Assignments

Due dates

• All assignments will be due on Tuesdays or Thursdaysat the end of class.

• Assignments will be posted on this web page one week before they are due.

Marking scheme and lateness penalties

• Each of the 4 assignments will be worth 10% of the final grade.

• Except in the case of an official Student Medical Certificate, assignments that are submitted late will be graded out of 7, 5, or 0 depending on whether they are 1, 2, or more days late. The time past the 2.00 pm deadline will be rounded UP to an integer number of days.

Collaboration Policy for Assignments

• You are expected to work on the assignments by yourself. You should not discuss them with anyone except the tutors or the instructor. The report you hand in should be entirely your own work and you may be asked to demonstrate how you got any results that you report.

What will be in the assignments

• A typical assignment will require you to write (or modify) and use some Matlab code that implements a simple version of a learning procedure that has recently been covered in the course. You will have to submit a very brief report (one page plus figures) that describes the results you obtained.

• Assignment 1 will involve using the backpropagation algorithm to learn distributed representations of words.
  

• Assignment 2 will involve using variations of the basic backpropagation algorithm

• Assignment 3 will involve learning a mixture of Gaussians.

• Assignment 4 will involve learning a Restricted Boltzmann Machine and using it to improve backpropagation.

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