• Stuart Russell and Peter Norvig, "Artificial Intelligence: A Modern Approach", 2nd edition, Prentice Hall, 2002
  • Richard O. Duda, Peter E. Hart, David G. Stork, "Pattern Classification", 2nd Edition, John Wiley & Sons, November 2000
  • Tom M. Mitchel, "Machine Learning", available here.
  • Trevor Hastie, Robert Tibshirani, Jerome Friedman, "The Elements of Statistical Learning: Data Mining, Inference, and Prediction", 2nd edition, Springer, February 2009, available here.
  • Morris H. DeGroot, Probability and Statistics, 2nd edition, Addison-Wesley, January 1986.

Bayesian Networks and Causality:

  • Judea Perl, "Causality: models, reasoning, and inference", Cambridge University Press New York, NY, 2000.

  • Peter Spirtes, Clark Glymour, Richard Scheines, "Causation, Prediction, and Search", available here.

Optimization Theory and Support Vector Machines
  • Christopher J.C. Burges, "A Tutorial on Support Vector Machines for Pattern Recognition", Data Mining and Knowledge Discovery, Volume 2, Issue 2, pp 121-167, available here.
  • Nello Cristianini and John Shawe-Taylor, "An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods", Cambridge University Press, Cambridge, U.K., 2000. 

Τελευταία τροποποίηση: Δευτέρα, 21 Δεκεμβρίου 2015, 1:17 PM