Fall 2023 Course Descriptions

CS 135-01 Introduction to Machine Learning

M. Hughes
TR 10:30-11:45, Room To Be Announced
D+ Block

An overview of methods whereby computers can learn from data or experience and make decisions accordingly. Topics include supervised learning, unsupervised learning, reinforcement learning, and knowledge extraction from large databases with applications to science, engineering, and medicine.

Prerequisite: Comp 15 and COMP/MATH 22 or 61 or consent of instructor. (Comp 160 is highly recommended).

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