DSC 391L DSC 391L. Principles of Machine Learning. 3 Hours.
Examine computing systems that automatically improve their performance with experience, including various approaches to inductive classification such as version space, decision tree, rule-based, neural network, Bayesian, and instance-based methods; as well as computational learning theory, explanation-based learning, and knowledge refinement. The equivalent of three lecture hours a week for one semester. Data Science 391L and Computer Science 391L may not both be counted. Offered on the letter-grade basis only. Prerequisite: Graduate standing and Data Science 382.