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Lectures, Readings and Due Dates

Optional Readings

Tutorials

Computing

Assignments

Tests

 

 Anthony Bonner's Homepage:

www.cs.toronto.edu/~bonner

 

CSC321 Spring 2016
Introduction to Neural Networks and Machine Learning
University of Toronto Mississauga

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


Announcements:

The final exam and midterm will be based, in part, on the homework assignments and will assume that you have completed them by yourselves. More generally, you are responsible for all material covered in class, in tutorials, in the readings and on the assignments (except as described below). However, you will not be required to write any Matlab code, and you are not responsible for historical facts mentioned in class or on the slides (or anywhere else).


The final exam will have five questions. One question will be on lecture 11, one will be on lecture 12, and the remaining three will be from the rest of the course. There will be no questions on Lectures 7 and 15.


Like midterm test, the final exam will follow the "I don't know" policy: if you leave a question (or part) blank and write "I don't know", you will receive 20% of the marks for that question (pr part). Otherwise, if you get the answer wrong, you may receive 0 marks.


The final exam will be closed book. You may bring a 1-page double-sided cheat sheet on Letter-size (8.5x11in) paper with no more than 12,000 characters (6,000 per side). If typed, it must be in 12pt font or larger. No other aids are allowed.


Assignment 4 is now available. It is due on Friday April 1 at 11pm.

The slides for Lecture 14 have been updated.
Lecture 13 has been replaced by Lecture 14.
Assignment 3 is now available on the Assignments page.
For the midterm, you will be responsible for all material covered in class, the homework assignments and the tutorials up until February 25 (except for the lecture on clustering and mixtures of Gaussians). You will not be responsible for historical facts mentioned in class or on the lecture slides (or anywhere else), and you will not be required to write any Matlab code.
Broken links to lecture slides have been fixed.

Some slides have been added to the lecture on Clustering (right after Lecture 10).
The midterm test will follow the "I don't know" policy: if you leave a question (or part) blank and write "I don't know", you will receive 20% of the marks for that question (or part). Otherwise, if you get the answer wrong, you may receive 0 marks.
Marked Assignment 1s are now available on UTORSubmit.
Assignment 2 is now available (see the Assignments page).

The midterm test will be on Friday February 26 in tutorial. It will start at 1:10pm sharp and will last 50 minutes.
The midterm test will be closed book. You may bring a 1-page single-sided cheat sheet on Letter-size (8.5x11in) paper with no more than 6000 characters. If typed, it must be in 12pt font or larger.

Lectures 7, 9 and 10 have been reordered. (Lecture 7 now comes after Lectures 9 and 10.)
Assignment 1 is now a available (see the Assignments page).
Readings have been added to the lecture schedule.

The first tutorial will be on Frday January 15.


Course Information sheet: click here.

Lectures:  Wednesdays 3-5pm in IB 335
First lecture January 6; Last lecture March 30; No lecture on February 17 (reading week)
Click here for a list of all the lectures (subject to change).

Tutorials:

Fridays 1-2pm in CC 2130

First tutorial:  January 15
Click here for more tutorial information.

Instructor:   Anthony Bonner
email:  [my last name] [at] cs [dot] toronto [dot] edu
Office:  DH 3090 (UTM),  BA 4268 (St George)
Phone:  905-828-3813 (UTM),  416-978-7441 (St George)
Office Hours:  Wednesdays 5-6pm

Teaching Assistant:  Hamed Heydari
email:  h [dot] heydari [at] mail [dot] utoronto [dot] ca

Prerequisites:
informally:  calculus, linear algebra, statistics and computer programming
formally:  CSC207H5/270H5, 290H5; MAT223H5/248Y5; STA257H5

Marking Scheme:
Closed book Midterm test worth 20%
Closed book Final exam worth 40%
Four assignments worth 10% each

On all work, 20% of the mark will be for quality of presentation, including the use of good English. The final exam and midterm will be based in part on the assignments and will assume that you have completed them by yourself. Final marks may be adjusted up or down to conform with University of Toronto grading policies. Late assignments will not be accepted.

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 tutorials.

Readings: There is no required textbook for the class. There will be occasional required readings which will be made available on the web (see Lectures and Readings). You may also find the following books and resources useful:

Plagiarism and Cheating:
Honesty and fairness are fundmental to the Univrrsity of Toronto's mission. Plagiarism is a form of academic fraud and is treated very seriously. The work that you submit must be your own and cannot contain anyone else's work or ideas without proper attribution. You are expected to read the handout How Not to Plagiarize
and to be familiar with the Code of Behaviour on Academic Matters, which is linked from the UTM calendar under the link Codes and Policies. The following website may also be helpful: Advice on academic offences.