflow'],,,https://pypi.org/project/tfdeploy,2017-03-30 10:51:26.000,,743.0,743.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +835,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.,9.0,17,False,,,1.0,pdvega,,,,,89.0,89.0,https://pypi.org/project/pdvega,2018-02-01 04:56:43.000,,194.0,194.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +836,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.,9.0,17,False,2022-02-14 13:45:54.000,0.0.23,18.0,skift,,,,['sklearn'],17.0,17.0,https://pypi.org/project/skift,2018-03-15 09:05:47.000,,6691.0,6691.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +837,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,,35.0,225.0,"A multi-functional library for full-stack Deep Learning. Simplifies Model Building, API development, and Model..",14.0,17,False,2021-11-26 17:10:22.000,0.2.0,38.0,chitra,conda-forge/chitra,,,,1.0,,https://pypi.org/project/chitra,2022-01-09 08:50:45.005,1.0,5003.0,5114.0,https://anaconda.org/conda-forge/chitra,2023-06-18 08:40:33.534,3689.0,,,,,3.0,,,,aniketmaurya/chitra,,,,,,,,,,,,,,,, +838,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,,45.0,1.0,,,,216.0,Pytorch framework for doing deep learning on point clouds.,29.0,17,False,2021-04-30 09:00:22.000,1.3.0,14.0,torch-points3d,,,,['pytorch'],,,https://pypi.org/project/torch-points3d,2021-04-30 09:00:22.000,,1569.0,1569.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +839,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,,5.0,205.0,"Automatic GPU+CPU memory profiling, re-use and memory leaks detection using jupyter/ipython experiment containers.",3.0,17,False,2023-12-15 03:21:06.000,0.1.29,25.0,ipyexperiments,,,,['jupyter'],12.0,10.0,https://pypi.org/project/ipyexperiments,2023-12-15 03:21:06.000,2.0,1777.0,1777.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +840,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,,17.0,8.0,184.0,11.0,23.0,155.0,Toolkit for developing and maintaining ML models.,14.0,17,False,2024-02-02 14:57:28.000,0.1.2,35.0,modelkit,,,,,,,https://pypi.org/project/modelkit,2024-02-02 14:55:53.000,,10821.0,10821.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +841,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.",7.0,17,False,2018-11-23 09:49:59.000,0.1.16,16.0,steppy,,,,,64.0,59.0,https://pypi.org/project/steppy,2018-11-23 09:49:59.000,5.0,564.0,564.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +842,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.",15.0,17,False,2023-03-31 16:09:03.477,1.3.1,10.0,collie,,,,['pytorch'],50.0,50.0,https://pypi.org/project/collie,2022-01-18 23:07:16.000,,1001.0,1001.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +843,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,,1055.0,120.0,24.0,17.0,353.0,4332.0,An Open-Source Package for Neural Relation Extraction (NRE).,13.0,16,True,,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +844,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,,531.0,176.0,110.0,56.0,149.0,3941.0,"Learning embeddings for classification, retrieval and ranking.",17.0,16,False,,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +845,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,,560.0,138.0,28.0,217.0,102.0,2897.0,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'],2.0,2.0,https://pypi.org/project/euler-gl,2019-04-10 01:53:45.000,,111.0,111.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +846,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,,119.0,30.0,111.0,14.0,25.0,1087.0,An autoML framework & toolkit for machine learning on graphs.,16.0,16,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,,,,,,,,,,,,,,,,,,,, +847,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,,117.0,20.0,295.0,3.0,70.0,1075.0,TextBox 2.0 is a text generation library with pre-trained language models.,18.0,16,False,2022-12-28 02:06:22.000,2.0.0,10.0,textbox,,,,,7.0,7.0,https://pypi.org/project/textbox,2021-04-15 09:35:06.000,,4.0,4.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +848,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,,121.0,49.0,22.0,15.0,9.0,846.0,A medical imaging framework for Pytorch.,8.0,16,False,2018-11-24 00:33:11.000,0.2,2.0,medicaltorch,,,,['pytorch'],18.0,18.0,https://pypi.org/project/medicaltorch,2018-11-24 00:29:36.000,,272.0,272.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +849,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,,203.0,42.0,667.0,28.0,27.0,824.0,Translate - a PyTorch Language Library.,88.0,16,False,,,1.0,pytorch-translate,,,,['pytorch'],,,https://pypi.org/project/pytorch-translate,2018-05-01 19:59:40.000,,50.0,50.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +850,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,,10.0,801.0,MADGRAD Optimization Method.,2.0,16,False,,,4.0,madgrad,,,,['pytorch'],90.0,89.0,https://pypi.org/project/madgrad,2022-03-08 18:23:32.000,1.0,3747.0,3747.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +851,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,,112.0,28.0,10.0,25.0,51.0,797.0,Code for High-Precision Model-Agnostic Explanations paper.,10.0,16,False,,,10.0,anchor_exp,,,,,2.0,,https://pypi.org/project/anchor_exp,2020-09-10 22:52:00.000,2.0,2822.0,2822.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +852,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,,85.0,16.0,15.0,10.0,22.0,732.0,Visualization toolkit for neural networks in PyTorch! Demo --.,2.0,16,False,2020-05-29 14:39:38.000,0.1.3,12.0,flashtorch,,,,['pytorch'],23.0,23.0,https://pypi.org/project/flashtorch,2020-05-29 14:38:32.000,,832.0,832.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +853,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']",1.0,,https://pypi.org/project/tensorframes,2018-05-16 14:20:28.000,1.0,9675.0,9675.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +854,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,,128.0,42.0,435.0,25.0,130.0,712.0,GPU accelerated signal processing.,46.0,16,False,2023-08-09 16:45:21.000,23.08.00,21.0,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +855,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,,38.0,24.0,4.0,4.0,2.0,683.0,Library for faster pinned CPU - GPU transfer in Pytorch.,3.0,16,False,2020-01-06 05:27:17.000,0.1.6,14.0,SpeedTorch,,,,['pytorch'],9.0,7.0,https://pypi.org/project/SpeedTorch,2020-01-06 05:27:17.000,2.0,691.0,691.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +856,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,,57.0,16.0,83.0,18.0,49.0,605.0,A Pytorch Knowledge Distillation library for benchmarking and extending works in the domains of Knowledge..,6.0,16,False,2022-05-18 08:35:04.000,0.0.32,8.0,KD-Lib,,,,['pytorch'],,,https://pypi.org/project/KD-Lib,2022-05-18 08:35:04.000,,475.0,475.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +857,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,,88.0,21.0,18.0,22.0,2.0,513.0,AtsPy: Automated Time Series Models in Python (by @firmai).,5.0,16,False,2020-11-12 16:10:48.000,zen,39.0,atspy,,,,,13.0,13.0,https://pypi.org/project/atspy,2020-04-24 18:16:15.000,,3630.0,3630.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +858,NeuralCompression,facebookresearch/NeuralCompression,others,,https://github.com/facebookresearch/NeuralCompression,https://github.com/facebookresearch/NeuralCompression,MIT,2021-07-09 15:14:13.000,2024-09-20 14:21:23.000000,2024-09-20 14:21:18,142.0,2.0,43.0,21.0,171.0,6.0,65.0,502.0,A collection of tools for neural compression enthusiasts.,10.0,16,True,2023-10-03 14:26:28.000,0.3.1,6.0,neuralcompression,,,,,,,https://pypi.org/project/neuralcompression,2023-10-03 14:26:28.000,,440.0,440.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +859,VizSeq,facebookresearch/vizseq,nlp,,https://github.com/facebookresearch/vizseq,https://github.com/facebookresearch/vizseq,MIT,2019-08-26 13:19:38.000,2024-09-28 19:50:20.000000,2024-09-28 19:49:30,81.0,1.0,61.0,16.0,67.0,7.0,9.0,442.0,"An Analysis Toolkit for Natural Language Generation (Translation, Captioning, Summarization, etc.).",4.0,16,True,2020-08-07 01:13:52.000,0.1.15,16.0,vizseq,,,,,12.0,12.0,https://pypi.org/project/vizseq,2020-08-07 01:13:52.000,,551.0,551.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +860,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 16:55:05,192.0,1.0,52.0,10.0,17.0,10.0,29.0,415.0,Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line..,5.0,16,True,2021-02-07 11:06:21.000,2.407,56.0,explainx,,,,,,,https://pypi.org/project/explainx,2021-02-04 16:44:24.000,,2641.0,2641.0,,,,,,,,3.0,19.0,,,,,,,,,,,,,,,,,,, +861,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,,395.0,Tool to generate adversarial text examples and test machine learning models against them.,5.0,16,False,2018-08-29 15:14:41.000,1.1.1,3.0,Adversary,conda-forge/artificial-adversary,,,,12.0,11.0,https://pypi.org/project/Adversary,2018-08-29 15:14:41.000,1.0,1051.0,1191.0,https://anaconda.org/conda-forge/artificial-adversary,2023-06-16 19:21:01.312,7151.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +862,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.",5.0,16,False,2019-03-05 01:36:12.000,0.6.1,9.0,pandas-ml,,,,"['sklearn', 'pandas']",2.0,,https://pypi.org/project/pandas-ml,2019-03-05 01:35:23.000,2.0,2260.0,2260.0,,,,,,,,3.0,12.0,,,,,,,,,,,,,,,,,,, +863,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 21:24:19,158.0,3.0,11.0,9.0,15.0,2.0,7.0,274.0,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'],2.0,2.0,https://pypi.org/project/nanodl,2024-08-28 20:41:08.000,,483.0,483.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +864,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,,12.0,16.0,14.0,5.0,4.0,243.0,"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,,,,,4.0,4.0,https://pypi.org/project/backprop,2024-07-31 15:16:51.000,,3279.0,3279.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +865,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.,2.0,16,False,2020-01-24 09:06:29.000,1.0.2,30.0,headliner,,,,,8.0,7.0,https://pypi.org/project/headliner,2020-01-24 09:06:29.000,1.0,2821.0,2821.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +866,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,,19.0,5.0,2.0,17.0,23.0,194.0,HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision.,2.0,16,False,2023-01-22 01:21:35.467,0.75.5,78.0,hugsvision,,,,['huggingface'],14.0,14.0,https://pypi.org/project/hugsvision,2023-01-22 01:21:35.467,,5913.0,5913.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +867,CometML,comet-ml/examples,ml-experiments,,,https://www.comet.com,MIT,,2024-10-23 09:28:06.000000,,,,,,,,,,Supercharging Machine Learning.,,16,True,2024-10-23 09:28:06.000,3.47.1,299.0,comet_ml,comet_ml,,,,77.0,,https://pypi.org/project/comet_ml,2024-10-23 09:28:06.000,77.0,617088.0,617088.0,https://anaconda.org/anaconda/comet_ml,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +868,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,,843.0,77.0,35.0,120.0,59.0,3423.0,Representation learning on large graphs using stochastic graph convolutions.,9.0,15,False,,,,,,,,['tensorflow'],,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +869,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,,420.0,142.0,72.0,12.0,53.0,2202.0,"A probabilistic programming library for Bayesian deep learning, generative models, based on Tensorflow.",20.0,15,False,,,,,,,,['tensorflow'],,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +870,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,,232.0,39.0,40.0,73.0,34.0,1168.0,Entity Linker solution.,16.0,15,False,,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +871,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,,68.0,19.0,177.0,87.0,16.0,414.0,A library that incorporates state-of-the-art explainers for text-based machine learning models and visualizes the..,18.0,15,True,2021-12-07 15:12:02.000,0.1.3,5.0,interpret-text,,,,['jupyter'],,,https://pypi.org/project/interpret-text,2021-12-07 01:57:31.000,,461.0,461.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +872,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'],5.0,5.0,https://pypi.org/project/ptgnn,2021-10-21 21:43:04.000,,976.0,976.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +873,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,,15.0,11.0,6.0,9.0,6.0,312.0,Drift Detection for your PyTorch Models.,4.0,15,False,2021-03-08 12:21:48.000,0.1.0,3.0,torchdrift,,,,['pytorch'],28.0,28.0,https://pypi.org/project/torchdrift,2021-03-08 12:51:05.000,,207.0,207.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +874,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,,,,,,,https://pypi.org/project/data-describe,2020-12-03 23:07:43.000,,845.0,845.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +875,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,,29.0,8.0,6.0,8.0,8.0,252.0,"Summarization, translation, sentiment-analysis, text-generation and more at blazing speed using a T5 version..",4.0,15,False,2021-01-28 09:26:15.000,0.1.8,11.0,onnxt5,,,,,4.0,4.0,https://pypi.org/project/onnxt5,2021-01-28 09:26:15.000,,331.0,331.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +876,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,,32.0,8.0,72.0,31.0,8.0,231.0,NeuralQA: A Usable Library for Question Answering on Large Datasets with BERT.,3.0,15,False,,,27.0,neuralqa,,,,,6.0,6.0,https://pypi.org/project/neuralqa,2020-09-18 17:54:50.000,,837.0,837.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +877,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'],9.0,,https://pypi.org/project/nx-altair,2020-06-02 21:11:12.000,9.0,922.0,922.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +878,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'],29.0,29.0,https://pypi.org/project/parfit,2018-10-11 22:03:16.000,,1056.0,1056.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +879,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,,35.0,14.0,18.0,27.0,18.0,123.0,A deep learning python package for neuroimaging data. Made by:.,6.0,15,False,2019-06-10 21:04:04.000,0.2.3,6.0,deepneuro,,,,,3.0,3.0,https://pypi.org/project/deepneuro,2019-06-10 21:04:04.000,,352.0,352.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +880,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,,994.0,64.0,13.0,44.0,25.0,3703.0,Implementation and experiments of graph embedding algorithms.,9.0,14,False,,,,,,,,['sklearn'],,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +881,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,,,,,,,,,,,,,,,,,,,, +882,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,,294.0,53.0,23.0,42.0,85.0,1304.0,"The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN,..",3.0,14,False,,,,,,,,['pytorch'],,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +883,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,,151.0,32.0,,53.0,60.0,1223.0,GraphVite: A General and High-performance Graph Embedding System.,1.0,14,True,,,4.0,,milagraph/graphvite,,,,,,,,,,78.0,https://anaconda.org/milagraph/graphvite,2023-06-16 16:16:18.265,4896.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +884,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,,,,1.0,,https://pypi.org/project/skater,2018-09-21 07:03:32.000,1.0,872.0,2435.0,https://anaconda.org/conda-forge/skater,2023-09-18 15:13:22.392,79728.0,,,,,3.0,,,,,,,,,,,,,,,,,,,, +885,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 20:48:27,72.0,4.0,47.0,11.0,11.0,1.0,16.0,761.0,"[NeurIPS21 Outstanding Paper] Library for reliable evaluation on RL and ML benchmarks, even with only a handful of..",9.0,14,True,,,,rliable`,,,,,156.0,156.0,https://pypi.org/project/rliable`,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +886,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,,,,,2.0,,https://pypi.org/project/tsaug,2020-04-17 02:50:25.000,2.0,1792.0,1792.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +887,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,,16.0,11.0,58.0,4.0,20.0,291.0,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'],,,https://pypi.org/project/transfer-nlp,2020-05-28 19:00:02.000,,381.0,381.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +888,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.,11.0,14,False,2021-03-03 02:00:23.000,2.0,7.0,auptimizer,,,,,,,https://pypi.org/project/auptimizer,2021-03-02 02:40:32.000,,2579.0,2579.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +889,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.,11.0,14,False,2019-09-12 07:41:04.000,2.0,4.0,textvec,,,,['sklearn'],6.0,6.0,https://pypi.org/project/textvec,2020-12-03 14:17:09.000,,168.0,168.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +890,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.,3.0,14,False,2019-04-09 10:43:15.000,0.4.0,37.0,modelchimp,,modelchimp/modelchimp-server,,,,,https://pypi.org/project/modelchimp,2019-04-09 10:41:20.000,,1381.0,1390.0,,,,https://hub.docker.com/r/modelchimp/modelchimp-server,2019-04-09 10:15:09.532793,,667.0,3.0,,,,,,,,,,,,,,,,,,,, +891,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,,8.0,7.0,4.0,14.0,18.0,83.0,"An intelligent, flexible grammar of machine learning.",3.0,14,False,2021-06-25 14:27:32.000,0.0.7,8.0,nylon-ai,,,,,3.0,3.0,https://pypi.org/project/nylon-ai,2021-06-25 14:27:32.000,,342.0,342.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +892,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,,,,,42.0,42.0,https://pypi.org/project/lazycluster,2020-12-14 14:49:33.000,,310.0,310.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +893,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.,4.0,14,False,2024-02-04 11:31:27.000,0.0.13,12.0,bias-detector,,,,,3.0,3.0,https://pypi.org/project/bias-detector,2024-02-04 11:31:27.000,,2065.0,2065.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +894,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,,984.0,103.0,28.0,28.0,357.0,3823.0,An Open-Source Package for Knowledge Embedding (KE).,14.0,13,False,,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +895,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,,486.0,108.0,12.0,39.0,8.0,2701.0,PyTorch implementation of Efficient Neural Architecture Search via Parameters Sharing.,6.0,13,False,,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +896,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,,85.0,48.0,4.0,3.0,,2546.0,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'],1.0,,https://pypi.org/project/ane-transformers,2022-08-09 04:22:00.465,1.0,2109.0,2111.0,,,,,,,,3.0,76.0,,,,,,,,,,,,,,,,,,, +897,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,,175.0,37.0,10.0,13.0,3.0,1364.0,A web app to generate template code for machine learning.,3.0,13,False,,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +898,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,,53.0,17.0,3.0,2.0,1.0,536.0,DeltaPy - Tabular Data Augmentation (by @firmai).,4.0,13,False,2020-11-12 16:13:21.000,zen,11.0,deltapy,,,,,5.0,5.0,https://pypi.org/project/deltapy,2020-04-09 01:48:32.000,,513.0,513.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +899,Maze,enlite-ai/maze,reinforcement-learning,,https://github.com/enlite-ai/maze,https://github.com/enlite-ai/maze,Custom,2021-02-11 08:26:37.000,2024-09-24 14:15:45.000000,2022-11-21 12:12:41,1044.0,,12.0,6.0,26.0,1.0,2.0,265.0,Maze Applied Reinforcement Learning Framework.,3.0,13,False,2022-11-21 12:23:00.858,0.2.0,21.0,maze-rl,,enliteai/maze,,['pytorch'],,,https://pypi.org/project/maze-rl,2021-12-13 16:04:42.000,,880.0,885.0,,,,https://hub.docker.com/r/enliteai/maze,2021-06-24 21:00:27.801118,,256.0,3.0,11.0,,,,,,,,,,,,,,,,,,, +900,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.,11.0,13,False,,,2.0,autodist,,,,['tensorflow'],3.0,3.0,https://pypi.org/project/autodist,2020-07-16 05:36:19.000,,491.0,491.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +901,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,,2.0,4.0,122.0,Tools for training explainable models using attribution priors.,6.0,13,False,2021-03-16 17:47:18.000,1.0.0,4.0,attributionpriors,,,,"['tensorflow', 'pytorch']",6.0,6.0,https://pypi.org/project/attributionpriors,2019-10-31 18:03:05.000,,1036.0,1036.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +902,jaxdf,ucl-bug/jaxdf,jax-utils,,https://github.com/ucl-bug/jaxdf,https://github.com/ucl-bug/jaxdf,LGPL-3.0,2021-09-08 16:38:46.000,2024-09-17 10:38:04.000000,2024-09-17 10:34:46,319.0,5.0,7.0,7.0,127.0,9.0,9.0,120.0,A JAX-based research framework for writing differentiable numerical simulators with arbitrary discretizations.,4.0,13,False,2024-09-17 10:36:38.000,0.2.8,10.0,,,,,['jax'],6.0,6.0,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +903,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.",8.0,13,False,2019-10-23 15:40:12.000,0.5.1,11.0,hypermax,,,,,6.0,6.0,https://pypi.org/project/hypermax,2019-10-23 15:40:12.000,,461.0,461.0,,,,,,,,3.0,,,,genixpro/hypermax,,,,,,,,,,,,,,,, +904,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,,12.0,13.0,26.0,4.0,13.0,86.0,"Contextual AI adds explainability to different stages of machine learning pipelines - data, training, and inference -..",12.0,13,False,2021-01-25 04:56:57.000,0.0.2,2.0,contextual-ai,,,,,,,https://pypi.org/project/contextual-ai,2021-01-25 04:56:57.000,,212.0,212.0,,,,,,,,3.0,,,,SAP-archive/contextual-ai,,,,,,,,,,,,,,,, +905,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.,3.0,13,False,2021-12-23 15:53:08.000,1.2.0,3.0,nptsne,,,,,8.0,8.0,https://pypi.org/project/nptsne,2021-12-23 15:53:08.000,,776.0,776.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +906,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,,408.0,64.0,6.0,65.0,17.0,1937.0,Many studies have shown that the performance on deep learning is significantly affected by volume of training data...,1.0,12,False,,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +907,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,,323.0,88.0,11.0,12.0,6.0,1767.0,Find big moving stocks before they move using machine learning and anomaly detection.,6.0,12,False,,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +908,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,,11.0,8.0,4.0,6.0,14.0,105.0,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'],,,https://pypi.org/project/spacy-dbpedia-spotlight,2022-10-07 09:58:11.751,,800.0,800.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +909,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,,459.0,93.0,22.0,52.0,15.0,3267.0,AutoML algorithms for model architecture search at scale.,1.0,11,False,,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +910,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,,116.0,44.0,13.0,7.0,20.0,949.0,Genetic neural architecture search with Keras.,18.0,11,False,,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +911,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,,146.0,39.0,7.0,19.0,14.0,916.0,Approximate Nearest Neighbor Search for Sparse Data in Python!.,5.0,11,False,,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +912,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,,21.0,12.0,41.0,7.0,12.0,366.0,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'],5.0,5.0,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +913,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.,2.0,11,False,2020-01-26 23:08:16.000,1.0.1,7.0,hypertunity,,,,,4.0,4.0,https://pypi.org/project/hypertunity,2020-01-26 23:08:16.000,,252.0,252.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +914,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,,89.0,17.0,5.0,4.0,12.0,611.0,An optical music recognition (OMR) system. Converts sheet music to a machine-readable version.,6.0,10,False,,,,,,,,['sklearn'],,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +915,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,,51.0,16.0,13.0,14.0,11.0,526.0,Library for Textless Spoken Language Processing.,8.0,10,False,,,,,,,,['pytorch'],,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +916,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.,,10,False,2020-11-02 02:25:32.000,0.0.3,3.0,traintool,,,,"['pytorch', 'tensorflow', 'sklearn']",2.0,2.0,https://pypi.org/project/traintool,2020-11-02 02:25:32.000,,182.0,182.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +917,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,,25.0,7.0,2.0,2.0,6.0,148.0,Python package to generate stock portfolios.,4.0,9,False,2020-03-13 20:04:08.000,0.2,3.0,pyrtfolio,,,,,2.0,2.0,https://pypi.org/project/pyrtfolio,2020-03-13 20:31:47.000,,45.0,45.0,,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, +918,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,,8.0,8.0,2.0,1.0,,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,,,,1.0,,https://pypi.org/project/tslumen,2022-11-22 17:50:34.944,1.0,83.0,83.0,https://anaconda.org/conda-forge/tslumen,,,,,,,3.0,,,,,,,,,,,,,,,,,,,, diff --git a/latest-changes.md b/latest-changes.md index 3f66a97..65fb75e 100644 --- a/latest-changes.md +++ b/latest-changes.md @@ -2,29 +2,29 @@ _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._ -- VisPy (πŸ₯ˆ36 Β· ⭐ 3.3K Β· πŸ“ˆ) - High-performance interactive 2D/3D data visualization library. BSD-3 -- NIPYPE (πŸ₯ˆ35 Β· ⭐ 750 Β· πŸ“ˆ) - Workflows and interfaces for neuroimaging packages. Apache-2 -- pygraphistry (πŸ₯ˆ32 Β· ⭐ 2.1K Β· πŸ“ˆ) - PyGraphistry is a Python library to quickly load,.. BSD-3 -- mtcnn (πŸ₯ˆ29 Β· ⭐ 2.2K Β· πŸ“ˆ) - MTCNN face detection implementation for TensorFlow, as a PIP.. MIT -- pyRiemann (πŸ₯‰27 Β· ⭐ 630 Β· πŸ“ˆ) - Machine learning for multivariate data through the.. BSD-3 -- NIPY (πŸ₯‰27 Β· ⭐ 380 Β· πŸ“ˆ) - Neuroimaging in Python FMRI analysis package. ❗Unlicensed -- scikit-posthocs (πŸ₯‰26 Β· ⭐ 340 Β· πŸ“ˆ) - Multiple Pairwise Comparisons (Post Hoc) Tests in.. MIT -- PARL (πŸ₯‰25 Β· ⭐ 3.3K Β· πŸ“ˆ) - A high-performance distributed training framework for.. Apache-2 -- Quantus (πŸ₯‰21 Β· ⭐ 540 Β· πŸ“ˆ) - Quantus is an eXplainable AI toolkit for responsible evaluation.. ❗️GPL-3.0 -- DeepNeuro (πŸ₯‰15 Β· ⭐ 120 Β· πŸ’€) - A deep learning python package for neuroimaging data. Made by:. MIT +- Core ML Tools (πŸ₯ˆ36 Β· ⭐ 4.4K Β· πŸ“ˆ) - Core ML tools contain supporting tools for Core ML model.. BSD-3 +- optimum (πŸ₯‡36 Β· ⭐ 2.5K Β· πŸ“ˆ) - Accelerate training and inference of Transformers and Diffusers.. Apache-2 +- cartopy (πŸ₯ˆ36 Β· ⭐ 1.4K Β· πŸ“ˆ) - Cartopy - a cartographic python library with matplotlib support. BSD-3 +- SpeechRecognition (πŸ₯‡35 Β· ⭐ 8.4K Β· πŸ“ˆ) - Speech recognition module for Python, supporting.. BSD-3 +- causalml (πŸ₯ˆ31 Β· ⭐ 5.1K Β· πŸ“ˆ) - Uplift modeling and causal inference with machine learning.. Apache-2 +- LIT (πŸ₯ˆ28 Β· ⭐ 3.5K Β· πŸ“ˆ) - The Learning Interpretability Tool: Interactively analyze ML models.. Apache-2 +- pycm (πŸ₯ˆ28 Β· ⭐ 1.4K Β· πŸ“ˆ) - Multi-class confusion matrix library in Python. MIT +- tinytag (πŸ₯‰28 Β· ⭐ 700 Β· πŸ“ˆ) - Python library for reading audio file metadata. MIT +- Chartify (πŸ₯‰27 Β· ⭐ 3.5K Β· πŸ“ˆ) - Python library that makes it easy for data scientists to create.. Apache-2 +- Pytorch Toolbelt (πŸ₯‰24 Β· ⭐ 1.5K Β· πŸ“ˆ) - PyTorch extensions for fast R&D prototyping and.. MIT ## 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._ -- PaddlePaddle (πŸ₯‡45 Β· ⭐ 22K Β· πŸ“‰) - PArallel Distributed Deep LEarning: Machine Learning.. Apache-2 -- PySpark (πŸ₯ˆ44 Β· ⭐ 39K Β· πŸ“‰) - Apache Spark Python API. Apache-2 -- litellm (πŸ₯‡42 Β· ⭐ 13K Β· πŸ“‰) - Python SDK, Proxy Server (LLM Gateway) to call 100+.. MIT o t h e r s -- sentence-transformers (πŸ₯‡40 Β· ⭐ 15K Β· πŸ“‰) - State-of-the-Art Text Embeddings. Apache-2 -- Shapely (πŸ₯‡40 Β· ⭐ 3.9K Β· πŸ“‰) - Manipulation and analysis of geometric objects. BSD-3 -- PyCaret (πŸ₯ˆ36 Β· ⭐ 8.9K Β· πŸ“‰) - An open-source, low-code machine learning library in Python. MIT -- horovod (πŸ₯ˆ35 Β· ⭐ 14K Β· πŸ“‰) - Distributed training framework for TensorFlow, Keras, PyTorch,.. Apache-2 -- PyOD (πŸ₯‡35 Β· ⭐ 8.5K Β· πŸ“‰) - A Python Library for Outlier and Anomaly Detection, Integrating.. BSD-2 -- imbalanced-learn (πŸ₯‡33 Β· ⭐ 6.8K Β· πŸ“‰) - A Python Package to Tackle the Curse of Imbalanced.. MIT -- cleanlab (πŸ₯ˆ31 Β· ⭐ 9.6K Β· πŸ“‰) - The standard data-centric AI package for data quality and.. ❗️AGPL-3.0 +- PyTorch (πŸ₯‡55 Β· ⭐ 83K Β· πŸ“‰) - Tensors and Dynamic neural networks in Python with strong GPU.. BSD-3 +- PaddleOCR (πŸ₯‡40 Β· ⭐ 44K Β· πŸ“‰) - Awesome multilingual OCR toolkits based on PaddlePaddle.. Apache-2 +- gensim (πŸ₯‡39 Β· ⭐ 16K Β· πŸ“‰) - Topic Modelling for Humans. ❗️LGPL-2.1 +- flair (πŸ₯‡38 Β· ⭐ 14K Β· πŸ“‰) - A very simple framework for state-of-the-art Natural Language.. MIT +- dgl (πŸ₯‡38 Β· ⭐ 13K Β· πŸ“‰) - Python package built to ease deep learning on graph, on top of.. Apache-2 +- EasyOCR (πŸ₯‡35 Β· ⭐ 24K Β· πŸ“‰) - Ready-to-use OCR with 80+ supported languages and all popular.. Apache-2 +- spark-nlp (πŸ₯ˆ35 Β· ⭐ 3.9K Β· πŸ“‰) - State of the Art Natural Language Processing. Apache-2 +- VisPy (πŸ₯ˆ34 Β· ⭐ 3.3K Β· πŸ“‰) - High-performance interactive 2D/3D data visualization library. BSD-3 +- PML (πŸ₯‡32 Β· ⭐ 6K Β· πŸ“‰) - The easiest way to use deep metric learning in your application... MIT +- pomegranate (πŸ₯‰27 Β· ⭐ 3.4K Β· πŸ“‰) - Fast, flexible and easy to use probabilistic modelling in Python. MIT