TensorFlow2.0-for-Deep-Reinforcement-Learning

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TensorFlow2.0-for-Deep-Reinforcement-Learning

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TensorFlow 2.0 for Deep Reinforcement Learning. :octopus:

TensorFlow2.0-for-Deep-Reinforcement-Learning 최신버젼 다운로드

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## TensorFlow 2.0 for Deep Reinforcement Learning
<img src="https://github.com/Huixxi/TensorFlow2.0-for-Deep-Reinforcement-Learning/blob/master/images/gym_cartpole_v0.gif" title="CartPole-v0 with Deep Reinforcement Learning" width="500" hegiht="313" align=center />
  
This is a simple tutorial of deep reinforcement learning with tensorflow 2.0, which has simple demos and detailed model implementations to help beginners get start in this research region.

### How to install TensorFlow 2.0
```
$ conda create --name tensorflow_2_0
$ conda activate tensorflow_2_0
$ pip install tensorflow==2.0.0-b1 # pip install tensorflow-gpu==2.0.0-b1 for GPU version
```
Test:
```
>>> import tensorflow as tf
>>> tf.__version__
'2.0.0-beta1'
```

### TensorFlow 2.0 Tutorial
* [Official Tutorial](https://www.tensorflow.org/tutorials/)  
* [Hands-on ML2](https://github.com/ageron/handson-ml2)  
* [Summary of some of the new features in TensorFlow 2.0](https://colab.research.google.com/github/zaidalyafeai/Notebooks/blob/master/TF_2_0.ipynb)  
* [Model building with TensorFlow 2.0](https://colab.research.google.com/drive/17u-pRZJnKN0gO5XZmq8n5A2bKGrfKEUg)

### Python Tutorial
* Welcome to visit my [Fast Py3 Repo](https://github.com/Huixxi/Fast-Py3). This is a fast python3 tutorial.

### Gym Tutorial
* [Basic Gym](https://github.com/Huixxi/TensorFlow2.0-for-Deep-Reinforcement-Learning/blob/master/tutorial_blogs/gym_tutorial.md)

### Reinforcement Learning
Book notes ...

### Deep Reinforcement Learning
* Rainbow
([Building Rainbow Step by Step with TensorFlow2.0](https://github.com/Huixxi/TensorFlow2.0-for-Deep-Reinforcement-Learning/blob/master/tutorial_blogs/Building_Rainbow_Step_by_Step_with_TensorFlow2.0.md))
  * [Deep Q-Network](https://github.com/Huixxi/TensorFlow2.0-for-Deep-Reinforcement-Learning/blob/master/01_dqn.py)
  * +[Double DQN](https://github.com/Huixxi/TensorFlow2.0-for-Deep-Reinforcement-Learning/blob/master/02_ddqn.py)
  * +[Prioritized Experience Replay](https://github.com/Huixxi/TensorFlow2.0-for-Deep-Reinforcement-Learning/blob/master/03_priority_replay.py) 
  * +[Dueling Network](https://github.com/Huixxi/TensorFlow2.0-for-Deep-Reinforcement-Learning/blob/master/04_dueling.py)
  * +[Multi-Step Q-Learning](https://github.com/Huixxi/TensorFlow2.0-for-Deep-Reinforcement-Learning/blob/master/05_multistep_td.py)
  * +[Distributional RL](https://github.com/Huixxi/TensorFlow2.0-for-Deep-Reinforcement-Learning/blob/master/06_distributional_rl.py)(Failed Yet, But I Will Try My BestTo Make It Work Soon!)
  * +[Noisy Network](https://github.com/Huixxi/TensorFlow2.0-for-Deep-Reinforcement-Learning/blob/master/07_noisynet.py)(Failed Yet, But I Will Try My Best To Make It Work Soon!)

### Paper Reading
* Welcome to visit my personal blog website: [HU's Blog](https://huixxi.github.io/). There is a list of **RL Paper Overviews**.

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