Prerequisites: MATH 010A, MATH 031 or EE 020B; STAT 155 or EE 114; CS 100 or CS 120B or EE 120B
Description: Introduces formalisms and methods in data mining and machine learning. Topics include data representation, supervised learning, and classification. Covers regression and clustering. Also covers rule learning, function approximation, and margin- based methods.
Cross-listing: Cross-listed with EE 142.