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@ -5,7 +5,7 @@ The following is a list of free, open source books on machine learning, statisti
* [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
* [Think 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/)
@ -49,7 +49,7 @@ and Prediction](http://users.soe.ucsc.edu/~draper/draper-BMIP-dec2005.pdf)
## Probability & Statistics
* [Thinking Stats](http://www.greenteapress.com/thinkstats/) - Book + Python Code
* [Think 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)
* [All of Statistics](http://www.ucl.ac.uk/~rmjbale/Stat/wasserman2.pdf)
@ -58,7 +58,7 @@ and Prediction](http://users.soe.ucsc.edu/~draper/draper-BMIP-dec2005.pdf)
* [Introduction to probability](http://math.dartmouth.edu/~prob/prob/prob.pdf) - By Dartmouth College
* [Principle of Uncertainty](http://uncertainty.stat.cmu.edu/wp-content/uploads/2011/05/principles-of-uncertainty.pdf)
* [Probability & Statistics Cookbook](http://matthias.vallentin.net/probability-and-statistics-cookbook/)
* [Advanced Data Analysis From An Elmentary Point of View](http://www.stat.cmu.edu/~cshalizi/ADAfaEPoV/ADAfaEPoV.pdf)
* [Advanced Data Analysis From An Elementary Point of View](http://www.stat.cmu.edu/~cshalizi/ADAfaEPoV/ADAfaEPoV.pdf)
* [Introduction to Probability](http://athenasc.com/probbook.html) - Book and course by MIT
* [The Elements of Statistical Learning: Data Mining, Inference, and Prediction.](http://statweb.stanford.edu/~tibs/ElemStatLearn/) -Book
* [An Introduction to Statistical Learning with Applications in R](http://www-bcf.usc.edu/~gareth/ISL/) - Book