[mlpack] Regarding GSoC 17
marcus.edel at fu-berlin.de
Thu Mar 2 08:03:40 EST 2017
welcome and thanks for your interest in the project. Have you searched through
the list archives for other messages about the Essential Deep Learning project?
There is a lot of information that has been written about this project over the
In general, to be successful at this project, you should have a good knowledge
of deep learning; i.e., you should be familiar with the way deep neural networks
are typically built and trained, and certainly you should be familiar with the
individual components that you plan to implement.
You are welcome to propose to implement any or all of the four modules that are
currently listed (RBM, RBFN, BRN, GAN), or you can even propose other modules
that mlpack does not currently have implemented. We can always discuss other
interesting ideas, that you have in mind.
Maybe these pages are also helpful:
There are also some issues open in the Github issue tracker, and any
contributions of new techniques or efficiency improvements for existing
implementations are always welcome.
I hope this is helpful, let us know if you have any more questions.
> On 2 Mar 2017, at 07:07, Kushagra Agrawal <kushagra106 at gmail.com> wrote:
> I am Kushagra Agrawal, I'm pursuing my bachelors in Electronics and Communications Engineering from BITS Pilani, Hyderabad Campus. I'm interested in participating in GSoC 17 with mlpack.
> I went through the project ideas, and the project "Essential Deep Learning Modules" really caught my interest. I have worked on a project regarding Deep Learning for Video Classification that involved CNN's. While I was working on that, I had also read about RBM's and RNN's
> Please guide me on how should I start and how should I go about if I wish to participate in GSoC 17 with mlpack.
> Kushagra Agrawal
> mlpack mailing list
> mlpack at lists.mlpack.org
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