IE 434

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Credit: 3 OR 4 hours.

Mathematical foundations of deep learning and applications to topical examples. Understanding of mathematical formulations of building blocks of machine learning. Design of deep learning algorithms for practical applications. Examples will be drawn from real datasets, and implementations will involve PyTorch.

3 undergraduate hours. 4 graduate hours. Credit is not given for IE 434 and IE 534. Prerequisite: IE 300(or equivalent), MATH 231, MATH 257 or MATH 415, CS 101 or CS 124.

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