Old announcements 11/11 (Wednesday): Homework 6 has been released. 11/10 (Tuesday): The grade/comments for Homework 4 have been released. 10/29 (Thursday): Homework 5 has been released. 10/27 (Tuesday): The grade of homework 3 has been released in the compass system. 10/19 (Monday): The solution of Homework 4 has been released.

Course Information

	Course Information
	Handouts & Resources
	Schedule
	Lecture Notes
	Problem Sets & Exams

Books

Text: Tom Mitchell, Machine Learning (McGraw Hill 1997) I will not follow the text book closely - most of the material covered isn't there, but it is still a very useful book to have. Some, but not all of the material covered is covered in the recommended books below. All the books listed below are reserved in the Engineering Library. If you plan to do research in Machine Learning or related areas you will eventually need these books; otherwise, borrowing a copy may be sufficient for now.

Recommended books: Duda and Hart, Pattern Recognition and Scene Analysis (Wiley 1973 - Out of Print) Duda, Hart, and Stork, Pattern Classification (Wiley 2000) J. Shawe-Taylor and N Crisianini, Kernel Methods for Pattern Analysis (Cambridge University Press 2004) C. M. Bishop, Neural Networks for Pattern Recognition (Oxford University Press 1996) Kearns and Vazirani, Introduction to Computational Learning Theory (MIT Press 1994) Schölkopf and Smola, Learning with Kernels (MIT Press 2002) Herbrich, Learning Kernel Classifiers (MIT Press 2002)