FSAN 815 - Analytics I: Statistical Learning (3cr.)

Credit(s): 3

ANALYTICS I:STATISICAL LEARNIN
Component: Lecture
Introduction to the mathematics of data analysis. Bayes estimation, linear regression and classification methods. The singular value decomposition and the pseudo-inverse. Statistical models for inference and prediction in finance, marketing, and engineering applications. Regularization methods and principles of sparsity priors are applied. Streaming solutions. High dimensional problems. Concepts reinforced in R programming experiments.
Repeatable for Credit: N Allowed Units: 3 Multiple Term Enrollment: N Grading Basis: Student Option
Crosslisted: Crosslisted with ELEG 815. PREREQ: First course in linear algebra. First course in probability and statistics (ELEG310 or equivalent). Basic programming skills.