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CSE 4820: Introduction to Machine Learning
An introduction to the basic tools and techniques of machine learning, including models for both supervised and unsupervised learning, related optimization techniques, and methods for model validation. Topics include linear and logistic regression, SVM classification and regression, kernels, regularization, clustering, and on-line algorithms for regret minimization.
- Credits
- 3
- Offered
- Spring 2027, Fall 2026
- Campuses
- Storrs, Stamford
- Requirements
- MATH 2210Q; STAT 3025Q or STAT 3345Q or STAT 3375Q or MATH 3160; open only to junior or higher students in the College of Engineering. Recommended preparation: CSE 3500.
Spring 2027 sections
Taught by Suining He, Jinbo Bi, and Ellie Sherafat.
| Section | Type | Meets | Instructor | Campus | Room | Seats |
|---|---|---|---|---|---|---|
| 001 | LEC | 12:30PM - 1:45PM / MoWe | Suining He | Storrs | MCHU 301 | 9 of 45 open |
| 002 | LEC | 12:30PM - 1:45PM / TuTh | Jinbo Bi | Storrs | MCHU 305 | 0 of 40 open |
| 801 | LEC | 3:30PM - 4:45PM / TuTh | Ellie Sherafat | Stamford | DWTN 3117 | 27 of 30 open |
Seats as of Nov 12, 2026. HuskyScheduler shows live seats when you search.
Fall 2026 sections
Taught by Jonathan Ji and Jinbo Bi.
| Section | Type | Meets | Instructor | Campus | Room | Seats |
|---|---|---|---|---|---|---|
| 001 | LEC | 12:30PM - 1:45PM / TuTh | Jonathan Ji | Storrs | MCHU 302 | 1 of 43 open |
| 002 | LEC | 2:00PM - 3:15PM / TuTh | Jinbo Bi | Storrs | ITE 336 | 3 of 35 open |
Seats as of Nov 12, 2026. HuskyScheduler shows live seats when you search.
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