Old announcements 12/5: Practice final is now available. 11/29: In problem set #6, part (f) and (g) of question 2 is changed. 11/27: The final projects are due on Thursday, December 13th. Please send email with the final report to (danr at uiuc dot edu). Please consult the suggestions for how to write the project report. The final exam is on Monday December 10th at 1:30pm in 1105SC. Problem set #6 released. Due date: 12/6. You may not use extra hours for this homework. 11/13: Problem set #5's due date has been changed to tuesday 11/20 at 4:00pm. 10/23: Midterm solution is now available.

Course Information

	Course Information
	Handouts & Resources
	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)