Lectures related to Zero matrix

Covers the LU decomposition algorithm, transforming a matrix into L and U.

Covers elementary matrices, their types, properties, and invertibility.

Covers matrix invertibility, determining if a matrix is invertible, calculating its inverse, and elementary matrices.

Delves into singular value decomposition and its applications in linear algebra.

Explores least squares in linear regression, hypothesis testing, outliers, and model assumptions.

Covers the ring structure, focusing on polynomials and coefficients, including associativity, distributivity, and the product of rings.

Covers the Singular Value Decomposition theorem and its applications in practice.

Covers elementary matrices, their properties, and the algorithm to find the inverse of a matrix.