Great, thanks Oliver!

I'll have a look around and I'll try to analyse what I've already used in
my past projects. I mainly asked to know if that was something important in
particular that you'd like people to focus on, given that there is going to
be a 1.0 release pretty soon.
Looking forward to contributing!

-Nantas


On 4 November 2013 08:43, Olivier Grisel <olivier.gri...@ensta.org> wrote:

> 2013/11/4 Nantas Nardelli <nantas.narde...@gmail.com>
>
>> Thank you, Andy!
>> I've opened a pull request for the README bit. I think I'll have to look
>> to the untagged issues, as the majority of the easy open issues have either
>> already some pull request open or are really old and irrelevant (although I
>> may find something interesting to dive in).
>>
>
>
> I think the best way to get started is to actually use scikit-learn
> yourself, either on your own work / research or as on fun problems such as
> a kaggle.com challence. Then if you hit bugs or under performing bits try
> to work on fixing them and submit a PR.
>
> Also, reviewing the PRs that are related to your area of expertise will
> help:
>
> - pull the PR branch and run the tests on your box and report failures
> - review the code, examples and documentation, make sure it follows
> http://scikit-learn.org/stable/developers/#contributing-code
> - profile the code to identifiy the performance bottlenecks (see
> http://scikit-learn.org/stable/developers/performance.html )
>
> Finally, browsing the examples and running then is a good way to get to
> know the project. If examples lack documentation or could be simplified or
> improved to make them clearer to new-comers, you can also write a PR to
> improve them. Here is an example of such a PR:
> https://github.com/scikit-learn/scikit-learn/pull/2556
>
> --
> Olivier
> http://twitter.com/ogrisel - http://github.com/ogrisel
>
>
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