Dear Roland,
In my opinion the directions in Issam's deep learning proposal are a bit better suited for scikit-learn. Our estimators are supposed to be black-box and as general as possible with sensible defaults. I don't know to what extent recurrent nets can be implemented in such a way. Could you discuss a bit how recurrent networks with long-short term memory would fit in scikit-learn and in what ways they would be useful? As for the Kohonen SOM, for some reason academics in our country *love* them, but they had enough time to prove themselves useful and apparently have not. There was a failed attempt to merge this a while back: https://github.com/scikit-learn/scikit-learn/pull/39 In my opinion autoencoders are exciting as a scikit-learn contribution. A good design should be figured out to allow sharing of low-level code with the MLP. Yours, Vlad On Sat, Apr 20, 2013 at 12:43 AM, Roland Szabo <[email protected]> wrote: > Hi! > > I'm a 2nd year student at Babes-Bolyai university in Cluj. I am interested > in contributing to scikit-learn and in participating in GSOC. > > I am doing my bachelor's thesis about neural networks and I would to > implement some of the most commonly used ones in scikit-learn. > > I know there are two pull requests about multi-layer perceptrons (one from > Lars and one from Hannes) and one for Restricted Boltzmann Machines. I read > that Andreas would like to merge the RBM as soon as possible, but the MLP > pull request still has plenty of work left to do. > > Besides this I would like to implement autoencoders, Kohonen Self-Organizing > Maps[1] and Long Short Term Memory[2] > > I have already contributed a three small fixes to scikit-learn (and if you > have any other issues with which I can help I would be happy to do so). > > What do you think? > > -- > Roland > http://rolisz.ro/ > > [1] > http://www.eicstes.org/EICSTES_PDF/PAPERS/The%20Self-Organizing%20Map%20(Kohonen).pdf > [2] http://www.cs.umd.edu/~dmonner/papers/nn2012.pdf > > > ------------------------------------------------------------------------------ > Precog is a next-generation analytics platform capable of advanced > analytics on semi-structured data. The platform includes APIs for building > apps and a phenomenal toolset for data science. Developers can use > our toolset for easy data analysis & visualization. Get a free account! > http://www2.precog.com/precogplatform/slashdotnewsletter > _______________________________________________ > Scikit-learn-general mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > ------------------------------------------------------------------------------ Try New Relic Now & We'll Send You this Cool Shirt New Relic is the only SaaS-based application performance monitoring service that delivers powerful full stack analytics. Optimize and monitor your browser, app, & servers with just a few lines of code. Try New Relic and get this awesome Nerd Life shirt! http://p.sf.net/sfu/newrelic_d2d_apr _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
