CSC321 Spring 2013
Introduction to Neural Networks and Machine Learning

Look here at least one a week for news about the course.

This course is going to be taught by Tijmen Tieleman with help from Geoffrey Hinton using the "reverse classroom" model. Each lecture has been recorded by Geoffrey Hinton as a set of about 5 short videos. If you are registered for the class, you will be able to view these videos on the Coursera website. Details of how to do this will be given in the first lecture period. Each lecture period will consist of a class discussion of the content of the videos for that lecture, so you must watch the videos before the corresponding lecture period.

Lectures: Tuesdays and Thursdays 1.00-2.00pm in BA 1200
First lecture January 8; Last lecture April 4; No lectures on February 19 and 21
Click on the lectures page for a list of all the lectures (subject to change).

Tutorials: Thursdays 12.00-1.00pm (also in BA 1200)
Click on the tutorial page for details of the tutorials
Instructor: Tijmen Tieleman; email csc321prof[at sign]cs.toronto.edu
Office Hours: Tuesdays 2.10 - 3.30 for individual meetings (Pratt ??)

Teaching Assistants
TBA : email csc321a[at sign]cs.toronto.edu, (for the Assignments)
Office hours: Friday 2.00-4.00 (Pratt TBA)
TBA : email csc321na[at sign]cs.toronto.edu, (for things Not about the Assignments)
Office hours: Thurday 3.00-4.00 (Pratt TBA)

Please do NOT send the instructor or tutors email about the class directly to their personal accounts. They will not answer.

Prerequisites: If you want a waiver, you MUST contact Geoffrey Hinton in the first week
The prerequisites that will be enforced are:
(MAT135H1, MAT136H1)/MAT135Y1/MAT137Y1/MAT157Y1;
MAT223H1/MAT240H1;
STA247H1/STA255H1/STA257H1;
CGPA 3.0/enrollment in a CSC subject POSt

Load: 25 hours of lectures; 10 hours of Tutorials.

Required Readings: There is no required textbook for the class.
There will be one or two required papers or chapters per week. (see Lectures, Readings, & Due Dates). These required readings will all be available on the web.

Marking Scheme
Weekly Quizzes worth 15% Closed book Midterm test worth 15% (in same room as lectures)
Closed book Final exam worth 30% (See lectures page for time and place)
Four assignments worth 10% each

Computing
The assignments will all be done in Matlab, but prior knowledge of Matlab is not required. Basic Matlab will be taught during the first few tutorials.

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.

CSC321 - Computation In Neural Networks: || www.cs.toronto.edu/~hinton/csc321/

CSC321 Spring 2013 Introduction to Neural Networks and Machine Learning

CSC321 Spring 2013
Introduction to Neural Networks and Machine Learning