[mlpack] add rbm to mlpack

[Marcus Edel]

Hi Shangtong,

Thanks for your interest. mlpack is open source and everyone is welcome to
contribute. :)

Recently I've committed some code to support neural networks (feed forward
neural networks, recurrent neural networks with a bunch of different layers
including LSTM). It's a first a temp to cover recent work. Anyway I'm highly
interested in projects that are going in that direction. I think RBM's are an
interesting idea to start, if you like we can discuss about some details. Over
the mailing list or in irc either way is fine with us.

I think it's a good idea to get familiar with mlpack in the meantime. The best
way to get started is to download mlpack and compile it from source, then use it
for some simple machine learning tasks. The tutorials might prove helpful:

http://www.mlpack.org/tutorial.html

Once you've got a basic feel for mlpack programs and source, you can take a look
at the list of open tickets you might find something interesting:

https://github.com/mlpack/mlpack/issues

Also, there is the mlpack IRC channel (#mlpack on freenode), which could be a
useful resource for real-time help. The logs are here:

http://www.mlpack.org/irc/

Also, be aware that Google hasn't selected orgs yet (The application phase isn't
even open! I guess they open the application phase in about a month). We've
participated in the past years, but this is no guarantee they'll select us
again.

Let me know if I can help out further.

Marcus



> On 03 Jan 2015, at 13:21, Shangtong Zhang <zhangshangtong.cpp at qq.com> wrote:
> 
> Hi,
> 
> I’m a third year undergraduate majoring in Computer Science in Fudan University, China.
> I want to get involved in GSoC 2015 with mlpack. I completed GSoC 2014 with Xapian.
> 
> I’m interested in machine learning, and in this field, matlab is popular, but many still want a tool written C++.
> Neural Network has been getting more and more popular in recent years and have made great success 
> in various fields. But it seems I don’t find support for NN in mlpack. So is it appropriate that we make NN supported 
> in GSoC 2015 ? If this task is a little big, can we just start up with support for Restricted Boltzmann Machines(RBM) ?
> 
> Thanks for your reading.
> 
> Best Regards
> 
> 
> 
> Shangtong Zhang,
> Third Year Undergraduate,
> School of Computer Science,
> Fudan University, China.
> _______________________________________________
> mlpack mailing list
> mlpack at cc.gatech.edu
> https://mailman.cc.gatech.edu/mailman/listinfo/mlpack

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