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
That being said, it is definitely cool to have a Jupyter-notebook based set of examples of practical linear algebra
One of the challenges of learning Linear Algebra is where to start. Most textbooks start with vector arithmetic, which make senses if you are working with paper and pencil, but they take a long time to get to something useful.
With a computational approach, we have the option to proceed top-down -- that is, we can start with libraries that implement the core algorithms of linear algebra, and wait until later to see how they work. With this approach we can can get to the good stuff faster.I would have benefited from some more handwaving in this regard (matrix multiplication, eigenvectors and eigenvalues) and less on the mechanics of the operations, before starting on the basic technicalities. But a “lesson” on these topics on day 0 is too soon
Strang can be great as a first book. He focuses more on what rather than why, so if one wants to delve deeper, it needs to be supplemented by a few other books.
For the long term his emphasis on operators is probably better as naturally transitions into functional analysis, but you can get a lot of stuff done without ever touching them.
That said, Jordan form is uglier than spectral decomposition, to my taste that is. Spectral decomposition so beautiful and neat.