Lectures related to Tensors: Motivations and Introduction

Covers the Singular Value Decomposition (SVD) in detail, including properties of matrices and system linearity.

Introduces special and general relativity, Einstein equations, and gravitational dynamics.

Explores the transformation of vectors and tensors, including rotations and representations in quantum physics.

Covers the concept of tensor product in the context of bilinear maps and explores the uniqueness of tensor products.

Explores the transformation of vectors and tensors in quantum physics, emphasizing Lie groups and algebras.

Covers the representations of SU(2) and their transformations in quantum mechanics.

Explores eigenvalues and eigenvectors in 3D linear algebra, covering characteristic polynomials, stability under transformations, and real roots.

Introduces multilinear forms in linear algebra, emphasizing clarity and logic in presentation.