CSE547: Machine Learning for Big Data
Catalog Description: 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 (Map-reduce, GraphLab). Prerequisite: either STAT 535 or CSE 546.Prerequisities: (none listed) Credits: 4.0
Portions of the CSE547 web may be reprinted or adapted for academic nonprofit purposes, providing the source is accurately quoted and duly creditied. The CSE547 Web: © 1993-2019, Department of Computer Science and Engineering, Univerity of Washington. Administrative information on CSE547 (authentication required).