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