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4255. Introduction to Statistical Learning
3.00 credits
Prerequisites: STAT 3115Q or 3215Q or instructor consent. Recommended preparation: Background in computer programming is preferred, but not required.
Grading Basis: Graded
Modern statistical learning methods arising frequently in data science and machine learning with real-world applications: linear and logistic regression, generalized additive models, decision trees, boosting, support vector machines, and neural networks (deep learning).
Last Refreshed: 24-APR-24 05.20.12.452237 AM
| Term | Campus | Instruction Mode | Instructor | Section | Session | Schedule | Location | Enrollment | Notes | |
|---|---|---|---|---|---|---|---|---|---|---|
| 1248 8785 1 001 | Fall 2024 | Storrs | In Person | Gu, Yuwen | 001 | Reg | TuTh 11:00am‑12:15pm |
AUST 163 | 29/40 |