Hi,
I recommend Theano <http://deeplearning.net/software/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
>> >
>> >
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>
>
>
> --
> 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
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--
----------------------------------------------------------------------
#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
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