Books:

The second and third books by Mackay and Hastie et al. are available electronically.

  • Christopher Bishop, Pattern Recognition and Machine Learning, Springer, 2006.

  • Trevor Hastie, Robert Tibshirani, and Jerome Friedman, Statistical Learning, Springer, 2009 (2nd edition). (PDF version available here ).

  • David MacKay, Information Theory, Inference, and Learning Algorithms, Cambridge University Press, 2003. ( PDF version available here ).

  • Bernhard Scholkopf and Alexander Smola, Learning with Kernels, MIT Press, 2001.

  • Duda, Hart, and Stork: Pattern Classification (Wiley), 2nd edition .

  • Richard Sutton and Andrew Barto, Reinforcement Learning, MIT Press, 1998. (Online version available here ).

  • Mitchell, Tom: Machine Learning, McGraw-Hill, 1997.

    Mathematical Foundations:

    Additionaly, you will find it helpful to consult background texts on mathematical foundations, including linear algebra (e.g. Strang), statistics (e.g. Casella and Berger), and convex optimization (e.g., Boyd and Vanderberge).

  • Casella and Berger, Statistical Inference, Duxbury Press, 2001.

  • Weber, Statistics , a concise overview of statistics from a course taught at Cambridge University, 2000.

  • Gilbert Strang, Introduction to Linear Algebra, Wellesley Press, 2009. (See this link for online lectures by Strang).

  • Steven Boyd and Lieven Vandenberghe, Convex Optimization, Cambridge University Press, 2004. (There is an online PDF version at this website ).

  • Fan Chung Graham, Spectral Graph Theory, American Mathematical Society, 1996.

    Research Forums

  • Two premier forums for publication of current research in machine learning are the annual International Conference on Machine Learning (ICML) and the International Neural Information Processing systems (NIPS) conference. You will be required to present 2-3 papers from recent ICML/NIPS proceedings at the end of the class.

  • Two premier journal forums for publication of current research are the Journal for Machine Learning Research, and the Machine Learning journal.

  • Besides the above, ML research is reported in a vast array of auxiliary conferences and journals, including AAAI, UAI, IEEE conferences and journals, statistics conferences and journals.