I am quite busy until Monday (included) but I'll work after that on the 1-page abstract. This shouldn't take very long. Also, I don't think we need the demo to be ready by the time of submission, so this leaves us even more time to prepare nice examples.
What do you think of the following structure for the abstract? (this is merely a proposal from the top of my head) a) Short introduction of Scikit-Learn - what is it? - what does it include? (... and what it does *not* include?) - large and vivid dev/user base b) Integration of Scikit-Learn into the scientific Python eco-system - use of Numpy and Scipy as building blocks, and nothing more - simple and non-intrusive API (limited set of methods, consistency throughout the whole library, duck typing) - ... which makes it very easy to connect with other Python packages c) Briefly outline some of the examples we would present at the demo? Gilles On 26 September 2013 12:32, Olivier Grisel <olivier.gri...@ensta.org> wrote: > 2013/9/26 Gael Varoquaux <gael.varoqu...@normalesup.org>: >> On Mon, Sep 16, 2013 at 09:19:23AM +0200, Gilles Louppe wrote: >>> So basically, do we agree that the goal of our proposal to this >>> workshop will only be to further promote the project in the scientific >>> community? >> >> Sounds good to me :) >> >>> Besides that, I like the idea of showing examples to highlight the >>> strengths of the package. >> >> Yes, very important, I believe. >> >>> > Parallel cross-validation with IPython notebook >> >>> This one would be great. It also shows our ambition to integrate with >>> other open source projects. >> >> We can probably extract that from our scipy tutorial, that is already an >> IPython notebook. >> >>> > Feature hashing? (any good examples?) >> >>> Maybe we could instead cook up an NLP example? We have a bunch of >>> tools for that (vectorizers). >> >> I think that the new out-of-core learning example is a very good one. I >> have an IPython notebook with it, and it shows a lot of things. It is not >> exactly a simple example, though. >> >>> Finally, how shall we proceed? Is there a template to use for the >>> 1-page abstract? I can't find any on the call for papers. > > There is no template for the abstract. We need to make sure that the > MLOSS entry is up to date which is not the case: > > http://mloss.org/software/view/240/ > > The question was answered on twitter: > > https://twitter.com/ahonkela/status/381671918836789248 > > -- > Olivier > http://twitter.com/ogrisel - http://github.com/ogrisel > > ------------------------------------------------------------------------------ > October Webinars: Code for Performance > Free Intel webinars can help you accelerate application performance. > Explore tips for MPI, OpenMP, advanced profiling, and more. Get the most from > the latest Intel processors and coprocessors. See abstracts and register > > http://pubads.g.doubleclick.net/gampad/clk?id=60133471&iu=/4140/ostg.clktrk > _______________________________________________ > Scikit-learn-general mailing list > Scikit-learn-general@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general ------------------------------------------------------------------------------ October Webinars: Code for Performance Free Intel webinars can help you accelerate application performance. Explore tips for MPI, OpenMP, advanced profiling, and more. Get the most from the latest Intel processors and coprocessors. See abstracts and register > http://pubads.g.doubleclick.net/gampad/clk?id=60133471&iu=/4140/ostg.clktrk _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
