Description
This is an overview of linear algebra fundamentals which focuses on providing an intuitive / geometric review of some of the main concepts.
I was trying to find a readable overview presented in the same style as 3Blue1Brown's lectures on the essence of linear algebra, and didn't have much luck finding many, so this overview is my attempt at providing one.
It contains:
- A basic review of linear algebra fundamentals.
- Some of the important applications of linear algebra which includes an overview of how it can be used to model and solve systems of linear equations, as well as some examples showing how it's used in the real world.
This is by no means my own work, as I've taken my favourite review material and simply compiled it in what I believe is a more readable format. Full credit for all of the material goes to the content creators I've listed in the Credits section.
Credits
Full credit for the content goes to the authors of the works provided below:
- 3Blue1Brown's Essence of Linear Algebra Series
- The Mathematics of Quantum Mechanics
- Immersive Math Dot Product Chapter
- Math Insight Determinants and Linear Transformation Section
- Math Insights Cross Product Section
- Gilbret Strang's Linear Algebra Course Notes / Lectures
- NYU's Geometric Review of Linear Algebra
- Interactive Linear Algebra: The Method of Least Squares Section
- Computer Vision for Dummies: Eigenvectors and Eigenvalues Section
- Computer Vision for Dummies: Geometric Interpretation of the Covariance Matrix Section
- Stack Exchange: Making sense of principal component analysis, eigenvectors & eigenvalues post
- University of Cornell: PageRank Algorithm - The Mathematics of Google Search Lecture
- Kenneth Shum's PageRank Algorithm Paper/Notes
- The Nature of Code Neural Networks Chapter
- The Matrix Calculus You Need for Deep Learning Notes
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