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

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

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