Linear algebra an optimization: An introduction -- Linear transformations and linear systems -- Eigenvectors and Diagonalizable matrices -- Optimization basics: A machine learning view -- Advanced optimization solutions -- Constrained optimization and duality -- Singular value decomposition -- Matrix factorization -- The linear algebra of similarity -- The linear algebra of graphs -- Optimization in computational graphs -- Bibliography.