STAT 548

Machine Learning for Big Data

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.

Current Time Schedule

Spring, 2024

SLN/Section Time Location Instructor
0
Open

 

 

20239 A
Open

T Th 10:00AM - 11:20AM

T Th 10:00AM - 11:20AM

CSE2 G01

CSE2 G01

Tim Althoff

Yikun Zhang

 

 

20240 B
Open

T Th 10:00AM - 11:20AM

CSE2 G01

Tim Althoff

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