Matrix Analysis and Linear Algebra for Data Science

Catalog description

Students will study a branch of mathematics called linear algebra, which is the foundation of advanced data mining techniques such as principal component analysis, support vector machines, and regression. Topics will include vector spaces, eigenvalues and eigenvectors, and the singular value decomposition. Special emphasis will be placed on applications such as network analysis, dimension reduction, and data clustering, and will involve interactive programming exercises.