Seeking advice on contributing to Julia: A faster Lasso solver

[Albert_Zevelev]

I copy and pasted these packages from a list I had prepared months ago when I was new to Julia & wanted to contribute to some of the ML packages.

There is a ton of great Julia stuff that is hard to discover.

Here is what I wrote about this in March:

@Albert_Zevelev

If I were searching for Julia repos on pdes, the following 6 are the ones I’d try:

1 #partial-differential-equations 15 repos: partial-differential-equations · GitHub Topics · GitHub
2 #pde 11 repos: https://github.com/topics/pde?l=julia
3 #pdes 2 repos: https://github.com/topics/pdes?l=julia
4 Observer: https://juliaobserver.com/searches?utf8=✓&term=pde
5 Filter by tag: https://pkg.julialang.org/docs/
6 Svaksha’s: GitHub - svaksha/Julia.jl: Curated decibans of Julia programming language.

Of course you wouldn’t discover repos that are not tagged or registered.
In none of these searches would you discover @jlchan’s repo on DG methods for pdes or several other nice repos in @PetrKryslUCSD’s survey.

The R community’s solution is CRAN Task Views, for example see Differential Equations.
Python is trying Python Task Views .

To be clear before CRAN Task Views R users have informally posted links to packages in their domains on their blogs etc. However, having something in an official place w/ volunteers who maintain it is more reliable.

There have been multiple requests for a Julia Task Views. I would be happy to volunteer to organize one on Data sources.

To repeat, MLJLinearModels.jl is likely your best bet, prob b/c it has great maintainers & is part of the AlanTuringInstitute.