Matrix Methods in Data Analysis

Part I: Linear Algebra And Machine Learning.- Why Should We Care?.- What You May Have Learned Before..- Core Topics.- Supplementary Topics.- Part II: Matrix Multiplication And Partitioned Matrices.- Why Should We Care?.- What You May Have Learned Before.- Core Topics.- Supplementary Topics.- From The Classroom To Real Life.- Part III: Norms, Distances, And Similarities.- Why Should We Care?.- What You May Have Learned Before.- Core Topics.- Supplementary Topics.- From The Classroom To Real Life.- Part IV: The Four Fundamental Subspaces Of A Matrix, And Gram-Matrices.-  Why Should We Care? .- What You May Have Learned Before.- Core Topics.- Supplementary Topics.- From The Classroom To Real Life.- Part V: The Lu Factorization Of A Matrix.- Why Should We Care? .- What You May Have Learned Before.- Core Topics.- Supplementary Topics.- From The Classroom To Real Life.- Part VI: Orthogonality And The Qr Factorization.- Why Should We Care? .- What You May Have Learned Before.- Core Topics.- Supplementary Topics.- From The Classroom To Real Life.- Part VII: Orthogonal Projections And The Least Squares Problem.- Why Should We Care? .- What You May Have Learned Before.- Core Topics.- Supplementary Topics.- From The Classroom To Real Life.- Part VIII: Eigenvalues, Eigenvectors, And Algorithms.- Why Should We Care? .- What You May Have Learned Before.- Core Topics.- Supplementary Topics.- From The Classroom To Real Life.- Part IX: Symmetric And Positive Definite Matrices.- Why Should We Care? .- What You May Have Learned Before.- Core Topics.- Supplementary Topics.- From The Classroom To Real Life.- Part X: Singular Value Decomposition.- Why Should We Care? .- What You May Have Learned Before.- Core Topics.- Supplementary Topics.-From The Classroom To Real Life.- Part XI: Nonnegative Matrices And Perron Theory.- Why Should We Care? .- What You May Have Learned Before.- Core Topics.- Supplementary Topics.- From The Classroom To Real Life.- Index.