# Seeking advice on contributing to Julia: A faster Lasso solver

**URL:** https://discourse.julialang.org/t/seeking-advice-on-contributing-to-julia-a-faster-lasso-solver/42023
**Category:** Statistics
**Tags:** question, package
**Created:** [June 25, 2020, 3:30am UTC](https://discourse.julialang.org/t/seeking-advice-on-contributing-to-julia-a-faster-lasso-solver/42023 "2020-06-25T03:30:13Z")
**Posts on this page:** 1
**Showing post:** 6

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### Author: ![Albert\_Zevelev](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/albert_zevelev/32/11844_2.png) [@Albert\_Zevelev](https://discourse.julialang.org/u/Albert_Zevelev)
#### Post date: [June 25, 2020, 4:31am UTC](https://discourse.julialang.org/t/seeking-advice-on-contributing-to-julia-a-faster-lasso-solver/42023/6 "2020-06-25T04:31:31Z")

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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:

> [@JuliaPDE: Survey of PDE Packages](https://discourse.julialang.org/t/juliapde-survey-of-pde-packages/35672/25):
>
> 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](https://github.com/topics/partial-differential-equations?l=julia)  
> 2 `#pde` 11 repos: [https://github.com/topics/pde?l=julia](https://github.com/topics/pde?l=julia)  
> 3 `#pdes` 2 repos: [https://github.com/topics/pdes?l=julia](https://github.com/topics/pdes?l=julia)  
> 4 Observer: [https://juliaobserver.com/searches?utf8=✓&term=pde](https://juliaobserver.com/searches?utf8=%E2%9C%93&term=pde)  
> 5 Filter by tag: [https://pkg.julialang.org/docs/](https://pkg.julialang.org/docs/)  
> 6 Svaksha’s: [GitHub - svaksha/Julia.jl: Curated decibans of Julia programming language.](https://github.com/svaksha/Julia.jl)
> 
> 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](https://cran.r-project.org/web/views/), for example see [Differential Equations](https://cran.r-project.org/web/views/DifferentialEquations.html).  
> Python is trying [Python Task Views](https://github.com/open-risk/pythontaskviews).
> 
> To be clear before [CRAN Task Views](https://cran.r-project.org/web/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.

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