This is the home page for the course CS 295: Machine Learning in which we will cover supervised and unsupervised learning algorithms, reinforcement learning, and some of the mathematical theory that underlies machine learning.
Prerequisites: A introductory course in probability (e.g., STAT 151 or 153), and linear algebra (MATH 124). Multivariate calculus (Math 121) is highly recommended.