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 - [Interpretable Machine Learning](https://christophm.github.io/interpretable-ml-book/): 一份指南，教你如何构建具有可解释性的黑盒模型
 - [Neural Networks and Deep Learning](http://neuralnetworksanddeeplearning.com/index.html): 深度学习开源书籍
 - [Neural Networks and Deep Learning](https://github.com/zhanggyb/nndl): 深度学习开源书籍 - 中文
+- [pydata-book](https://github.com/wesm/pydata-book):利用Python进行数据分析，[中文版一](https://github.com/iamseancheney/python_for_data_analysis_2nd_chinese_version)，[中文版二](https://github.com/BrambleXu/pydata-notebook)
 - [PythonDataScienceHandbook](https://github.com/jakevdp/PythonDataScienceHandbook)：Python数据科学手册
 - [机器学习实战](https://github.com/apachecn/MachineLearning): Machine Learning in Action（机器学习实战）
 - [简单粗暴TensorFlow](https://github.com/snowkylin/TensorFlow-cn): 本手册是一篇精简的TensorFlow入门指导