That book is about NumPy and not linear algebra. For actually learning linear algebra you need a math book, pen and paper.

NumPy is the worst way of abstracting linear algebra into a programming language. Octave is better in not obfuscating the concepts with OO boilerplate and having actually useful printed matrix output instead of ugly list representations. Even Fortran is better.

Of course, this is about Python and NumPy.

In practice, you'll often encounter the code before the underlying math (especially in Machine Learning), so developing intuition from both directions is always helpful.

Btw, if you enjoy pure mathematics, starting from Chapter 4 in the book, I begin defining vectors and the axioms of vector spaces:

https://little-book-of.github.io/linear-algebra/books/en-US/...

The best is of course Wolfram + the Mathematica libraries. You get full symbolic manipulation as well, so you can do abstract linear algebra as well.

hard disagree. octave and matlab (and maybe even r) are first and foremost calculator languages, not programming languages.

numpy is an intuitive way of doing those numerical calculations in a general use programming language. only minus is the missing gong and why commands

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