Mathematical Methods in Data Science III

4 credits

This is the third course in the sequence for mathematical methods in data science. Topics include non-linear signal processing, compressed sensing and its extensions, phase retrieval, blind deconvolution, neural networks, non-convex optimization, and optimal transport distances. Some scientific programming experience is recommended. Prerequisites: MATH 216B. Students who have not completed MATH 216B may enroll with consent of instructor.