[mlpack] Google Summer of Code 2018

[Marcus Edel]

Hello Luca,

A good first step is to become very familiar with mlpack's abstractions and
implementation. For the particle swarm project, you can look at the Optimizer
API https://arxiv.org/abs/1711.06581 or at the existing code:
https://github.com/mlpack/mlpack/tree/master/src/mlpack/core/optimizers; that
might be a good place to start.

For the reinforcement learning and profiling project, there is a fair amount of
discussion about both from previous years, as they are recurring projects. Here
is an example:

http://knife.lugatgt.org/pipermail/mlpack/2017-March/thread.html

The String Processing project is not polished yet and is in need of updating,
unfortunately, we haven't had a chance to get around to it yet. So,
unfortunately, you'll have to spelunk for further documentation on how the
project can work.

Also in case, you haven't seen it: mlpack.org/gsoc.html and
www.mlpack.org/involved.html might be helpful.

I hope this was helpful, don't hesitate to ask if we should clarify anything.

Thanks,
Marcus

> On 13. Jan 2018, at 15:04, Luca Foschiani <foschiani01 at gmail.com> wrote:
> 
> Hello,
> I'm a computer science student at the University of Udine (Italy).
> I got my bachelor's degree (in computer science) in 2016 and I'm currently working towards my master's degree. My studies are focused on optimization algorithms and artificial intelligence.
> 
> Some time ago I heard about Google Summer of Code and I began reading about it.
> I thought it would be a really interesting opportunity, so I started learning more about the organizations which were involved in the 2017 GSoC and mlpack is one of them. I also briefly read the descriptions of the 2017 projects which were done by past students.
> 
> The main reasons why I'm interested in mlpack are that C++ is the language which I used the most during the past few years (both for academic purposes and for personal projects), and artificial intelligence (machine learning in particular), together with optimization are the main topics of my master's degree.
> 
> I have already read the ideas for GSoC 2018, and they seem interesting to me. In particular, particle swarm optimization, reinforcement learning, string processing, profiling caught my attention, but I would be interested in pretty much any other idea as well (among the ones listed in the page).
> 
> I just wanted to ask if you could point me in the right direction in order to start thinking about what I could do for mlpack.
> 
> Thank you,
> Luca Foschiani
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