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Dec 12, 2024
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CS 5780 - Introduction to Machine Learning
Fall, Spring. 4 credits. Student option grading.
Prerequisite: probability theory (e.g. BTRY 3080 , ECON 3130 , MATH 4710 , ENGRD 2700 ) and linear algebra (e.g. MATH 2940 ) and calculus (e.g. MATH 1920 ) and programming proficiency (e.g. CS 2110 ). Co-meets with CS 4780 .
Fall: A. Damle, K. Weinberger; Spring: C. De Sa.
The course provides an introduction to machine learning, focusing on supervised learning and its theoretical foundations. Topics include regularized linear models, boosting, kernels, deep networks, generative models, online learning, and ethical questions arising in ML applications.
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