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免费下载 | 20本机器学习和数据科学必读书籍

笑看国际风云 2019-02-10 11:50:22


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免费下载 | 20本机器学习和数据科学必读书籍



整理 | 阿司匹林

出品 | 人工智能头条(公众号ID:AI_Thinker)


炎炎夏日,有什么比学习更能振奋人心!


KDnuggets 网站编辑 Matthew Mayo 特意为广大读者挑选了 20 本机器学习和数据科学相关的书籍。


这份书单除了 Ian Goodfellow 等人的 Deep Learning、吴恩达的 Machine Learning Yearning 等经典著作之外,还有 Python、统计学习、贝叶斯理论等相关书籍。


重点是,这些书籍全都可以免费下载或者在线阅读。


一分钱都不用花,妈妈再也不用担心我的学习了~





1. Think Stats: Probability and Statistics for Programmers


  • 作者:

    Allen B. Downey

  • 地址:

    http://www.greenteapress.com/thinkstats/


2. Probabilistic Programming & Bayesian Methods for Hackers


  • 作者:

    Cam Davidson-Pilon

  • 地址:

    http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/#contents


3. Understanding Machine Learning: From Theory to Algorithms


  • 作者:

    Shai Shalev-Shwartz and Shai Ben-David

  • 地址:

    http://www.cs.huji.ac.il/~shais/UnderstandingMachineLearning/


4. The Elements of Statistical Learning


  • 作者:

    Trevor Hastie, Robert Tibshirani and Jerome Friedman

  • 地址:

    https://web.stanford.edu/~hastie/Papers/ESLII.pdf


5. An Introduction to Statistical Learning with Applications in R


  • 作者:

    Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani

  • 地址:

    http://www-bcf.usc.edu/~gareth/ISL/


6. Foundations of Data Science


  • 作者:

    Avrim Blum, John Hopcroft, and Ravindran Kannan

  • 地址:

    https://www.cs.cornell.edu/jeh/book.pdf


7. A Programmer's Guide to Data Mining: The Ancient Art of the Numerati


  • 作者:

    Ron Zacharski

  • 地址:

    http://guidetodatamining.com/


8. Mining of Massive Datasets


  • 作者:

    Jure Leskovec, Anand Rajaraman and Jeff Ullman

  • 地址:

    http://mmds.org/


9. Deep Learning


  • 作者:

    Ian Goodfellow, Yoshua Bengio and Aaron Courville

  • 地址:

    http://www.deeplearningbook.org/


10. Machine Learning Yearning


  • 作者:

    Andrew Ng

  • 地址:

    http://www.mlyearning.org/



11. Python Data Science Handbook


  • 作者:

    Jake VanderPlas

  • 地址:

    https://github.com/jakevdp/PythonDataScienceHandbook

 

12. Neural Networks and Deep Learning


  • 作者:

    Michael Nielsen

  • 地址:

    http://neuralnetworksanddeeplearning.com/

 

13. Think Bayes


  • 作者:

    Allen B. Downey

  • 地址:

    http://greenteapress.com/wp/think-bayes/

 

14. Machine Learning & Big Data


  • 作者:

    Kareem Alkaseer

  • 地址:

    http://www.kareemalkaseer.com/books/ml

 

15. Statistical Learning with Sparsity: The Lasso and Generalizations


  • 作者:

    Trevor Hastie, Robert Tibshirani, Martin Wainwright

  • 地址:

    https://web.stanford.edu/~hastie/StatLearnSparsity/

 

16. Statistical inference for data science


  • 作者:

    Brian Caffo

  • 地址:

    https://leanpub.com/LittleInferenceBook/read

 

17. Convex Optimization


  • 作者:

    Stephen Boyd and Lieven Vandenberghe

  • 地址:

    http://stanford.edu/~boyd/cvxbook/

 

18. Natural Language Processing with Python 


  • 作者:

    Steven Bird, Ewan Klein, and Edward Loper

  • 地址:

    https://www.nltk.org/book/

 

19. Automate the Boring Stuff with Python


  • 作者:

    Al Sweigart

  • 地址:

    https://automatetheboringstuff.com/

 

20. Social Media Mining: An Introduction


  • 作者:

    Reza Zafarani, Mohammad Ali Abbasi and Huan Liu

  • 地址:

    http://dmml.asu.edu/smm/


参考链接:

https://www.kdnuggets.com/2017/04/10-free-must-read-books-machine-learning-data-science.html

https://www.kdnuggets.com/2018/05/10-more-free-must-read-books-for-machine-learning-and-data-science.html


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