MATH 216B. Mathematical Methods in Data Science II (4 units)
Link to catalog page: https://catalog.ucsd.edu/courses/MATH.html#math216b
Description
This is the second course in a three-course sequence in mathematical methods in data science. Topics include analysis on graphs, random walks and diffusion geometry for uniform and non-uniform sampling, eigenvector perturbation, multi-scale analysis of data, concentration of measure phenomenon, binary embeddings, quantization, topic modeling, and geometric machine learning, as well as scientific applications. Some scientific programming experience is recommended. Prerequisites: MATH 216A. Students who have not completed MATH 216A may enroll with consent of instructor.
Prerequisite courses
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Successor courses
MATH 216B is a prerequisite of the following 1 courses: