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DSC 391L DSCĀ 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.