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@ -301,6 +301,13 @@ Original Source: [Free Programming books](http://stackoverflow.com/revisions/392
* [Practical and Theoretical Aspects of Compiler Construction](http://www.stanford.edu/class/archive/cs/cs143/cs143.1128/) (class lectures and slides) * [Practical and Theoretical Aspects of Compiler Construction](http://www.stanford.edu/class/archive/cs/cs143/cs143.1128/) (class lectures and slides)
#### Computer Vision
* [Computer Vision](http://homepages.inf.ed.ac.uk/rbf/BOOKS/BANDB/bandb.htm) - Dana Ballard, Chris Brown
* [Computer Vision: Algorithms and Applications](http://szeliski.org/Book/) - Richard Szeliski
* [Computer Vision: Models, Learning, and Inference](http://www.computervisionmodels.com/) - Simon J.D. Prince
* [Programming Computer Vision with Python](http://programmingcomputervision.com/) - Jan Erik Solem
#### Database #### Database
* [Big Data Now: Current Perspectives from O'Reilly Radar](http://shop.oreilly.com/product/0636920022640.do) * [Big Data Now: Current Perspectives from O'Reilly Radar](http://shop.oreilly.com/product/0636920022640.do)
* [Database Fundamentals](http://public.dhe.ibm.com/software/dw/db2/express-c/wiki/Database_fundamentals.pdf) (PDF) * [Database Fundamentals](http://public.dhe.ibm.com/software/dw/db2/express-c/wiki/Database_fundamentals.pdf) (PDF)
@ -337,7 +344,6 @@ Original Source: [Free Programming books](http://stackoverflow.com/revisions/392
* [An Introduction to Statistical Learning](http://www-bcf.usc.edu/~gareth/ISL/) - Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani * [An Introduction to Statistical Learning](http://www-bcf.usc.edu/~gareth/ISL/) - Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani
* [Artificial Intelligence | Machine Learning](http://see.stanford.edu/see/materials/aimlcs229/handouts.aspx) - Andrew Ng *(Notes, lectures, and problems)* * [Artificial Intelligence | Machine Learning](http://see.stanford.edu/see/materials/aimlcs229/handouts.aspx) - Andrew Ng *(Notes, lectures, and problems)*
* [Bayesian Reasoning and Machine Learning](http://web4.cs.ucl.ac.uk/staff/D.Barber/pmwiki/pmwiki.php?n=Brml.HomePage) * [Bayesian Reasoning and Machine Learning](http://web4.cs.ucl.ac.uk/staff/D.Barber/pmwiki/pmwiki.php?n=Brml.HomePage)
* [Computer Vision: Algorithms and Applications](http://hackershelf.com/book/134/computer-vision-algorithms-and-applications/)
* [Gaussian Processes for Machine Learning](http://www.gaussianprocess.org/gpml/) * [Gaussian Processes for Machine Learning](http://www.gaussianprocess.org/gpml/)
* [Inductive Logic Programming](http://www-ai.ijs.si/SasoDzeroski/ILPBook/) * [Inductive Logic Programming](http://www-ai.ijs.si/SasoDzeroski/ILPBook/)
* [Information Theory, Inference, and Learning Algorithms](http://www.inference.phy.cam.ac.uk/itila/) * [Information Theory, Inference, and Learning Algorithms](http://www.inference.phy.cam.ac.uk/itila/)
@ -348,7 +354,6 @@ Original Source: [Free Programming books](http://stackoverflow.com/revisions/392
* [Machine Learning, Neural and Statistical Classification](http://www1.maths.leeds.ac.uk/~charles/statlog/whole.pdf) (PDF) or [online version](http://www1.maths.leeds.ac.uk/~charles/statlog/) - This book is based on the EC (ESPRIT) project StatLog. * [Machine Learning, Neural and Statistical Classification](http://www1.maths.leeds.ac.uk/~charles/statlog/whole.pdf) (PDF) or [online version](http://www1.maths.leeds.ac.uk/~charles/statlog/) - This book is based on the EC (ESPRIT) project StatLog.
* [Neural Networks and Deep Learning](http://neuralnetworksanddeeplearning.com) * [Neural Networks and Deep Learning](http://neuralnetworksanddeeplearning.com)
* [Probabilistic Models in the Study of Language](http://idiom.ucsd.edu/~rlevy/pmsl_textbook/text.html) (Draft, with R code) * [Probabilistic Models in the Study of Language](http://idiom.ucsd.edu/~rlevy/pmsl_textbook/text.html) (Draft, with R code)
* [Programming Computer Vision with Python](http://programmingcomputervision.com/) - Jan Erik Solem
* [Reinforcement Learning: An Introduction](http://webdocs.cs.ualberta.ca/~sutton/book/ebook/the-book.html) * [Reinforcement Learning: An Introduction](http://webdocs.cs.ualberta.ca/~sutton/book/ebook/the-book.html)
* [The Elements of Statistical Learning](http://www-stat.stanford.edu/~tibs/ElemStatLearn/) - Trevor Hastie, Robert Tibshirani, and Jerome Friedman * [The Elements of Statistical Learning](http://www-stat.stanford.edu/~tibs/ElemStatLearn/) - Trevor Hastie, Robert Tibshirani, and Jerome Friedman
* [The LION Way: Machine Learning plus Intelligent Optimization](http://www.e-booksdirectory.com/details.php?ebook=9575) * [The LION Way: Machine Learning plus Intelligent Optimization](http://www.e-booksdirectory.com/details.php?ebook=9575)

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