Matrix Methods for Machine Learning

1 Unit · Undergraduate

A second course on linear algebra with emphasis on methods applicable to machine learning. Spectral theory, matrix factorizations, singular value decomposition, principal component analysis. Spectral methods for graphs, including graph Laplacians and clustering techniques.