I'm just finishing my reading of the Artificial Intelligence a modern approach 3rd Ed. by Perter Norvig. I used this book mostly as an introduction, and to learn more about the general concept of AI. I'll soon start in a machine learning study group with one of my professors and I'd like to know if anyone knows some good books to learn more about Machine Learning (especially Neural Nets, but not just it).
Here's some extracts from the reading list of a course I finished recently:
Machine Learning by Tom Mitchell, McGraw-Hill Press, 1997
D. Chen and P. Burrell, 'Case-based reasoning system and artificial neural networks: A Review (pdf file)', in Neural Computing & Applications, vol. 10, no. 3, pp. 264-276, 2001 (Copyright 2001 Springer).
M.F. Valstar and M. Pantic, 'Biologically vs. logic inspired encoding of facial actions and emotions in video (pdf file)', in Proc. IEEE Int'l Conf. on Multimedia and Expo (ICME '06), Toronto, Canada, July 2006 (Copyright 2006 IEEE Press).
S. Petridis and M. Pantic, 'Audiovisual Discrimination between Laughter and Speech (pdf file)', in Proc. IEEE Int’l Conf. Acoustics, Speech and Signal Processing (ICASSP’08), pp. 5117-5120, Las Vegas, USA, April 2008 (Copyright © 2008 IEEE Press).
Pattern Classification by R.O. Duda, P.E. Hart, and D.G. Stork, John Wiley Press, 2005.
Pattern Recognition and Machine Learning by Christopher Bishop, Springer, 2006
You may want to check out these free online courses:
Elements of Statistical Learning
This book (there's a free PDF available in the link webpage) is an excellent and nearly exhaustive review of the field of machine learning. I know this sounds a bit presumptuous, but it's that good.
By the way, even though the book of Norvig and Russell is very good, it provides next to nothing on machine learning. So, the PDF will be a tough read if you are not sure of your math background.
