Prerequisites: MATH 010A with a grade of C- or better, MATH 031 with a grade of C- or better; or equivalent; or consent of instructor
Description: Introduction to mathematical concepts in machine learning methods emphasizing the theoretical tools needed for developing new machine learning algorithms. Topics include linear algebra and vector calculus in application to supervised learning, regression, classification, unsupervised learning, clustering, dimensionality reduction and optimization, and probability theory used in machine learning algorithms.