The author of the Airfoil article has made several similar tutorials on various topics:

https://ciechanow.ski/archives/

For machine learning, Distill.pub has some excellent hands-on tutorials. For example, here's one on momentum:

https://distill.pub/2017/momentum/

Octave has not implemented all of Matlab's functionality. You can see a list of Matlab functions that have not yet been implemented in Octave at the link below. It's a long list.

https://hg.savannah.gnu.org/hgweb/octave/file/tip/scripts/he...

EDIT: If the original link above isn't working, here's a fairly recent archived version:

https://web.archive.org/web/20250123192851/https://hg.savann...

Matlab is an great tool, if you can afford it.

It was a very unpleasant feeling when I graduated from my PhD and realized that most, if not all, of the Matlab scripts I had used for my research would now be useless to me unless I joined a company or national laboratory that paid for licenses with the specific toolboxes I had used.

I'm glad that a significant portion of tools in my current field are in open source languages such as Python and Julia. It widens access to other researchers who can then build upon it.

(And yes, I'm aware of Octave. It does not have the capabilities of Matlab in the areas that I worked in, and was not able to run all of my PhD scripts. I have not tried RunMat yet, but am looking forward to experimenting with it.)