Matrix theory provides a framework for representing and manipulating linear transformations across diverse scientific domains. Key properties include rank, invertibility and spectral characteristics ...

Linear algebra is rarely described as popular, but rarely does a mathematician portray it in a different, illuminating light. That is certainly one reason Gilbert Strang’s linear algebra lectures are ...

Slack for questions about the course and student - led discussions (See Canvas for link) Note about email: Email should be used only for personal/individual matters, and even then it is better to come ...

Understanding and implementation of algorithms to calculate matrix decompositions such as eigenvalue/vector, LU, QR, and SVD decompositions. Applications include data-fitting, image analysis, and ...

Most linear algebra courses start by considering how to solve a system of linear equations. \[ \begin{align} a_{0,0}x_0 + a_{0,1}x_0 + \cdots a_{0,n-1}x_0 & = b_0 ...

I'm planning my next semester and am wanting to take Linear Algebra and Differential equations and need to know if there is anything I need to brush up on for either class. A lot of my friends are ...

These pages provide a showcase of how to use Python to do computations from linear algebra. We will demonstrate both the NumPy (SciPy) and SymPy packages. This is meant to be a companion guide to a ...

Although linear algebra is regarded as a relatively modern mathematics topic, its ideas have been around for a long time. The first instance of the solution of a system of linear equations, using what ...