STAT 538
Statistical Learning: Modeling, Prediction, and Computing
3.0 credits
Course Description
Reviews optimization and convex optimization in its relation to statistics. Covers the basics of unconstrained and constrained convex optimization, basics of clustering and classification, entropy, KL divergence and exponential family models, duality, modern learning algorithms like boosting, support vector machines, and variational approximations in inference. Prerequisite: experience with programming in a high level language. Offered: W.
Syllabus Downloads
Current Time Schedule
Winter, 2025
SLN/Section | Time | Location | Instructor |
---|---|---|---|
20777 A Open |
M W 9:00AM - 10:20AM |
PCAR 295 |
Armeen Taeb |
JOINT WITH STAT 538B.
|
|||
20778 B Open |
M W 9:00AM - 10:20AM |
PCAR 295 |
Armeen Taeb |
JOINT WITH STAT 538A. GRADS ONLY STAT MS FEE-BASED STUDENTS ONLY.
|