Elements of Statistical Learning 2nd edition and Other Books

The second edition of the classic, Elements of Statistical Learning is available. The book covers topics such as:

• Supervised and Unsupervised Learning
• Regression
• Linear Classification (including LDA)
• Kernel Methods
• Evaluation and Assessment (including the right and wrong way to do cross-validation)
• Bayesian inference
• Decision Trees and boosting methods
• Neural Nets
• SVMs
• K-Means clustering and nearest neighbor classification
• Random Forests
• Ensemble learning (shown to be very effective in the Netflix competition)
• Undirected Graphical Models (including RBMs)

The PDF is available for download, so you can read/search it before you buy it.

While you're looking at books, another book to check out is Probabilistic Graphical Models.