# Linear Algebra

Linear algebra, the study of vectors and vector spaces, has many incredibly interesting applications including mathematical physics, modern algebra and coding theory. Unlike more vague and new fields of Mathematics, our understanding of linear algebra is pretty air tight; you can make really satisfying progress in this topic and won't find yourself feeling like you've got gaping holes in your knowledge. Wanting to go into AI, machine learning or computing? This is the one for you.

## Resources

### Textbooks

# No bullshit guide to linear algebra by Ivan Savov

Free

Linear Algebra Done Right by Sheldon Axler

Linear Algebra by Jim Hefferon (and answers to exercises)

### Videos

Intro to Linear Algebra Series by 3Blue1Brown - this is a several part series so make sure you go through the different videos in order!

Lectures:

The author of Linear Algebra Done Right made this INCREDIBLE video series to go along with the book - a great combo for anyone hoping for a good understanding of undergraduate Linear Algebra.

Linear Algebra Lecture Series by MIT

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### Online Courses

Mathematics for Machine Learning: Linear Algebra

Free

Introduction to Linear Models and Matrix Algebra (Probably one of the best available)

Linear Algebra I: Linear Equations (This is a series of collected course materials from an archived course)

Math for AI beginner part 1 Linear Algebra

Differential Equations: Linear Algebra and NxN Systems of Differential Equations (For more advanced mathematicians who have learned the basics of Linear Algrebra)