1. Singular Value Decomposition (SVD) is an important part of machine learning algorithms and this article goes through the mechanics of SVD in a tutorial format. Download the article here.

A Powerpoint presentation can be accessed here.

2. The theory of matrix exponentiation is covered in linear ordinary differential equations courses usually. If you want some practice at how the theory works, there are several problems in the Cambridge Tripos Part 1A exam from 30 May 2019 which may be of interest. Full solutions can be found here.

3. The Gram-Schmidt orthogonalization process is an important tool in linear algebra and much more. It is based on a recursive process which can be visualised in 2 and 3 dimensions and inductively extended to n dimensions. To learn more about why it works read this article.