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《Machine Learning: A Probabilistic Perspective》(Kevin P. Murphy)中文翻译和书中算法的Python实现。

Jupyter Notebook 97.94% Python 2.06%

mlapp_cn_code's Introduction

MLAPP_CN_CODE

《Machine Learning: A Probabilistic Perspective》(Kevin P. Murphy)中文翻译和书中算法的Python实现。

《MLAPP》的中文翻译,以及书中算法模型的Python语言实现。翻译文章中的图形下方标有对应的程序的名字, 可在MLAPP-CODE文件夹下获取代码文件。


由于mlapp 已经更新了2021版本,后面将陆续翻译2021版本的内容,由于作者已经使用Python编写了所有算法并且代码已经开源,所以后期的翻译工作主要包括三个方面:

(1) 传统的文字翻译;

(2) 重要的代码解释;

(3) 相关的论文解读。

新版的mlapp包含了更多内容,其中重点增加了deep learning相关的内容,并且涉及了很多最新的领域研究及相关论文,如 self-supervised learning 等,所引用的文献截止2020年,具有很强的时效性。

2021/6/9-- 继续更新 dep learning 一章,新增了反向传播的相关内容,对包括线性层,softmax层的梯度计算有了进一步的认识。 具体更新可查看博客 https://qiguming.github.io/

2021/5/31-- 为方便大家更好地在线阅读文章,特推出该项目的博客版本,后续内容逐步迁移到新的博客网址:https://qiguming.github.io/ (博客功能将陆续完善,目前已基本实现在线阅读功能)

2021/5/18--更新至13.2.5 节。其中对多种激活函数进行了总结,值得关注的包括 激活函数异方差回归(可以用于异方差分类,从而评估分类的不确定性);

2021/5/17--更新 deep learning. 13.2.4 节,属于初步翻译,相关表述待调整;

2021/5/12--开始更新 mlapp 2021版本的翻译内容,Part III : deep learning;

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