machine-learning/books.md

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

## Machine-Learning / Data Mining

* [Real World Machine Learning](https://www.manning.com/books/real-world-machine-learning) [Free Chapters]
* [An Introduction To Statistical Learning](http://www-bcf.usc.edu/~gareth/ISL/) - Book + R Code
* [Elements of Statistical Learning](http://web.stanford.edu/~hastie/ElemStatLearn/) - Book
* [Probabilistic Programming & Bayesian Methods for Hackers](http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/) - Book + IPython Notebooks
* [Think Bayes](http://greenteapress.com/wp/think-bayes/) - 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://users.isr.ist.utl.pt/~wurmd/Livros/school/Bishop%20-%20Pattern%20Recognition%20And%20Machine%20Learning%20-%20Springer%20%202006.pdf)
* [Machine Learning & Bayesian Reasoning](http://web4.cs.ucl.ac.uk/staff/D.Barber/textbook/090310.pdf)
* [Introduction to Machine Learning](http://alex.smola.org/drafts/thebook.pdf) - Alex Smola and S.V.N. Vishwanathan
* [A Probabilistic Theory of Pattern Recognition](http://www.szit.bme.hu/~gyorfi/pbook.pdf)
* [Introduction to Information Retrieval](http://nlp.stanford.edu/IR-book/pdf/irbookprint.pdf)
* [Forecasting: principles and practice](https://www.otexts.org/fpp/)
* [Practical Artificial Intelligence Programming in Java](https://www.saylor.org/site/wp-content/uploads/2011/11/CS405-1.1-WATSON.pdf)
* [Introduction to Machine Learning](https://arxiv.org/pdf/0904.3664v1.pdf) - Amnon Shashua
* [Reinforcement Learning](http://www.intechopen.com/books/reinforcement_learning)
* [Machine Learning](http://www.intechopen.com/books/machine_learning)
* [A Quest for AI](http://ai.stanford.edu/~nilsson/QAI/qai.pdf)
* [Introduction to Applied Bayesian Statistics and Estimation for Social Scientists](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.177.857&rep=rep1&type=pdf) - Scott M. Lynch
* [Bayesian Modeling, Inference and Prediction](https://users.soe.ucsc.edu/~draper/draper-BMIP-dec2005.pdf)
* [A Course in Machine Learning](http://ciml.info/)
* [Machine Learning, Neural and Statistical Classification](http://www1.maths.leeds.ac.uk/~charles/statlog/)
* [Bayesian Reasoning and Machine Learning](http://web4.cs.ucl.ac.uk/staff/D.Barber/pmwiki/pmwiki.php?n=Brml.HomePage) Book+MatlabToolBox
* [R Programming for Data Science](https://leanpub.com/rprogramming)
* [Data Mining - Practical Machine Learning Tools and Techniques](http://cs.du.edu/~mitchell/mario_books/Data_Mining:_Practical_Machine_Learning_Tools_and_Techniques_-_2e_-_Witten_&_Frank.pdf) Book

## Deep-Learning

* [Deep Learning - An MIT Press book](http://www.deeplearningbook.org/)

## Natural Language Processing

* [Coursera Course Book on NLP](http://www.cs.columbia.edu/~mcollins/notes-spring2013.html)
* [NLTK](http://www.nltk.org/book/)
* [NLP w/ Python](http://victoria.lviv.ua/html/fl5/NaturalLanguageProcessingWithPython.pdf)
* [Foundations of Statistical Natural Language Processing](http://nlp.stanford.edu/fsnlp/promo/)

## Information Retrieval

* [An Introduction to Information Retrieval](http://nlp.stanford.edu/IR-book/pdf/irbookonlinereading.pdf)

## Neural Networks

* [A Brief Introduction to Neural Networks](http://www.dkriesel.com/_media/science/neuronalenetze-en-zeta2-2col-dkrieselcom.pdf)
* [Neural Networks and Deep Learning](http://neuralnetworksanddeeplearning.com/)

## Probability & Statistics

* [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)
* [Introduction to statistical thought](http://people.math.umass.edu/~lavine/Book/book.pdf)
* [Basic Probability Theory](http://www.math.uiuc.edu/~r-ash/BPT/BPT.pdf)
* [Introduction to probability](https://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://statistics.zone/)
* [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
* [Learning Statistics Using R](http://health.adelaide.edu.au/psychology/ccs/teaching/lsr/)
* [Introduction to Probability and Statistics Using R](https://cran.r-project.org/web/packages/IPSUR/vignettes/IPSUR.pdf) - Book
* [Advanced R Programming](http://adv-r.had.co.nz) - Book
* [Practical Regression and Anova using R](http://cran.r-project.org/doc/contrib/Faraway-PRA.pdf) - Book
* [R practicals](http://www.columbia.edu/~cjd11/charles_dimaggio/DIRE/resources/R/practicalsBookNoAns.pdf) - Book
* [The R Inferno](http://www.burns-stat.com/pages/Tutor/R_inferno.pdf) - Book

## Linear Algebra

* [Linear Algebra Done Wrong](http://www.math.brown.edu/~treil/papers/LADW/book.pdf)
* [Linear Algebra, Theory, and Applications](https://math.byu.edu/~klkuttle/Linearalgebra.pdf)
* [Convex Optimization](http://web.stanford.edu/~boyd/cvxbook/bv_cvxbook.pdf)
* [Applied Numerical Computing](http://www.seas.ucla.edu/~vandenbe/103/reader.pdf)
* [Applied Numerical Linear Algebra](http://egrcc.github.io/docs/math/applied-numerical-linear-algebra.pdf)
added list of ML books 2014-07-17 13:41:41 -04:00			`The following is a list of free, open source books on machine learning, statistics, data-mining, etc.`

			`## Machine-Learning / Data Mining`

Update links 2017-02-13 06:26:41 -05:00			`* [Real World Machine Learning](https://www.manning.com/books/real-world-machine-learning) [Free Chapters]`
added list of ML books 2014-07-17 13:41:41 -04:00			`* [An Introduction To Statistical Learning](http://www-bcf.usc.edu/~gareth/ISL/) - Book + R Code`
correct link to ESL 2017-07-10 14:46:42 -04:00			`* [Elements of Statistical Learning](http://web.stanford.edu/~hastie/ElemStatLearn/) - Book`
added list of ML books 2014-07-17 13:41:41 -04:00			`* [Probabilistic Programming & Bayesian Methods for Hackers](http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/) - Book + IPython Notebooks`
Update links 2017-02-13 06:26:41 -05:00			`* [Think Bayes](http://greenteapress.com/wp/think-bayes/) - Book + Python Code`
added list of ML books 2014-07-17 13:41:41 -04:00			`* [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)`
fix the 404 error for the book of PRML fix the 404 error for the book of PRML(Pattern recognition and Machine Learning) and replace it with a new resource I found on the Internet 2016-12-09 19:45:01 -05:00			`* [Pattern Recognition and Machine Learning](http://users.isr.ist.utl.pt/~wurmd/Livros/school/Bishop%20-%20Pattern%20Recognition%20And%20Machine%20Learning%20-%20Springer%20%202006.pdf)`
added books; 2014-07-20 18:51:53 -04:00			`* [Machine Learning & Bayesian Reasoning](http://web4.cs.ucl.ac.uk/staff/D.Barber/textbook/090310.pdf)`
adding authors to intro to machine learning Adding authors to same titled links. Adding Machine Learning, Neural and Statistical Classification book link. 2015-05-15 01:03:14 -04:00			`* [Introduction to Machine Learning](http://alex.smola.org/drafts/thebook.pdf) - Alex Smola and S.V.N. Vishwanathan`
added books; 2014-07-20 18:51:53 -04:00			`* [A Probabilistic Theory of Pattern Recognition](http://www.szit.bme.hu/~gyorfi/pbook.pdf)`
			`* [Introduction to Information Retrieval](http://nlp.stanford.edu/IR-book/pdf/irbookprint.pdf)`
Update links 2017-02-13 06:26:41 -05:00			`* [Forecasting: principles and practice](https://www.otexts.org/fpp/)`
Update link Current link to 'Practical Artificial Intelligence Programming in Java' does not point to book. Maybe you can use link proposed here. 2017-05-17 12:40:14 -04:00			`* [Practical Artificial Intelligence Programming in Java](https://www.saylor.org/site/wp-content/uploads/2011/11/CS405-1.1-WATSON.pdf)`
Update links 2017-02-13 06:26:41 -05:00			`* [Introduction to Machine Learning](https://arxiv.org/pdf/0904.3664v1.pdf) - Amnon Shashua`
added more books 2014-07-20 19:01:10 -04:00			`* [Reinforcement Learning](http://www.intechopen.com/books/reinforcement_learning)`
			`* [Machine Learning](http://www.intechopen.com/books/machine_learning)`
			`* [A Quest for AI](http://ai.stanford.edu/~nilsson/QAI/qai.pdf)`
whitesapce fix 2016-08-31 11:38:44 -04:00			`* [Introduction to Applied Bayesian Statistics and Estimation for Social Scientists](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.177.857&rep=rep1&type=pdf) - Scott M. Lynch`
Update links 2017-02-13 06:26:41 -05:00			`* [Bayesian Modeling, Inference and Prediction](https://users.soe.ucsc.edu/~draper/draper-BMIP-dec2005.pdf)`
books.md: Add CIML and fix typo 2015-02-09 23:27:31 -05:00			`* [A Course in Machine Learning](http://ciml.info/)`
adding authors to intro to machine learning Adding authors to same titled links. Adding Machine Learning, Neural and Statistical Classification book link. 2015-05-15 01:03:14 -04:00			`* [Machine Learning, Neural and Statistical Classification](http://www1.maths.leeds.ac.uk/~charles/statlog/)`
add BOOK Bayesian Reasoning and Machine Learning 2015-10-24 23:27:09 -04:00			`* [Bayesian Reasoning and Machine Learning](http://web4.cs.ucl.ac.uk/staff/D.Barber/pmwiki/pmwiki.php?n=Brml.HomePage) Book+MatlabToolBox`
Updated books.md 2015-12-28 16:58:04 -05:00			`* [R Programming for Data Science](https://leanpub.com/rprogramming)`
Update links 2017-02-13 06:26:41 -05:00			`* [Data Mining - Practical Machine Learning Tools and Techniques](http://cs.du.edu/~mitchell/mario_books/Data_Mining:_Practical_Machine_Learning_Tools_and_Techniques_-_2e_-_Witten_&_Frank.pdf) Book`
added list of ML books 2014-07-17 13:41:41 -04:00
Deep Learning Section added New Deep Learning - An MIT Press book added 2016-04-07 13:50:15 -04:00			`## Deep-Learning`

			`* [Deep Learning - An MIT Press book](http://www.deeplearningbook.org/)`

books.md: Add CIML and fix typo 2015-02-09 23:27:31 -05:00			`## Natural Language Processing`
added NLP section 2014-07-22 10:29:50 -04:00
			`* [Coursera Course Book on NLP](http://www.cs.columbia.edu/~mcollins/notes-spring2013.html)`
more books 2014-07-22 10:32:55 -04:00			`* [NLTK](http://www.nltk.org/book/)`
			`* [NLP w/ Python](http://victoria.lviv.ua/html/fl5/NaturalLanguageProcessingWithPython.pdf)`
Update books.md 2015-02-13 08:34:02 -05:00			`* [Foundations of Statistical Natural Language Processing](http://nlp.stanford.edu/fsnlp/promo/)`
add irbook 2015-08-18 02:24:35 -04:00
			`## Information Retrieval`

			`* [An Introduction to Information Retrieval](http://nlp.stanford.edu/IR-book/pdf/irbookonlinereading.pdf)`
added NLP section 2014-07-22 10:29:50 -04:00
Add Neural Networks section 2015-03-22 06:37:56 -04:00			`## Neural Networks`

			`* [A Brief Introduction to Neural Networks](http://www.dkriesel.com/_media/science/neuronalenetze-en-zeta2-2col-dkrieselcom.pdf)`
books: neural-network: add new book http://neuralnetworksanddeeplearning.com is a great book (html version unfortunately) on Neural network. 2016-10-08 10:37:26 -04:00			`* [Neural Networks and Deep Learning](http://neuralnetworksanddeeplearning.com/)`
Add Neural Networks section 2015-03-22 06:37:56 -04:00
added list of ML books 2014-07-17 13:41:41 -04:00			`## Probability & Statistics`

Fix typos. 2015-12-27 03:58:57 -05:00			`* [Think Stats](http://www.greenteapress.com/thinkstats/) - Book + Python Code`
added list of ML books 2014-07-17 13:41:41 -04:00			`* [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)`
Update links 2017-02-13 06:26:41 -05:00			`* [Introduction to statistical thought](http://people.math.umass.edu/~lavine/Book/book.pdf)`
added books; 2014-07-20 18:51:53 -04:00			`* [Basic Probability Theory](http://www.math.uiuc.edu/~r-ash/BPT/BPT.pdf)`
Update links 2017-02-13 06:26:41 -05:00			`* [Introduction to probability](https://math.dartmouth.edu/~prob/prob/prob.pdf) - By Dartmouth College`
added books; 2014-07-20 18:51:53 -04:00			`* [Principle of Uncertainty](http://uncertainty.stat.cmu.edu/wp-content/uploads/2011/05/principles-of-uncertainty.pdf)`
Update links 2017-02-13 06:26:41 -05:00			`* [Probability & Statistics Cookbook](http://statistics.zone/)`
Fix typos. 2015-12-27 03:58:57 -05:00			`* [Advanced Data Analysis From An Elementary Point of View](http://www.stat.cmu.edu/~cshalizi/ADAfaEPoV/ADAfaEPoV.pdf)`
add some books 2015-03-22 08:26:48 -04:00			`* [Introduction to Probability](http://athenasc.com/probbook.html) - Book and course by MIT`
Add BangML meetup group 2016-11-13 22:30:06 -05:00			`* [The Elements of Statistical Learning: Data Mining, Inference, and Prediction.](http://statweb.stanford.edu/~tibs/ElemStatLearn/) -Book`
add some books 2015-03-22 08:26:48 -04:00			`* [An Introduction to Statistical Learning with Applications in R](http://www-bcf.usc.edu/~gareth/ISL/) - Book`
moving lsr to books 2015-06-08 18:00:06 -04:00			`* [Learning Statistics Using R](http://health.adelaide.edu.au/psychology/ccs/teaching/lsr/)`
Updated books.md 2015-12-28 16:58:04 -05:00			`* [Introduction to Probability and Statistics Using R](https://cran.r-project.org/web/packages/IPSUR/vignettes/IPSUR.pdf) - Book`
Added R Programming books under "Probability & Statistics" 2015-12-31 21:27:47 -05:00			`* [Advanced R Programming](http://adv-r.had.co.nz) - Book`
			`* [Practical Regression and Anova using R](http://cran.r-project.org/doc/contrib/Faraway-PRA.pdf) - Book`
			`* [R practicals](http://www.columbia.edu/~cjd11/charles_dimaggio/DIRE/resources/R/practicalsBookNoAns.pdf) - Book`
			`* [The R Inferno](http://www.burns-stat.com/pages/Tutor/R_inferno.pdf) - Book`
added list of ML books 2014-07-17 13:41:41 -04:00
added books; 2014-07-20 18:51:53 -04:00			`## Linear Algebra`

books.md: Fix link to LADW book The book resides at: http://www.math.brown.edu/~treil/papers/LADW/book.pdf 2015-02-13 07:48:47 -05:00			`* [Linear Algebra Done Wrong](http://www.math.brown.edu/~treil/papers/LADW/book.pdf)`
added books; 2014-07-20 18:51:53 -04:00			`* [Linear Algebra, Theory, and Applications](https://math.byu.edu/~klkuttle/Linearalgebra.pdf)`
Update links 2017-02-13 06:26:41 -05:00			`* [Convex Optimization](http://web.stanford.edu/~boyd/cvxbook/bv_cvxbook.pdf)`
added books; 2014-07-20 18:51:53 -04:00			`* [Applied Numerical Computing](http://www.seas.ucla.edu/~vandenbe/103/reader.pdf)`
Update links 2017-02-13 06:26:41 -05:00			`* [Applied Numerical Linear Algebra](http://egrcc.github.io/docs/math/applied-numerical-linear-algebra.pdf)`