MATH 161A: MATHEMATICAL FOUNDATIONS OF MACHINE LEARNING

University of California, Riverside

4 Units, Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): MATH 010A with a grade of C- or better; MATH 031 with a grade of C- or better; or equivalent; or consent of instructor. Introduction to mathematical and computational concepts in machine learning methods with emphasis on developing new machine learning algorithms. Topics include linear algebra and vector calculus in application to supervised learning, regression, classification, unsupervised learning, clustering, and dimensionality reduction. Topics also include optimization and probability theory used in machine learning algorithms.