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No, a free online version of An Introduction to Statistical Learning, with Applications in R by James, Witten, Hastie and Tibshirani (Springer, 2013) is available from that website. Springer has agreed to this, so no need to worry about copyright. Of course you may not distribiute printed versions of this pdf file. The emphasis is on supervised learning, but the course addresses the elements of both supervised learning and unsupervised learning. It covers essential material for developing new statistical learning algorithms. Prerequisites Calculus-level probability and statistics, such as in CSI 672, and some general knowledge of applied statistics.

An Introduction to Statistical Learning with Applications in R by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani (June 2013) Book Homepage pdf (9.4Mb, 6th corrected printing) The Elements of Statistical Learning: Data Mining, Inference, and Prediction (Second Edition) by Trevor Hastie, Robert Tibshirani and Jerome Friedman (2009) Statistical Learning Theory 177 It turns out that there are many ways to do so, but no best one. For example in Physics, people tend to prefer models which have a

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ESL = Elements of Statistical Learning, 2nd Ed., by Hastie, Tibshirani, and Friedman ISLR = An Introduction to Statistical Learning with Applications in R, by James, Witten, Hastie, and Tibshirani. ... Tibshirani and FriedmanвЂ™s Elements of Statistical Learning first to Statistical Learning with applications in R Free books on statistical learning.

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