[s-zeng]

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

[rahimnathwani]

This is a deliberate pedagogical choice, and one which will familiar to those who did one of Jeremy Howard's deep learning courses.

  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.

[bsoles]

And eigenvectors in the first lesson!

[finghin]

I think at the beginning of learning LA I would have benefited from a more broad introduction to the topic by explaining that it is the algebra of transformations, generally linear transformations, and also the art of quantifying those transformations in meaningful ways.

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

[krackers]

Vector addition is just matrix multiplication in a homogeneous coordinate system, what's the problem?

[Pay08]

"The Fibonacci sequence is just addition of specific numbers, what's the problem?"

[krackers]

Funnily enough Fibonacci sequence is also matrix multiplication

[victor106]

What would you suggest as a complimentary resource to this?

[isomorphic]

I think GP is both referring to and suggesting:

https://linear.axler.net/

[srean]

This is a great book but and as the author himself notes, it's not an ideal first linear algebra book.

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.

[mamonster]

I still don't get why Axler decided to discuss the Jordan normal form after already doing the spectral theorem, it's a bit like presenting Riemannian integration after Lebesgue.

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.

[KalMann]

Did you misstate your comment? The Jordan normal form is more general than spectral decomposition so it should come after.

[mamonster]

I'm open to being corrected, but AFAIK the normal form (1870) precedes the official focus on operators (with Hilbert) by like 20-30 years.

[Koshkin]

Also: https://lew98.github.io/Mathematics/LADR_Solutions/LADR_Solu...