|
..
|
|
Lecture 01 - Systems of linear equations, vectors, matrices, Gauss Elimination and LU-factorization.pdf
|
|
Lecture 02 - Pivots + Permutations, Matrix Inverses (Gauss-Jordan), Transposes, Symmetric Matrices, and General Linear Systems.pdf
|
|
Lecture 03 - Vector Spaces 1_ Definitions, Subspaces, Span, Linear Independence, Basis, and Dimension.pdf
|
|
Lecture 04 - The Fundamental Matrix Subspaces (Kernel, Image, CoKernel, CoImage), Fundamental Theorem of Linear Algebra, and a brief interlude on the Matrix Transpose.pdf
|
|
Lecture 05 - Inner products, length, angles, and norms.pdf
|
|
Lecture 06 - Clustering and K-means.pdf
|
|
Lecture 07 - Orthogonality, Gram-Schmidt, Orthogonal Matrices, and QR-Factorization.pdf
|
|
Lecture 08 - Orthogonal Projections and Subspaces, Least Squares Problems and Solutions.pdf
|
|
Lecture 09 - Least Squares Data Fitting.pdf
|
|
Lecture 10 - Linearity, Linear Functions, Transformations, and Operators.pdf
|
|
Lecture 11 - Eigvenvalues and Eigenvectors part 1 (dynamical systems, determinants, basic definitions and computations).pdf
|
|
Lecture 12 - Eigvenvalues and Eigenvectors part 2 (complex eigenvalues and eigenvectors, similarity transformation, diagonalization and eigenbases).pdf
|