Discussion:
Help for learning/contributing
(too old to reply)
Ignacio Rossi
2014-06-25 18:56:21 UTC
Permalink
Hello,

Today I dropped by the freenode channel, but no one was around at the
time, so I'm relaying my message here, thanks for reading :)

I’m a math undergraduate who works as a python developer. I’m currently
between jobs, so I have one month worth of spare time and i was thinking
about learning ML and contributing to the project during that time
I’ve peeked the issue tracker (the easy tag), but I might need some
guidance on where to start. I don't know much about ML yet - taking the
course on coursera, but wishing to contribute some code in the meantime

Any suggestions regarding learning/contributing will be appreciated

Thanks

Ignacio
Joel Nothman
2014-06-25 19:54:29 UTC
Permalink
Hi Ignacio,

A good starting place is often working on the documentation. For example,
https://github.com/scikit-learn/scikit-learn/pull/3084 is an attempt at
filling in a gap in the documentation, but it doesn't look like Raul is
going to complete the work any time soon. If you want to pull his branch,
finish responding to the comments (i.e. fixing up the changes), and create
a new PR out of it, that would be helpful.

A similarly stalled documentation change is
https://github.com/scikit-learn/scikit-learn/pull/2529

Also in the space of cross-validation (which I figure is a fairly trivial
ML idea to understand), but working on code:
https://github.com/scikit-learn/scikit-learn/issues/2904 is mostly an issue
of rewriting the cross_validation module to have a different API. As
suggested by the discussion there, its design may not be trivial, but it
would be very valuable to see a first attempt at the rewrite.
https://github.com/scikit-learn/scikit-learn/issues/1848 is similarly
mostly about moving things around, and it will help making a clean change
together with #2904. You should make sure you have read the contributing
guidelines and are familiar with the deprecation procedures for either of
these restructure tasks.

Is that along the lines of the sort of things you would like to start on?

Joel
Post by Ignacio Rossi
Hello,
Today I dropped by the freenode channel, but no one was around at the
time, so I'm relaying my message here, thanks for reading :)
I’m a math undergraduate who works as a python developer. I’m currently
between jobs, so I have one month worth of spare time and i was thinking
about learning ML and contributing to the project during that time
I’ve peeked the issue tracker (the easy tag), but I might need some
guidance on where to start. I don't know much about ML yet - taking the
course on coursera, but wishing to contribute some code in the meantime
Any suggestions regarding learning/contributing will be appreciated
Thanks
Ignacio
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Ignacio Rossi
2014-06-25 21:15:39 UTC
Permalink
Hi Joel,
Post by Joel Nothman
Is that along the lines of the sort of things you would like to start on?
Yes, I think these look good. I'll start looking into them and pop around
here or github if anything comes up.

Thanks

Ignacio
Post by Joel Nothman
Hi Ignacio,
A good starting place is often working on the documentation. For example,
https://github.com/scikit-learn/scikit-learn/pull/3084 is an attempt at
filling in a gap in the documentation, but it doesn't look like Raul is
going to complete the work any time soon. If you want to pull his branch,
finish responding to the comments (i.e. fixing up the changes), and create
a new PR out of it, that would be helpful.
A similarly stalled documentation change is
https://github.com/scikit-learn/scikit-learn/pull/2529
Also in the space of cross-validation (which I figure is a fairly trivial
https://github.com/scikit-learn/scikit-learn/issues/2904 is mostly an
issue of rewriting the cross_validation module to have a different API. As
suggested by the discussion there, its design may not be trivial, but it
would be very valuable to see a first attempt at the rewrite.
https://github.com/scikit-learn/scikit-learn/issues/1848 is similarly
mostly about moving things around, and it will help making a clean change
together with #2904. You should make sure you have read the contributing
guidelines and are familiar with the deprecation procedures for either of
these restructure tasks.
Is that along the lines of the sort of things you would like to start on?
Joel
Post by Ignacio Rossi
Hello,
Today I dropped by the freenode channel, but no one was around at the
time, so I'm relaying my message here, thanks for reading :)
I’m a math undergraduate who works as a python developer. I’m
currently between jobs, so I have one month worth of spare time and i was
thinking about learning ML and contributing to the project during that time
I’ve peeked the issue tracker (the easy tag), but I might need some
guidance on where to start. I don't know much about ML yet - taking the
course on coursera, but wishing to contribute some code in the meantime
Any suggestions regarding learning/contributing will be appreciated
Thanks
Ignacio
------------------------------------------------------------------------------
Open source business process management suite built on Java and Eclipse
Turn processes into business applications with Bonita BPM Community Edition
Quickly connect people, data, and systems into organized workflows
Winner of BOSSIE, CODIE, OW2 and Gartner awards
http://p.sf.net/sfu/Bonitasoft
_______________________________________________
Scikit-learn-general mailing list
https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
------------------------------------------------------------------------------
Open source business process management suite built on Java and Eclipse
Turn processes into business applications with Bonita BPM Community Edition
Quickly connect people, data, and systems into organized workflows
Winner of BOSSIE, CODIE, OW2 and Gartner awards
http://p.sf.net/sfu/Bonitasoft
_______________________________________________
Scikit-learn-general mailing list
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Ignacio Rossi
2014-07-01 09:05:18 UTC
Permalink
Hi Joel,

I've sent this email on friday, but it got stuck on some revision queue
because of the attachment size, so I'm repeating it with a link :P
https://github.com/pignacio/scikit-learn/blob/loo_is_bad_doc/doc/images/cross_validation_comparison.svg

In https://github.com/scikit-learn/scikit-learn/pull/2529, there's an image
that should be stripped from the repository and generated via matplotlib on
doc generation:
https://github.com/pignacio/scikit-learn/blob/loo_is_bad_doc/doc/images/cross_validation_comparison.svg

I'm failing to understand the x-axis meaning, as I could not find
references to regularization in the LogisticRegression docs. If someone
could provide a link/explanation, that would be great.

Once that's settled I'm pretty sure I can write the code to generate the
image using some example dataset.

Thanks

Ignacio
Post by Joel Nothman
Hi Ignacio,
A good starting place is often working on the documentation. For example,
https://github.com/scikit-learn/scikit-learn/pull/3084 is an attempt at
filling in a gap in the documentation, but it doesn't look like Raul is
going to complete the work any time soon. If you want to pull his branch,
finish responding to the comments (i.e. fixing up the changes), and create
a new PR out of it, that would be helpful.
A similarly stalled documentation change is
https://github.com/scikit-learn/scikit-learn/pull/2529
Also in the space of cross-validation (which I figure is a fairly trivial
https://github.com/scikit-learn/scikit-learn/issues/2904 is mostly an
issue of rewriting the cross_validation module to have a different API. As
suggested by the discussion there, its design may not be trivial, but it
would be very valuable to see a first attempt at the rewrite.
https://github.com/scikit-learn/scikit-learn/issues/1848 is similarly
mostly about moving things around, and it will help making a clean change
together with #2904. You should make sure you have read the contributing
guidelines and are familiar with the deprecation procedures for either of
these restructure tasks.
Is that along the lines of the sort of things you would like to start on?
Joel
Post by Ignacio Rossi
Hello,
Today I dropped by the freenode channel, but no one was around at the
time, so I'm relaying my message here, thanks for reading :)
I’m a math undergraduate who works as a python developer. I’m
currently between jobs, so I have one month worth of spare time and i was
thinking about learning ML and contributing to the project during that time
I’ve peeked the issue tracker (the easy tag), but I might need some
guidance on where to start. I don't know much about ML yet - taking the
course on coursera, but wishing to contribute some code in the meantime
Any suggestions regarding learning/contributing will be appreciated
Thanks
Ignacio
------------------------------------------------------------------------------
Open source business process management suite built on Java and Eclipse
Turn processes into business applications with Bonita BPM Community Edition
Quickly connect people, data, and systems into organized workflows
Winner of BOSSIE, CODIE, OW2 and Gartner awards
http://p.sf.net/sfu/Bonitasoft
_______________________________________________
Scikit-learn-general mailing list
https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
------------------------------------------------------------------------------
Open source business process management suite built on Java and Eclipse
Turn processes into business applications with Bonita BPM Community Edition
Quickly connect people, data, and systems into organized workflows
Winner of BOSSIE, CODIE, OW2 and Gartner awards
http://p.sf.net/sfu/Bonitasoft
_______________________________________________
Scikit-learn-general mailing list
https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
Olivier Grisel
2014-07-01 09:14:47 UTC
Permalink
This PR has been made obsolete by another that was already merged (see
the comments).
--
Olivier
Ignacio Rossi
2014-07-01 09:26:39 UTC
Permalink
Oh, didn't see that, thanks!
Post by Olivier Grisel
This PR has been made obsolete by another that was already merged (see
the comments).
--
Olivier
------------------------------------------------------------------------------
Open source business process management suite built on Java and Eclipse
Turn processes into business applications with Bonita BPM Community Edition
Quickly connect people, data, and systems into organized workflows
Winner of BOSSIE, CODIE, OW2 and Gartner awards
http://p.sf.net/sfu/Bonitasoft
_______________________________________________
Scikit-learn-general mailing list
https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
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