While working on a project for a class on deep learning, I was looking for a way to differentiate functions of a matrix and I stumbled upon the book ‘Matrix Differential Calculus with Applications in Statistics and Econometrics’ by Jan R. Magnus and Heinz Neudecker. I found the book to be very well written and I wanted to share some of the key concepts I learned from it.

While writing the previous article for this blog, I realised that I did not have an easy way to retrieve code snippets (entire files or just some sections) from GitHub. I needed something that would allow me to retrieve the code from an external source without having to copy and paste it into the post.

This summer, I am trying to teach myself Rust, and I thought it would be a good idea to start by implementing a basic linear regression model. In this post we will briefly go over the theory behind linear regression, then we will see how to implement it in Rust.