This repository contains a series of Jupyter Notebooks that progressively walk through the fundamentals of linear algebra. The guides aren't exhaustive introductions to all the concepts and theory behind linear algebra. While I certainly don't shy away from theory where it's helpful, I try to avoid the guides appearing too academic in nature. In support of that, I provide a fair number of examples and try to help establish the intuition behind the concepts. Additionally, the concepts are accompanied by an implementation in Python. The code is certainly not meant to replace industrial standards like NumPy or Pandas, but rather serve as another teaching tool.
- Introduction
- Vectors
- Linear Systems
- Matrices
- Solving Systems of Linear Equations
More to be added soon.
I'm open to feedback, so please don't hesitate to reach out if there is something that is confusing, could be expanded on, or is flat out wrong. Errata can be managed by creating Github issues or by sending them to bryan@bryan.blog.