The teaching and learning of linear algebra have evolved significantly over recent decades, underpinned by diverse approaches ranging from theoretical expositions to dynamic, model-based environments.

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

Last year, I started writing about my experiences taking courses on machine learning and artificial intelligence. One of the big, unexpected problems I ran into was calculus and linear algebra. I've ...

Want to understand how multivariate linear regression really works under the hood? In this video, we build it from scratch in C++—no machine learning libraries, just raw code and linear algebra. Ideal ...

In scientific computing, researchers build and use models based on established physical laws. Machine learning differs in ...

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 ...

Indian parents selecting barbers for their children meant the latter got haircuts that were so unattractive that they killed any prospect of youthful romance that could distract from studies It’s a ...

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 ...