MA 220

This is a course in mathematical methods used in data analysis, computation, and modelling. The topics include matrix algebra in Rn, eigenvalue problems, diagonalization and quadratic forms, least-squares solutions, selected numerical methods of linear algebra, singular value decomposition, principal component method and other applications in data analysis and statistical modelling. A part of the course is devoted to nonlinear multivariable optimization, and selected numerical methods, including gradient descent, are presented. <br>