CSC2515 -- Fall 2007
Introduction to Machine Learning

Students should check these pages at least once a week for important information.

News:

Assignment 4 is now available here.

For students who are doing a Netflix project, information can be found here.

Lectures and Tutorials: Tuesdays 11.00am-2.00pm Room BA B024 (in the basement)
The three hour period will typically be used for a two hour lecture and a one hour tutorial.
First lecture September 11

Instructors: Geoffrey Hinton and Richard Zemel; email csc2515prof[at sign]cs.toronto.edu
Office Hours: Richard Zemel: Thursdays 2.00-3.00pm (Pratt 290D)

Tutors: Andriy Mnih and Russ Salakhutdinov; email csc2515ta[at sign]cs.toronto.edu
Office Hours: Thursdays 3.00-4.00pm (Pratt 275)

Please do NOT send the instructors or tutors email about the class directly to their personal accounts. It will be deleted. We will only respond to class email if it is sent to csc2515prof or csc2515ta[at sign]cs.toronto.edu

Prerequisites: some knowledge of calculus, linear algebra, and statistics
Load: About 26 hours of lectures; four assignments; one project.

Required Readings: The textbook for the course is "Pattern Recognition and Machine Learning" by Chris Bishop. This was being sold at a large discount by Amazon.ca so, to save you money, we bought all of their copies. With tax, the cost was $52.50 each. Please buy them from us at the first or second lecture. Most of the required readings will be parts of the textbook but there will be some additional readings and we will not cover all of the chapters in the textbook. The same textbook will be used for the advanced machine learning course (csc2535) after Christmas. (see Lectures, Readings, & Due Dates) for details of the required readings.

Marking Scheme
Project worth 36%
Four assignments worth 16% each

Computing
The project and parts of the assignments will be done in Matlab, but prior knowledge of Matlab is not essential.

Auditing
If you are not registered in the class, it is possible for you to audit it (sit in on the lectures), but only if you get the instructor's permission and follow some rules. See the audit page for more info.