Course Bulletins:

Lectures: Tuesdays 1:10-3:00 in CB 114
Tutorials: Thursdays 1:10-2:00 in RS 208

Instructor: Richard Zemel; email csc2515prof [at sign] cs.toronto.edu
Office Hours: Thursdays 3:00-4:00pm (Pratt 290D) or by appt.

Tutors: Laurent Charlin and Jasper Snoek; email csc2515ta [at sign] cs.toronto.edu

Please do NOT send the instructor 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

Course schedule: The schedule of lectures, readings, and assignments can be found here. It is subject to change.

Prerequisites: You should understand basic probability and statistics, and college-level algebra and calculus. For example it is expected that you know about standard probability distributions (such as Gaussians), and also how to calculate derivatives. Knowledge of linear algebra is also expected. For the programming assignments, you should have some background in programming, and it would be helpful if you know Matlab. Some introductory material for Matlab will be available on the course website as well as in the first tutorial.

Load: About 24 hours of lectures; three assignments; one project; plus one final test.

Required Readings: The textbook for the course is Pattern Recognition and Machine Learning, by Chris Bishop. This will be available in the U of T bookstore. 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.

Marking Scheme:

Three assignments worth 15% each

Project worth 30%

Final test worth 25%

Computing: Parts of the assignments will be done in Matlab, but prior knowledge of Matlab is not essential. [Computing Information] [Matlab Information]

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.