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最近在学习机器学习，深度学习，自然语言处理，统计学习方法等知识，理论学习主要根据readme的链接，在学习理论的同时，决定自己将学习的相关算法用Python实现一遍，并结合GitHub上相关大牛的代码进行改进，本项目会不断的更新相关算法，欢迎star，fork和关注。 主要包括： 1.吴恩达Andrew Ng老师的机器学习课程作业个人笔记 Python实现， 2.deeplearning.ai（吴恩达老师的深度学习课程笔记及资源） Python实现， 3.李航《统计学习方法》 Python代码实现， 4.自然语言处理NLP 牛津大学xDeepMind Python代码实现， 5.LeetCode刷题，题析，分析心得笔记 Java和Python代码实现， 6.TensorFlow人工智能实践代码笔记 北京大学曹健老师课程和TensorFlow：实战Google深度学习框架（第二版） Python代码实现， 附带一些个人心得和笔记。GitHub上有很多机器学习课程的代码资源，我也准备自己实现一下，后续会更新笔记，代码和百度云网盘链接。 这个项目主要是学习算法的，并且会不断更新相关资源和代码，欢迎关注，star，fork！ Min's blog 欢迎访问我的博客主页！ (Welcome to my blog website !)https://liweimin1996.github.io/

This repository contains Ipython notebooks and datasets for the data analytics youtube tutorials on The Semicolon.

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🚎 Notebook sharing hub