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.

Course Website

Course Website 

Current Time Schedule

Winter, 2023

SLN/Section Time Location Instructor
20797 A
Open

T Th 10:00AM - 11:20AM

T Th 10:00AM - 11:20AM

CSE2 G10

CSE2 G10

Tim Althoff

Yikun Zhang

 

 

20798 B
Open

T Th 10:00AM - 11:20AM

CSE2 G10

Tim Althoff

GRAD ONLY, STAT MAJORS ONLY