COS 302 - Mathematics for Numerical Computing and Machine Learning

Fall 2020

Course home Outline and Lectures Assignments



You must use LaTeX for your assignments, and we recommend working in the browser using Overleaf. The Overleaf template for each assignment will be provided. You must submit each assignment on Gradescope, via the provided links. Here are some screencasts to get you started:

Due dates, late assignments, and grading

All assignments are due at 12:00 noon, Eastern time, on the due date. Assignments will only be accepted up to 24 hours late, at a 10% penalty. The lowest assignment grade will be dropped.

Note that you will have two weeks to complete each assignment, but assignments will be handed out weekly. So, we very strongly encourage you not to wait until the last moment to complete your assignments. Most of the office hours are late in the week, so your best strategy is probably to try to have assignments mostly completed by the Thursday or Friday before the Monday due date.

Collaboration policy

You may discuss high-level concepts with others, but everything handed in must be your own work. All code and writeups must be your own - you may not use code or solutions from your classmates, the internet, or any other source. You are explicitly permitted (and expected) to use material from the textbook, lecture videos, precepts, and the online documentation for Python, NumPy, SciPy, Matplotlib, LaTeX, Overleaf, etc. You must acknowledge in your writeup everyone with whom you discussed the assignments, as well as any sources you used that are not among those listed above.

Last update 11-Nov-2020 10:48:10
smr at princeton edu