[mlpack] Fwd: Queries regarding GSoC

[Rajiv Vaidyanathan]

Hi Marcus,

As of now, I am working on writing a test for SPSA optimizer which I have
implemented... I'll try to finish it ASAP. As of now, I cannot think of any
DL model good enough to replace the suggested ones... Also, as you said,
lets wait until Google officials confirms :)

Regards,
Rajiv

On 3 February 2018 at 03:22, Marcus Edel <marcus.edel at fu-berlin.de> wrote:

> Hello Rajiv,
>
> Nice to hear from you again how are things going?
>
> > I am interested in the following topics(listed in the order of interest):
> > 1. Reinforcement Learning
> > 2. Essential Deep Learning Modules
> > 3. Particle Swarm Optimization
> >
> > How should I go about it? I read a few Mailing List archives for 1 and
> 3. What
> > should I do after that? Can I start working on the proposal submission?
>
>
> Going through the mailing list archive is definitely a good starting
> point, also
> the weekly updates from Kris and Shangtong
> (http://www.mlpack.org/gsocblog/index.html) could be interesting too.
>
> The models listed for the Essential Deep Learning Modules idea are just
> suggestions, if you like to work on an interesting network model over the
> summer
> please feel free to start a discussion.
>
> A good starting point, in general, is to get familiar with the codebase,
> if you
> have any question please don't hesitate to ask. About the submission
> that's up
> to you, but note Google hasn't announced the accepted organizations yet and
> there is plenty of time to prepare the proposal and get feedback.
>
> I hope this is helpful, let us know if we should clarify anything.
>
> Thanks,
> Marcus
>
> > On 2. Feb 2018, at 16:19, Rajiv Vaidyanathan <
> rajiv.vaidyanathan4 at gmail.com> wrote:
> >
> > Hi Marcus,
> >
> > I'm N Rajiv Vaidyanathan(github handle: rajiv2605). I have contributed
> to mlpack in the past and I really like this organisation. I am very
> interested in participating in GSoC.
> >
> > I am interested in the following topics(listed in the order of interest):
> > 1. Reinforcement Learning
> > 2. Essential Deep Learning Modules
> > 3. Particle Swarm Optimization
> >
> > How should I go about it? I read a few Mailing List archives for 1 and
> 3. What should I do after that? Can I start working on the proposal
> submission?
> >
> > Thanking you.
> >
> > Regards,
> > Rajiv
> >
> > _______________________________________________
> > mlpack mailing list
> > mlpack at lists.mlpack.org
> > http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack
>
>
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