Topics: statistical pattern recognition, linear and non-linear regression, non-parametric methods, exponential family, GLMs, support vector machines, kernel methods, model/feature selection, learning theory, VC dimension, clustering, density estimation, EM, dimensionality reduction, ICA, PCA, reinforcement learning and adaptive control, Markov decision processes, approximate dynamic programming, and policy search. Prerequisites: linear algebra, and basic probability and statistics.
Limited Enrollment Details: CS 229 (and STATS 229) are not open to High School Summer College or Horizon Scholar students. For a list of available Computer Science courses, please select "High School" or "Horizon Scholar" in the Student Population section of the Course page.
Linear Algebra and Basic Probability and Statistics.