Free Data Science Books

Title: Free Datascience books

URL Source: http://www.p-value.info/2012/11/free-datascience-books.html

Markdown Content:
# [p-value.info](http://www.p-value.info/)

Musings on data science, machine learning and stats.

## Sunday, November 25, 2012

[](http://www.p-value.info/2012/11/free-datascience-books.html)
### Free Datascience books

I've been impressed in recent months by the number and quality of free datascience/machine learning books available online. I don't mean free as in some guy paid for a PDF version of an O'Reilly book and then posted it online for others to use/steal, but I mean genuine published books with a free online version sanctioned by the publisher. That is, "the publisher has graciously agreed to allow a full, free version of my book to be available on this site."

Here are a few in my collection:

* [Mining of Massive datasets](http://infolab.stanford.edu/~ullman/mmds.html) by Rajamaran, Leskovic & Ullman
* [Bayesian Reasoning and Machine Learning](http://web4.cs.ucl.ac.uk/staff/D.Barber/textbook/090310.pdf) by David Barber [[website](http://web4.cs.ucl.ac.uk/staff/D.Barber/pmwiki/pmwiki.php?n=Brml.HomePage)]
* [Information Theory, Inference, and Learning Algorithms](http://www.inference.phy.cam.ac.uk/mackay/itila/) by David J.C. Mackay
* ~~[Foundations of Statistical Natural Language Processing](http://www-nlp.stanford.edu/fsnlp/) by Manning & Schütze~~only sample chapters

While we are on the subject, I would be remiss of me not to recommend D.J. Patil's free minibooks/essays. While they are not the thick comprehensive tomes of those above, they are definitely worth the time to read.

* [Data Jujitsu](http://oreillynet.com/oreilly/data/radarreports/data-jujitsu.csp) by D.J. Patil
* [Building Data Science Teams](http://shop.oreilly.com/product/0636920022770.do) by D.J. Patil

Finally, this is work in progress (just 3 chapters to date) but is one to watch: [Network Science](http://barabasilab.neu.edu/networksciencebook/downlPDF.html) by A.-L. Barabasi.

Update [12/27/12]: adding in some additions from a[hacker news discussion](http://news.ycombinator.com/item?id=4973450)and the comments below (thanks guys):

* [Introduction to Information Retrieval](http://www-nlp.stanford.edu/IR-book/), by Manning, Raghavan and Schütze[](http://nlp.stanford.edu/~manning/)
* [A first encounter with machine learning](https://www.ics.uci.edu/~welling/teaching/273ASpring10/IntroMLBook.pdf) by Welling
* [Gaussian processes for Machine Learning](http://www.gaussianprocess.org/gpml/chapters/RW.pdf) by C.E. Rasmussen
* [The Elements of Statistical Learning](http://www-stat.stanford.edu/~tibs/ElemStatLearn/), by Hastie, Tibshirani, Friedman -- grandaddy of them all
* [Introduction to Machine Learning](http://alex.smola.org/drafts/thebook.pdf)by Smola, Vishwanathan
* [Think Bayes](http://www.greenteapress.com/thinkbayes/thinkbayes.pdf) by Downey

Posted by [Carl Anderson](https://www.blogger.com/profile/11930448254473684406 "author profile") at [2:47 PM](http://www.p-value.info/2012/11/free-datascience-books.html "permanent link")[](https://www.blogger.com/post-edit.g?blogID=5547907074344788039&postID=1838504413927202579&from=pencil "Edit Post")

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