4820. Introduction to Machine Learning
3.00 credits
Prerequisites: MATH 2210Q; STAT 3025Q or STAT 3345Q or STAT 3375Q or MATH 3160; open only to junior or higher students in the College of Engineering. Recommended preparation: CSE 3500.
Grading Basis: Graded
An introduction to the basic tools and techniques of machine learning, including models for both supervised and unsupervised learning, related optimization techniques, and methods for model validation. Topics include linear and logistic regression, SVM classification and regression, kernels, regularization, clustering, and on-line algorithms for regret minimization.
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