Books

  • Machine Learning by Tom M. Mitchell (Hardcover)

  • The Elements of Statistical Learning by by T. Hastie, R. Tibshirani, J. H. Friedman (Hardcover)

  • Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning) by Bernhard Schölkopf (Author), Alexander J. Smola (Author) (Hardcover)

  • An Introduction to Support Vector Machines and Other Kernel-based Learning Methods by Nello Cristianini (Author), John Shawe-Taylor (Author) (Hardcover - March 2000)

  • Artificial Intelligence: A Modern Approach (2nd Edition)Peter Norvig (Author) (Hardcover)

  • C4.5: Programs for Machine Learning by J. Ross Quinlan, Ross Quinlan (Paperback)

  • Readings in Machine Learning (The Morgan Kaufmann Series in Machine Learning) by Jude W. Shavlik (Editor), Thomas G. Dietterich (Editor) (Paperback - December 1990)

  • Genetic Algorithms in Search, Optimization, and Machine Learning by David E. Goldberg (Author) (Hardcover)

  • Learning in Graphical Models (Adaptive Computation and Machine Learning) by Michael I. Jordan (Editor) (Paperback)

  • Bioinformatics (Adaptive Computation and Machine Learning) by Pierre Baldi (Author), Søren Brunak (Author) (Hardcover)

  • Computer Systems That Learn: Classification and Prediction Methods from Statistics, Neural Nets, Machine Learning, and Expert Systems by Casimir A. Kulikowski (Editor), Sholom Weiss (Editor) (Hardcover - January 1991)

  • Principles of Data Mining (Adaptive Computation and Machine Learning) by David J. Hand, et al (Hardcover)

  • Causation, Prediction, and Search, Second Edition (Adaptive Computation and Machine Learning) by Peter Spirtes (Author), et al (Hardcover)

  • Concept Formation: Knowledge and Experience in Unsupervised Learning (Morgan Kaufmann Series in Machine Learning) by Pat Langley (Editor), et al (Hardcover - August 1991)

  • Elements of Machine Learning by Pat Langley, Michael B. Morgan (Editor) (Hardcover - September 1995)

  • Machine Learning : Paradigms and Methods by Jaime Carbonell (Editor)

  • Machine Learning: A Guide to Current Research (Kluwer International Series in Engineering and Computer Science, 12) by Tom M. Mitchell (Editor), et al (Hardcover - February 2002)

  • Learning Bayesian Networks by Richard E. Neapolitan (Author)(Hardcover)

  • Probabilistic Reasoning in Expert Systems: Theory and Algorithms by Richard E. Neapolitan (Author)

  • Causality : Models, Reasoning, and Inference by Judea Pearl (Author) (Hardcover - March 2001)

  • Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference by Judea Pearl (Paperback - April 1997)

  • Computation, Causation, and Discovery by Clark Glymour (Editor), Gregory F. Cooper (Editor) (Paperback)