Linear Algebra Bootcamp

Welcome to the Linear Algebra Bootcamp! 🚀

This chapter reviews the essential concepts of linear algebra used in fields from data science to quantum mechanics. We’ll start with a quick tour of vector spaces, norms, and dot products before moving on to matrices and their structure.

We’ll explore the four fundamental subspaces of a matrix, then introduce two key tools: the eigendecomposition, which helps explain how linear systems evolve, and the singular value decomposition (SVD), which reveals the geometry of linear transformations.

Whether you need a quick refresher or are building your foundation, this bootcamp will help you prepare for numerical linear algebra. Let’s get started!