Linear Algebra for Data Science

Catalog description

Linear algebra with applications to core machine learning algorithms. Topics include vector spaces, subspaces, basis, and dimension, matrix operations, eigenvalue and eigenvector analysis, conditioning of matrix operations, singular value decomposition, generalized inverses.