Lectures related to Tutorial On Auto-encoders

Covers linear applications, diagonalizable matrices, eigenvectors, and orthogonal subspaces in R^n.

Explores the associated matrix of a linear map, basis formation, and space relationships.

Explains row-echelon and reduced row-echelon matrices and their role in simplifying system resolution.

Covers the diagonalization of linear transformations in R^3, exploring properties and examples.

Covers the general solution of inhomogeneous differential equations and explores linear dependence, uniqueness theorems, and second-order equations.

Explores basis transformation, eigenvalues, and linear operators in inner product spaces, emphasizing their significance in Quantum Mechanics.

Covers changing bases in vector spaces using matrices and the concept of dimension.