COMP 343: Machine Learning
Spring 2022
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Course info

  • Professor: Victoria Manfredi, vumanfredi [at], Exley 627, 860-685-2194

  • Lectures: Mon and Wed, 1:20-2:40p, Exley 137

  • In-person office hours (in my office): Mon 3-4:30p, Tu 4:30-6p, Wed 4-5:30p, and by appointment.

  • Virtual office hours (on Zoom): Email me to set-up a time to meet, sometime within my in-person office hours if possible.

  • Announcements and online discussion: We'll use Google Classroom. I will add you, but you should double-check that you've been added and receive announcements, etc.

  • Course assistants: Dylan Abramson, Oliver Diamond, Nick Franczak, Phil Kaelbling,                                  Theodore Sternlieb, Cisco Vielma, Ammie Wang, Jiner Zheng

  • In-person help sessions: Su 7-9p, Mo 7-9p, Tu 7-9p, Exley 638

  • Virtual help sessions: Mo 7-9p, Tu 7-9p. The link for these will be announced via Google Classroom and held on Zoom.


This course provides an introduction to the field of machine learning: the first half of the course will focus on specific regression and classification techniques while the second half of the course will focus on deep neural networks.


This class has COMP 211, COMP 212, and MATH 228 as pre-requisites. We will cover concepts from probability and linear algebra as needed to ensure the course is self-contained. Programming will be done in python.


Your grade will be based on approximately 9 homework assignments (60%), a midterm exam (20%) and a final project (20%). Assignments will be posted on the schedule. All work must be submitted electronically. I will email you your grades periodically to double-check that the information that I have is consistent with what you have. It is your responsibility to check your grades and feedback and report any issues promptly. It is always possible for mistakes to happen in recording scores, especially in larger classes. If I do not hear about a problem, it will not be fixed.