STAT 576 - Unsupervised Machine Learning

(3 units)

Prerequisite: STAT 510 or consent of instructor.
In-depth theory for unsupervised learning including clustering, recommendation, manifold learning, dimensionality reduction, autoencoders, generative models (generative adversarial networks/variational autoencoder), and semi-supervised learning. The choice of software (SAS, Enterprise Miner, R, and/or Python) is at the instructor’s discretion.

Letter grade only (A-F). (Lecture 3 hours).