This repository provides data source, Jupyter notebooks for machine learning projects. Each folder corresponds to one project or data sets. General notes about machine learning and TensorFlow are collected in the folder "0_Notes_for_Tensorflow". You can click 
Quick links of the projects are (with constant updates):
2_Classification_Pima_Indians_Diabetes
4_Clasification_DigitRecognizer
6_Renforcement_Learning_Gridword
7_Renforcement_Learning_blackjack
8_Renforcement_Learning_Clif_Env
9_Renforcement_Learning_CartPole
10_Renforcement_Learning_Moutain_Car
14_Classification_fasion_MINST
All codes are written in Python 3 on Jupyter Notebooks, with detailed notes and comments in English. Tensorflow tutorials for Chinease readers are provided.
If you like this repository please follow me on my Steemit or Jianshu.
For Chinese Readers:
本项目旨在通过项目实战的方式向读者介绍如何使用Tensorfow进行机器学习，每一个目录对应着一个项目或者一个训练数据集。一般性的学习笔记放在了"0_Notes_for_Tensorflow".目录。
所有的代码都是在Jupyter Notebook上用Python 3写成，详细的英文笔记和注释也都附在了Jupyter Notebook中。对于代码的解释以及Tensorflow的入门，我写成了中文教程。如果喜欢我的教程，欢迎关注我的 Steemit 或者 简书
也欢迎关注我的微信公众号tensorflow机器学习，共同学习，一起进步。
AI学习笔记——精准识别You Only Look Once(YOLO)
Tensorflow入门——处理overfitting的问题
Tensorflow_2_0_Tutorial_data_loading.ipynb
3-Regression_TF_eager_api.ipynb
Tensorflow入门——Eager模式像原生python一样训练模型.md
Tensorflow 2.0 快速入门 —— 自动求导与线性回归
2-TensorflowClassification.ipynb
Tensorflow入门——Tensorflow处理分类问题
3-KerasClassification-with-Regularization-dropout
1-Classification-keras-census.ipynb
1_DL_One_Layer_NN_for_DigitRecognizer.ipynb
Tensorflow入门——单层神经网络MNIST手写数子识别
2_DL_Multi_Layer_NN_for_DigitRecognizer.ipynb
Tensorflow入门——多层神经网络MNIST手写数子识别
3_DL_Multi_Layer_CNN_for_DigitRecognizer.ipnb
Tensorflow入门——卷积神经网络MNIST手写数子识别
4_DL_Multi_Layer_CNN_for_DigitRecognizer_with_tensorboard.ipynb
5_DL_Multi_Layer_CNN_for_DigitRecognizer_with_various_parameters
6_DL_Multi_Layer_CNN_for_DigitRecognizer_TF_2.0
Tensorflow_2.0_快速入门——引入Keras自定义模型
7_DL_Multi_Layer_CNN_for_DigitRecognizer_TF2_0_with_Tensorboard.ipynb
Tensorflow2.0——可视化工具Tensorboard
2_RNN_Many_to_Many_Keras.ipynb
3_RNN_Many_to_Many_Stateful_Keras.ipynb
Tensorflow 2.0 快速入门 —— RNN 预测牛奶产量
2_MC_Control_with Epsilon_Greedy Policies.ipynb
3_Off_Policy_MC Control_with_Weighted Importance_Sampling.ipynb
1_SARSA_Q-Learning_compare_Clif_Env.ipynb
2_q_learning_python_carpole.ipynb
4_SARSA_lambda_python_carpole.ipynb
强化学习_Q-Learning_SARSA玩Carpole经典游戏
6_double_dqn_kearas_cartpole.ipynb
7_policy_gradient_cartpole_tensorflow.ipynb
深度强化学习_Policy_Gradient_玩转_CartPole 游戏
8_policy_gradient_TF2_cartpole.ipynb
Tensorflow2.0_深度强化学习——Policy_Gradient
1_q_learning_python_mountain_car.ipynb
强化学习_Q-Learning玩MountainCar爬坡上山
2_SARSA_python_mountain_car.ipynb
3_SARSA_lambda_python_mountain_car.ipynb
强化学习_SARSA和SARSA lambda玩 MountainCa 爬坡上山
4_q_learning_python_mountain_car_continuos.
5_DQN_keras_mountain_car.ipynb
1_flowers_with_transfer_learning.ipynb
Tensorflow_2_0__ResNet实战CIFAR100数据集
1_RNN_LSTM_GRU_for_Reuters_TF2_0.ipynb
2_RNN_LSTM_GRU_cell_for_Reuters_TF2_0.ipynb