The following is a list of free, open source books on machine learning, statistics, data-mining, etc.

## Machine-Learning / Data Mining

* [An Introduction To Statistical Learning](http://www-bcf.usc.edu/~gareth/ISL/) - Book + R Code
* [Elements of Statistical Learning](http://statweb.stanford.edu/~tibs/ElemStatLearn/) - Book
* [Probabilistic Programming & Bayesian Methods for Hackers](http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/) - Book + IPython Notebooks
* [Thinking Bayes](http://www.greenteapress.com/thinkbayes/) - Book + Python Code
* [Information Theory, Inference, and Learning Algorithms](http://www.inference.phy.cam.ac.uk/mackay/itila/book.html)
* [Gaussian Processes for Machine Learning](http://www.gaussianprocess.org/gpml/chapters/)
* [Data Intensive Text Processing w/ MapReduce](http://lintool.github.io/MapReduceAlgorithms/)
* [Reinforcement Learning: - An Introduction](http://webdocs.cs.ualberta.ca/~sutton/book/ebook/the-book.html)
* [Mining Massive Datasets](http://infolab.stanford.edu/~ullman/mmds/book.pdf)
* [A First Encounter with Machine Learning](https://www.ics.uci.edu/~welling/teaching/273ASpring10/IntroMLBook.pdf)
* [Pattern Recognition and Machine Learning](http://www.hua.edu.vn/khoa/fita/wp-content/uploads/2013/08/Pattern-Recognition-and-Machine-Learning-Christophe-M-Bishop.pdf)

## Probability & Statistics

* [Thinking Stats](http://www.greenteapress.com/thinkstats/) - Book + Python Code
* [From Algorithms to Z-Scores](http://heather.cs.ucdavis.edu/probstatbook) - Book
* [The Art of R Programming](http://heather.cs.ucdavis.edu/~matloff/132/NSPpart.pdf) - Book (Not Finished)