ADVANCED LINEAR ALGEBRA.

Catalog description

Pre-requisites: MATH 225 and MATH 231 . This course further develops both the theory and applications of linear algebra. Topics include a survey of matrix factorizations, an introduction to inner product spaces, and analysis of applications, such as, Markov chains, least squares regression, principal component analysis, and gradient descents. This course also investigates how core concepts from linear algebra apply to modern techniques in data analysis, such as, image processing, machine learning, deep learning, and neural networks.