Tutorial 1 : Introduction to Python Basics

Lec 34 Statistical Mechanics

Lec 55 Spectral Theorem, Quadratic Forms

Lec 54 Effect of a real symmetric matrix - Geometric Interpretation

Lec 53 Eigenvalues and eigenvectors of real symmetric matrices

Lec 52 Real Symmetric matrix and properties

Lec 51 Eigensubspace and dimension

Lec 50 Eigendecomposition

Lec 48 Projection and Projection Matrices

Lec 49 Pseudoinverse of special matrices

Lec 47 Least squares solution, Pseudoinverse of A

Lec 46 System of linear equations with no solution - Inconsistent systems

Lec 45 Orientation of the four fundamental subspaces of a matrix A

Lec 43 Subspaces associated matrix A transpose, Nullity, Rank

Lec 44 Orthogonal Complement of a subspace

Lec 42 Column Space of A

Lec 41 Homogeneous system of linear equations and null space of a matrix

Lec 39 Combining vectors in a vector space, Linear Independence

Lec 40 Span, Basis, Dimension of a vector space, Fourier Expansion

Lec 37 Examples of vector spaces - Polynomial space, planes and lines through origin

Lec 38 Vector Subspaces and their geometry

Lec 36 Vector Space and Properties

Lec 35 Orthogonal Matrix, Linear Independence, eigenvalues and eigenvectors in 3D

Lec 34 Least Squares Solution, Gram-Schmidt Orthogonalization, QRDecomposition

Lec 33 LU Decomposition