Bibliography recommendations for AIT608

  • Machine Learning, Tom M. Mitchell, McGraw Hill, 1997.
  • Pattern Classification, R. O. Duda, P. E. Hart, D. G. Stork, Wiley, 2001. Book Web page containing additional information.
  • Evolutionary Learning Algorithms for Neural Adaptive Control, Dimitris C. Dracopoulos, Springer Verlag, August 1997.
  • NETLAB: Algorithms for Pattern Recognition, Ian Nabney, Springer Verlag, 2004.
  • Pattern Recognition and Machine Learning, Christopher M. Bishop, Springer Verlag, 2006.
  • Evolutionary Computation: A Unified Approach, Kenneth A. De Jong, 2006, MIT Press.
  • Reinforcement Learning: An Introduction, Richard S. Sutton, Andrew G. Barto, The MIT Press, 1998, available also online.
  • Artificial Intelligence, Rob Callan, Palgrave Macmillan, 2003.
  • Data Mining: Practical Machine Learning Tools and Techniques, Ian H. Witten and Eibe Frank, Elsevier, 2005.
  • MATLAB Guide, Desmond J. Higham and Nicholas J. Higham, SIAM, 2005.
  • Introduction to Machine Learning, Nils J. Nilsson, online notes, Stanford University.
  • Genetic Programming, John R. Koza, MIT Press, 1992.
  • A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition, Lawrence R. Rabiner, Proceedings of the IEEE, 77 (2), February 1989.
  • Matlab Primer, Kermit Sigmon.
  • A Practical Introduction to Matlab, Mark S. Gockenbach.
  • An Introduction to Matlab, David F. Griffiths, University of Dundee.
    Last modified: Thu Feb 28 10:35:20 GMT 2008