18.065 - Matrix Methods in Data Analysis, Signal Processing, and Machine Learning (Spring 2017)

Class: Thurs 11:00 - 12:30

Location: 2-190

Instructor: Gilbert Strang

E-mail: gilstrang@gmail.com

Office: 2-245

Office Hours: before class & more

COURSE DESCRIPTION

Reviews linear algebra with applications to life sciences, finance, and big data. Covers singular value decomposition, weighted least squares, signal and image processing, principal component analysis, covariance and correlation matrices, directed and undirected graphs, matrix factorizations, neural nets, machine learning, and hidden Markov models.

Prerequisites: 18.06

Text Book: Introduction to Linear Algebra, by Gilbert Strang