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Title: GitHub - linxid/Machine_Learning_Study_Path: 机器学习过程中所看的书，视频和源码

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《Mastering Natural Language Processing with Python》https://www.packtpub.com/big-data-and-business-intelligence/mastering-natural-language-processing-python
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《Machine Learning yearning》http://www.mlyearning.org/
《美团机器学习实战》http://item.jd.com/12414240.html?dist=jd
《集体智慧编程》https://www.amazon.cn/dp/B00UI93JD8/ref=sr_1_1?s=books&ie=UTF8&qid=1541669086&sr=1-1&keywords=%E9%9B%86%E4%BD%93%E6%99%BA%E6%85%A7%E7%BC%96%E7%A8%8B
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《神经网络与深度学习》http://neuralnetworksanddeeplearning.com/
《Deep Learning with python A Hands on Introduction》https://www.amazon.cn/dp/1484227654/ref=sr_1_1?ie=UTF8&qid=1541750979&sr=8-1&keywords=Deep+Learning+with+Python%3A+A+Hands-on+Introduction
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Open AIhttps://blog.openai.com/
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BAIR 博客https://bair.berkeley.edu/blog/
DeepMindhttps://deepmind.com/blog/?category=research
http://karpathy.github.io/http://karpathy.github.io/
https://medium.com/@karpathyhttps://medium.com/@karpathy
Colah的博客http://colah.github.io/
WildMLhttp://www.wildml.com/
Ruder的博客http://ruder.io/
FAIR博客https://research.fb.com/blog/
Adit Deshpande的博客https://adeshpande3.github.io/
inFERENCe的博客https://www.inference.vc/
Andrew Trask的博客http://iamtrask.github.io/
Tutorial: Deep Learning in PyTorchhttp://iamtrask.github.io/2017/01/15/pytorch-tutorial/
Anyone Can Learn To Code an LSTM-RNN in Python (Part 1: RNN)http://iamtrask.github.io/2015/11/15/anyone-can-code-lstm/
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