Matrices and Vector Spaces

Catalog description

Solving systems of linear equations, matrix factorizations and fundamental vector subspaces, orthogonality, least squares problems, eigenvalues and eigenvectors, the singular value decomposition and principal component analysis, applications to data-driven problems. An assignment will ask the student to relate this course to their research.