@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
> >
> >
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--
LI, Wei
Tsinghua/CUHK
http://kuantkid.github.com/
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analytics on semi-structured data. The platform includes APIs for building
apps and a phenomenal toolset for data science. Developers can use
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