CSE446: Machine Learning

Catalog Description: Design of efficient algorithms that learn from data. Representative topics include supervised learning, unsupervised learning, regression and classification, deep learning, kernel methods, and optimization. Emphasis on algorithmic principles and how to use these tools in practice.

Prerequisites: CSE 332; MATH 208 or MATH 136; and either STAT 390, STAT 391, or CSE 312.
Credits: 4.0

---

Portions of the CSE446 web may be reprinted or adapted for academic nonprofit purposes, providing the source is accurately quoted and duly creditied. The CSE446 Web: © 1993-2024, Department of Computer Science and Engineering, Univerity of Washington. Administrative information on CSE446 (authentication required).