[omaha] Group Data Science Competition

[Bob Haffner]

Hi All,

We're all set for the 12/14 group Kaggle competition kickoff!

All experience levels are welcome.  Bring your laptop if you'd like, but no
biggie if you don't

I didn't hear any objections to the Housing Prices competition so let's go
with that one
https://www.kaggle.com/c/house-prices-advanced-regression-techniques

Suggested things to do prior to 12/14
-- Sign up on Kaggle
-- Get your machine set up with some pydata libraries
(Pandas, Numpy, SciKit-Learn and Jupyter Notebooks).  I recommend the
Anaconda distribution if you're just starting out
-- Get some basic familiarity with the competition problem and data

Let me know if you have any questions.

Thanks!
Bob


On Tue, Oct 18, 2016 at 8:32 PM, Bob Haffner <bob.haffner at gmail.com> wrote:

> Good deal. That's 3 of us (Naomi, you and me) by my count.  Hopefully
> others will join in!!
>
>  I would be game for a December meetup.
>
> Sent from my iPhone
>
> > On Oct 18, 2016, at 8:13 PM, Steve Young via Omaha <omaha at python.org>
> wrote:
> >
> > I would enjoy participating, and learning what you data guys and gals do.
> > (I am not a math guy)
> >
> > If Hubert does not take December, maybe we could have a sprint that
> night?
> >
> > Steve
> >
> > On Mon, Oct 17, 2016 at 3:05 PM, Wes Turner via Omaha <omaha at python.org>
> > wrote:
> >
> >> On Monday, October 17, 2016, Bob Haffner via Omaha <omaha at python.org>
> >> wrote:
> >>
> >>> Hi All,
> >>>
> >>> A few months ago someone brought up the idea of doing a Kaggle data
> >> science
> >>> competition as a group.  Is there still interest in this?
> >>>
> >>> Some thoughts.
> >>> Not sure of the details, but Kaggle allows individuals to form groups.
> >> We
> >>> could collaborate thru email (or perhaps something like Slack) and
> maybe
> >>> meet occasionally.  When it's all said and done, we could present at a
> >>> monthly meeting.
> >>
> >>
> >> A GitHub (repo, issues, and sphinx docs/ and/or GH wiki) could also be
> >> useful:
> >>
> >> - gh-pages branch built from docs/ and nb/
> >>  - .ipynb in notebooks/ or nb/
> >> - https://github.com/audreyr/cookiecutter-pypackage/ has packaging and
> >> ReadTheDocs config
> >> -
> >> https://github.com/jupyter/docker-stacks/blob/master/
> >> scipy-notebook/Dockerfile
> >> includes conda
> >>
> >>
> >>
> >>>
> >>> This one looks good.  Doesn't end till March 1st which gives us some
> time
> >>> and it doesn't look overly complicated.  No prize money, though :-)
> >>> https://www.kaggle.com/c/house-prices-advanced-regression-techniques
> >>
> >>
> >> - http://rhiever.github.io/tpot/examples/Boston_Example/
> >>
> >>  - TPOT can utilize XGBoost (as mentioned in the Kaggle competition
> >> description)
> >>
> >>
> >>
> >> - https://github.com/donnemartin/data-science-ipython-notebooks/
> >>
> >>
> >>> Forming groups
> >>> https://www.kaggle.com/wiki/FormingATeam
> >>>
> >>> Would love to get some feedback on any of this
> >>>
> >>> Thanks,
> >>> Bob
> >>> _______________________________________________
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