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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: 27-FEB-24 05.20.21.437592 AM
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Term Campus Instruction Mode Instructor Section Session Schedule Location Enrollment Notes
Fall 2024 Storrs In Person Gu, Yuwen 001 Reg TuTh 11:00am‑12:15pm
AUST 163 0/40