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xyliao

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finish dqn

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`@@ -66,17 +66,15 @@ Learn Deep Learning with PyTorch`
`66`	`66`	`- Chapter 7: 深度强化学习`
`67`	`67`	`- [Q Learning](https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter7_RL/q-learning-intro.ipynb)`
`68`	`68`	`- Open AI gym`
`69`		`- - Deep Q-networks`
	`69`	`+ - [Deep Q-networks](https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter7_RL/dqn.ipynb)`
`70`	`70`
`71`	`71`	`- Chapter 8: PyTorch高级`
`72`	`72`	`- [tensorboard 可视化](https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter8_PyTorch-Advances/tensorboard.ipynb)`
`73`		`-`
`74`	`73`	`- [灵活的数据读取介绍](https://github.com/SherlockLiao/code-of-learn-deep-learning-with-pytorch/blob/master/chapter8_PyTorch-Advances/data-io.ipynb)`
`75`	`74`	`- autograd.function 的介绍`
`76`	`75`	`- 数据并行和多 GPU`
`77`		`- - PyTorch 的分布式应用`
`78`	`76`	`- 使用 ONNX 转化为 Caffe2 模型`
`79`		`- - PyTorch 写 C 扩展`
	`77`	`+ - 打造属于自己的 PyTorch 的使用习惯`
`80`	`78`
`81`	`79`	`### part2: 深度学习的应用`
`82`	`80`	`- Chapter 9: 计算机视觉`

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