Thursday, October 15

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.

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