AI书籍

机器学习、深度学习和自然语言处理领域，推荐的书籍列表，
是笔者awesome reference系列的一部分。
对于其他的资料、文章、视频教程、工具实践
请参考面向程序员的数据科学与机器学习知识体系及资料合集。
本文，算是抛砖引玉。
笔者最近有空，就会再Pad上面，随手翻阅这些书籍，
希望能够了解其他优秀的书籍。

数学基础

2010-all of statistics:
a concise course in statistical inference [book]：
the goal of this book is to provide a broad backgroud
in probability and statistics
for students in statistics,computer science
especially data mining and machine learning,
mathematics,and related disciplines.

2008-统计学完全教程。
由美国当代著名统计学家L-沃塞曼所著的《统计学完全教程》
是一本几乎包含了统计学领域，全部知识的优秀教材。
本书除了介绍，传统数理统计学的全部内容以外，
还包含了bootstrap方法-自助法
独立性推断
因果推断
图模型
非参数回归
正交函数光滑法
分类
统计学理论
数据挖掘
等统计学领域的新方法和技术。
本书不但注重概率论与数理统计基本理论的阐述，
同时还强调数据分析能力的培养。
本书中含有大量的实例以帮助广大读者快速掌握，使用R软件进行统计数据分析。

机器学习

2007 - Pattern Recognition And Machine Learning [Book]:
the book is suitable for courses on machine learning,
statistics,computer science,signal processing,
computer vision,
data mining,
and bioinformatics.

2012 - machine learning a probabilistic perspective [book]
this textbook offers a comprehensive and self-contained
introduction to the field of machine learning,
a unified,probabilistic approach.
the coverage combines breadth and depth,
offering necessary background material on such topics
as probability,optimization,
and linear algebra as well as discussion of recent developments
in the field,
including conditional random fields,L1 regularization,and deep learning.

2012 - 李航:统计方法学：李航老师的这本书，偏优化和推导，
推导相应算法的时候，可以参考这本书。

2014 - datascience from scratch [book]
in this book,you'll learn how many of the most fundamental data sience tools
and algorithms work by implementing them
from scratch.

2015 - python data sience handbook [book]
jupyter notebooks for the python data science handbook

2015 - data mining,the textbook [book]
this textbook explores the different aspects of
data mining frome the fundamentals
to the complex data types
and their applications,capturing the wide diversity of
problem domains for data mining issues.

2016 - 周志华 机器学习 [book]
周志华老师的这本书，非常适合，作为机器学习入门的书籍，
书中的例子十分形象且简单易懂。

university of illinois at urbana - champaign:text mining and analytics [course]

台大机器学习技法[course]

斯坦福机器学习课程[course]

CS224d:deep learning of natural language processing [course]

unsupervised feature learning and deep learning [course]
来自斯坦福的无监督特征学习与深度学习系列教程