STAT 548

Machine Learning for Big Data
4.0 credits

Course Description

Covers machine learning and statistical techniques for analyzing datasets of massive size and dimensionality. Representations include regularized linear models, graphical models, matrix factorization, sparsity, clustering, and latent factor models. Algorithms include sketching, random projections, hashing, fast nearest-neighbors, large-scale online learning, and parallel learning (Map-Reduce, GraphLab). Prerequisite: either STAT 535 or CSE 546. Offered: jointly with CSE 547; W.

Upcoming Time Schedule

Spring, 2025

SLN/Section Time Location Instructor
20149 A
Open

M F 2:00PM - 3:20PM

MLR 301

 

 

20150 B
Open

M F 2:00PM - 3:20PM

MLR 301

COURSE JOINT WITH STAT 548A/CSE 547A. STAT MS FEE-BASED STUDENTS ONLY.