Homogeneity: T(c * u) = c * T(u) for any scalar c and vector u. Additivity: T(u + v) = T(u) + T(v) for any vectors u and v. The range of a linear transformation T is the set of all vectors that can be ...

Abstract: This book contains a detailed discussion of the matrix operation, its properties, and its applications in finding the solution of linear equations and determinants. Linear algebra is a ...

These are some notes I've written to try to teach linear algebra and related aspects of linear differential equations to students of theoretical neuroscience. I've also included a nice set of notes ...

Vector spaces, linear transformation, matrix representation, inner product spaces, isometries, least squares, generalised inverse, eigen theory, quadratic forms, norms, numerical methods. The fourth ...

Abstract: This book contains a detailed discussion of the matrix operation, its properties, and its applications in finding the solution of linear equations and determinants. Linear algebra is a ...

This is a subject I struggled with the first time I took it. Ironically, this was the engineering version of it. It wasn't until I took the rigorous, axiomatic version that everything clicked.

A menu-driven image transformation tool implemented using linear algebra concepts and deployed as a web app using Streamlit. This tool allows you to apply common image processing operations like ...

This course aims to develop your knowledge in the mathematics topics of linear algebra and calculus, which provides the basic mathematics foundation that is necessary for anyone pursuing a computing ...