[mlpack] An Introduction

[Amitrajit Sarkar]

Hello Marcus,

I agree: each of these projects requires a lot of background study.
However, my undergrad research work has been focused on neural networks and
deep learning for over a year now. Hence I am already familiar with the
concepts appearing on the Ideas page, as well as those previously mentioned
in the mailing list, having implemented several myself. I shall certainly
look through the new references I find on the reading lists before filling
out my application. If there are any resources in particular that you would
like me to take note of, do mention them.

I built mlpack from source, tried the tutorials, and started deciphering
the source code. I understand that neural networks in mlpack use armadillo
matrices for efficiency, a vectorized approach. I was wondering whether a
connectionist approach would be better with regard to implementing the
Neuroevolution algorithms when dealing with Augmenting Topologies. I would
like your views on the matter.

Also, would you like to see a basic implementation of CNE, using the
existing mlpack neural networks, as a warm-up task? I really look forward
to contributing to mlpack.

Regards,
Amitrajit.

On Mon, Mar 7, 2016 at 5:38 AM, Marcus Edel <marcus.edel at fu-berlin.de>
wrote:

> Hello Amitrajit,
>
> sorry for the slow response.
>
> I am especially interested in:
>
> Neuroevolution Algorithms,
> Essential Deep Learning Modules,
> We Need To Go Deeper - Google LeNet.
>
>
> I might suggest that you narrow your focus because each of these projects
> has a
> significant amount of background knowledge that is necessary.
>
> To learn more about each of the projects than what has been listed on the
> Ideas
> page, take a look at the mailing list archives:
>
> https://mailman.cc.gatech.edu/pipermail/mlpack/
>
> However, others are already working on the warmup tasks listed alongside
> the
> projects. Are there any other tasks that I could try?
>
>
> Don't worry, contributing is not a requirement for an application. So if
> you
> don't find anything that you think you can do, that's not necessarily a
> problem.
> However, I'll see if I can add some more "easy" issues in the next couple
> of
> days. On the other side, you are always welcome to just poke around the
> library
> and try to fix any problems you find, or improve the speed of various
> parts.
>
> Thanks,
> Marcus
>
> On 06 Mar 2016, at 08:39, Amitrajit Sarkar <aaiijmrtt at gmail.com> wrote:
>
> Hi,
>
> I am Amitrajit Sarkar, a CS undergrad from Jadavpur University, India. I
> have been working on machine learning for over a year now. I even have my
> own neural networks library <https://github.com/aaiijmrtt/NET>, which I
> wrote from scratch while trying to understand existing theories. I am very
> eager to contribute to mlpack for GSoC 2016, as almost all the projects
> excite me equally.
>
> I am especially interested in:
>
> Neuroevolution Algorithms,
> <https://github.com/mlpack/mlpack/wiki/SummerOfCodeIdeas#neuroevolution-algorithms>
> Essential Deep Learning Modules,
> <https://github.com/mlpack/mlpack/wiki/SummerOfCodeIdeas#essential-deep-learning-modules>
> We Need To Go Deeper - Google LeNet.
> <https://github.com/mlpack/mlpack/wiki/SummerOfCodeIdeas#we-need-to-go-deeper---googlenet>
>
> I have implemented basic neuroevolution algorithms here
> <https://github.com/aaiijmrtt/LEARNING>, and several deep learning
> modules here <https://github.com/aaiijmrtt/NET>. I am certain that I can
> take up the tasks. However, others are already working on the warmup tasks
> listed alongside the projects. Are there any other tasks that I could try?
> I have a lot of experience with research work, and am a skilled coder.
>
> I am attaching my CV for reference. You may find more about my interests
> on my blog <http://aaiijmrtt.github.io/>.
>
> Cheers,
> Amitrajit.
> <cv.pdf>_______________________________________________
> mlpack mailing list
> mlpack at cc.gatech.edu
> https://mailman.cc.gatech.edu/mailman/listinfo/mlpack
>
>
>
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