Matrices and Vector Spaces

3 credits · Graduate

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.