Computational Linear Algebra

Catalog description

A course in the techniques and applications of linear algebra in the field of data science. The core topics include solving systems of linear equations, eigenvalues and eigenvectors, matrix decomposition, the pseudoinverse and least squares approximations, and the singular value decomposition. Theory is supplemented with extensive applications and computer programming.