An overview of statistical learning theory, containing no proofs, but most of the crucial theorems and milestones of learning theory. With a detailed chapter on SVMs for pattern recognition and regression
The goal of this textbook is to present the key algorithms and theory that form the core of machine learning. Machine learning draws on concepts and results from many fields, including statistics, artificial intelligence, philosophy, information the
This compact book provides a user-friendly tour for the uninitiated of the Mac Unix base. You can safely explore Terminal and familiarize yourself with the command line, learning as you go about the hundreds of Unix programs that come with your Mac.
Statistical machine learning algorithms deal with the problem of selecting an appropriate statistical model from a model space based on a training set {xi}N i=1 ⊂ X or {(xi, yi)}N i=1 ⊂ X × Y. In doing so they either implicitly or explicitly make
