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Prerequisites: MATH 2210Q; STAT 3025 or 3345 or 3375 or MATH 3160; open only to Computer Science and Engineering majors; juniors or higher. 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.
Last Refreshed: 06-MAY-21 05.20.19.123041 AM
|1218 12603 1 001||Fall 2021||Storrs||In Person||He, Suining||001||Reg||TuTh 5:00pm‑6:15pm