I work as a data engineer, and i was interested in learning some of the stuff our data scientists do so i can better communicate with them. Teaching myself some statistics was fine, probability was fine too and quite fun and surprising. Both subjects have plenty of books that allow you to understand the intuition behind the things they do without having to dive deep into the proofs. Linear algebra was and still is a struggle though. I've sampled many books, from Strang's book to Linear Algebra Done Wrong/Right to some books that are used in the local university in CS courses. But they are all the same. It's clear they are all written by mathematicians for math students, probably to be used as a way to teach students how to write proofs at the same time? It's just one page after another of increasingly esoteric calculations and proof after proof after proof. Which is fine if you study math, but bad for me, because i dont want to work out the proof that taking the determinant of an inverted matrix works, i want to know what it means and why one would want to make the effort to do it.

Basically, i want a book like Statistical Rethinking or Blitzstein's Introduction to Probaiblity, but for linear algebra. And i havent been able to find it.