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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apps and a phenomenal toolset for data science. Developers can use
our toolset for easy data analysis & visualization. Get a free account!
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