Hi Issam, The deadline is fast approaching. How is your proposal going? Could you share a version so we can give some feedback?
Yours, Vlad On Sat, Apr 20, 2013 at 3:57 AM, amir rahimi <noname01....@gmail.com> wrote: > Sorry, I didn't see Andy's note ;) > > > On Fri, Apr 19, 2013 at 11:23 PM, amir rahimi <noname01....@gmail.com> > wrote: >> >> Hi, >> I recommend Theano if you want to use python with GPU for deep learning. >> It is tightly integrated with numpy.... >> >> Best, >> Amir >> >> >> On Thu, Apr 18, 2013 at 9:21 PM, Wei LI <kuant...@gmail.com> wrote: >>> >>> @Andy What do you mean by "blackbox" algorithm? Does that mean something >>> similar to pylearn2? >>> >>> @Issam, It seems to me that scalablity is a key factor to train deep >>> models and make them work. Do you have any suggestion how to make it >>> scalable while still fits in sklearn framework? I think sklearn cannot >>> supports GPU easily. I wanna know is training a deep model for a mid-level >>> scale(maybe like cifar?) painful on CPU only with numpy? >>> >>> Best, >>> Wei >>> >>> On Fri, Apr 19, 2013 at 12:27 AM, Andreas Mueller >>> <amuel...@ais.uni-bonn.de> wrote: >>>> >>>> Hi Issam. >>>> Thank you for your interest. Have you looked at the >>>> MLP and RBM pull requests that are currently open? >>>> How would your project relate to those? >>>> >>>> A real problem is that we don't want to replicate theano >>>> and rather have a somewhat "black box" algorithm that people can >>>> apply.... >>>> >>>> Cheers, >>>> Andy >>>> >>>> >>>> On 04/18/2013 06:07 PM, Issam wrote: >>>> > Hi scikit, >>>> > >>>> > Here I am proposing to work on deep learning topic for GSOC 2013. Deep >>>> > learning is a relatively new research area that is progressing fast >>>> > with a lot of potential for contributions. It involves an intersting >>>> > idea by trying to imitate the brain, as it uses many levels (hidden >>>> > layers) of processing. Where the levels are at decreasing order of >>>> > abstractions! >>>> > >>>> > In this project, I'm planning to work on each step carefully, first I >>>> > look into "Deep Boltzmann machines", then "Deep belief >>>> > networks","Deep >>>> > auto-encoders", "Stacked denoising auto-encoders", and more. I could >>>> > create a complete plan for this, once I get your feedback :) >>>> > >>>> > I have been involved in quite a number of machine learning projects, >>>> > from dealing with imbalanced datasets (software quality prediction), >>>> > to >>>> > XML classification, from recognizing gender out of handwriting, to >>>> > breast cancer prediction using mammograms. I'm in my second semester >>>> > as >>>> > a graduate student (MSc), and machine learning is my research area. My >>>> > thesis would involve deep learning, which i will apply on >>>> > bioinformatics >>>> > and face recognition. >>>> > >>>> > I would be more than happy to work with a mentor on this! >>>> > >>>> > Thank you! >>>> > >>>> > Best regards, >>>> > --Issam Laradji >>>> > >>>> > >>>> > ------------------------------------------------------------------------------ >>>> > 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 >>>> > Scikit-learn-general@lists.sourceforge.net >>>> > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general >>>> >>>> >>>> >>>> ------------------------------------------------------------------------------ >>>> 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 >>>> Scikit-learn-general@lists.sourceforge.net >>>> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general >>> >>> >>> >>> >>> -- >>> LI, Wei >>> Tsinghua/CUHK >>> http://kuantkid.github.com/ >>> >>> >>> >>> ------------------------------------------------------------------------------ >>> 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 >>> Scikit-learn-general@lists.sourceforge.net >>> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general >>> >> >> >> >> -- >> ---------------------------------------------------------------------- >> #include <stdio.h> >> double d[]={9299037773.178347,2226415.983937417,307.0}; >> main(){d[2]--?d[0]*=4,d[1]*=5,main():printf((char*)d);} >> ---------------------------------------------------------------------- > > > > > -- > ---------------------------------------------------------------------- > #include <stdio.h> > double d[]={9299037773.178347,2226415.983937417,307.0}; > main(){d[2]--?d[0]*=4,d[1]*=5,main():printf((char*)d);} > ---------------------------------------------------------------------- > > ------------------------------------------------------------------------------ > 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 > Scikit-learn-general@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > ------------------------------------------------------------------------------ Introducing AppDynamics Lite, a free troubleshooting tool for Java/.NET Get 100% visibility into your production application - at no cost. 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