Assignment Submission Instructions
Neural Networks and Deep Learning
- You may work either individually or in a group of two
(i.e., with one other person). Our grading standards will be
a bit more stringent if you're working in a group.
- The assignment will give you specific questions to answer,
many of which will involve running simulations.
- We ask you to submit a hardcopy of your writeup (but not
code) in class on the due date.
- We also ask you to upload your writeup and any code on
CU's Desire2Learn system (instructions below).
- If you are working in a group, please hand in only one
hardcopy for the group, but each of you should upload to
- Be sure to write your full name on the hardcopy writeup.
- I'm not proud to tell you this, but from 30 years of
grading assignments, I have to warn you that professors and
TAs have a negative predisposition toward handprinted work.
It is much easier to read and grade responses that are typed
and have been spell corrected. And you will want to format
your work because you'll be inserting Figures and/or
- The homework assignment will be divided into specific
questions that will have labels (numbers, headings, or
whatever). Please use these labels in your writeup to make
it easier for us to parse.
- We ordinarily will not look at your code, unless there
appears to be a bug or other problem. If we ask you
questions concerning your implementation strategy, you
should try to make your answers as self contained as
Submit all assignments via CU's Desire2Learn
Submission instructions are as follows:
- Go to Desire2learn
site and enter identikey and
password, or access through mycuinfo
- Once on the desire2learn web
site, select CSCI 5922-001
- Select the "assessments" tab on the yellow bar
- Select "dropbox" from the
drop down menu
- Select "homework X" for assignment # X and
then upload the file containing your writeup and code.
Both Mike and Denis are eager to help folks
who are stuck or require clarification. For any clarification of
the assignment, what we're expecting, and how to implement, we
would appreciate it if you posted your question on piazza. In
fact, post on piazza unless your question is personal or you
believe it is specific to you. If you have the question,
it's likely others will have the same question. And if we give
you a clue, then we'll give the same clue to everyone else. If
you have python or tensorflow questions, definitely post to
piazza as other participants in the course are likely to have
It is fine to ask other students in the class for general advice
and clarification, but we would like for you (or you and your
partner) to do your own work, and we would like to know if
you're having problems.
The bottom of the course syllabus has a long
blurb about academic honesty and the CU honor code.