Think Linear Algebra (2023) (opens in new tab)

Allen Downey (author of the above) has a number of books on computer science-y things. You can buy hardcopies but I think all of them are also just freely available.

Here's a few:

Think Complexity

https://github.com/AllenDowney/ThinkComplexity2

Think DSP

https://github.com/AllenDowney/ThinkDSP

Think Stats

https://github.com/AllenDowney/ThinkStats/

Think Bayes

https://github.com/AllenDowney/ThinkBayes2/

Matrix multiplication introduced before vector addition... the "Linear Algebra Done Right" in me is screaming inside.

That being said, it is definitely cool to have a Jupyter-notebook based set of examples of practical linear algebra

I saw a linear algebra “textbook” on Twitter in maybe 2022? It was black background and bright text with a good amount of graphs like someone’s incredibly long blog post. I’ve tried a few times to find it since but haven’t had any luck.

This looks a bit more involved but lovely I think I’ll try it. I read Think Bayes and thought it was great.

Beyond regression, I’d like to see chapters on statistical topics like PCA, CCA. This textbook format which interleaves code and prose is the perfect way to show how scikitlearn’s decomposition.cca and decomposition.pca are implemented, e.g. the SVD matrix decomposition, etc.

what's the deal with the loop example? am i supposed to understand what this represents before going through the material?

Linear Algebra is dope, as in when we got to apply some mid-level linear to a real business problem and it worked i got high

Klong shines there:

https://www.t3x.org/klong/

Quick ref:

https://www.t3x.org/klong/klong-qref.txt.html

Intro:

https://www.t3x.org/klong/klong-intro.txt.html

Klong for K users:

https://www.t3x.org/klong/klong-vs-k.txt.html

I got my hands on a stanford Math 55 textbook and tried to do the exercises in numpy.