Came across this <https://github.com/mitmath/julia-mit> repo, which is
an intro to the Julia language. Apparently this is increasingly being
used in place of MATLAB in numerical-computation courses at MIT.

Why not Python? Because it is fine as long as you can use existing
computational kernels, but as soon as you need custom ones, it gets
slow if you do them in Python, or requires special skills to write them
in C or Fortran, and make them callable from Python. Julia
incorporates a ���just-in-time��� compiler using LLVM to achieve speed
close to that of C in this case.

Why not MATLAB? Because it is proprietary:

�� �� Unlike Matlab, [Julia] is free/open-source software, which
�� �� eliminates licensing headaches and allows you to look inside the
�� �� Julia implementation to see how it works (since Julia is mostly
�� �� written in Julia, its code is much more readable than a language
�� �� like Python that is largely implemented in low-level C).

They do like using Julia in Jupyter notebooks. I see a few .ipynb files
in the repos for other courses (along with a few .pptx ones as well,
unfortunately). Also several ���.jmd��� files, which look like some variety
of markdown.
_______________________________________________
wlug mailing list -- wlug@list.waikato.ac.nz | To unsubscribe send an email to wlug-leave@list.waikato.ac.nz
Unsubscribe: https://list.waikato.ac.nz/postorius/lists/wlug.list.waikato.ac.nz