University of Wisconsin-Madison 3 credits E C E
Mathematical foundations of machine learning theory and algorithms. Probabilistic, algebraic, and geometric models and representations of data, mathematical analysis of state-of-the-art learning algorithms and optimization methods, and applications of machine learning. Knowledge of probability [such as MATH/STAT 431 or COMP SCI/E C E 561] and linear algebra [such as MATH 341 or M E/COMP SCI/E C E 532] is required.
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