Shogun 2013 - Google Summer of Code - Shogun Machine Learning Toolbox

We are looking for interested students to join us in improving the
shogun machine learning toolbox (http://www.shogun-toolbox.org) in this
year's google summer of code.
Timeline
========
Application deadline is May 3, 19hrs UTC and the program will run from
May to the end of September (cf.
http://www.google-melange.com/gsoc/events/google/g... )
About Google Summer of Code
===========================
Google Summer of Code is a global program that offers students stipends
($5000 / per student) to write code for open source projects.
http://www.google-melange.com/gsoc/homepage/google...
About the shogun machine learning toolbox
=========================================
SHOGUN is a machine learning toolbox, which is designed for unified
large-scale learning for a broad range of feature types and learning
settings. It offers a considerable number of machine learning models
such as support vector machines for classification and regression,
hidden Markov models, multiple kernel learning, linear discriminant
analysis, linear programming machines, and perceptrons. Most of the
specific algorithms are able to deal with several different data
classes, including dense and sparse vectors and sequences using floating
point or discrete data types. We have used this toolbox in several
applications from computational biology, some of them coming with no
less than 10 million training examples and others with 7 billion test
examples. With more than a thousand installations worldwide, SHOGUN is
already widely adopted in the machine learning community and beyond.
SHOGUN is implemented in C++ and interfaces to all important languages
like MATLAB, R, Octave, Python, Lua, Java, C#, Ruby and has a
stand-alone command line interface. The source code is freely available
under the GNU General Public License, Version 3 at
http://www.shogun-toolbox.org.
During Summer of Code 2013 we intend to improve the accessibility of the
library. Additionally we will be complementing it with promising (new) machine
learning algorithms.
How to Apply
============
- To apply for shogun, select one or multiple topics from our ideas list
http://shogun-toolbox.org/page/Events/gsoc2013_ide... or propose topics you are
highly interested in - we might be very interested too :)
- Before applying, please ensure that you have your working environment
set up, i.e. checkout shogun from git and successfully compiled its
relevant parts (see instructions on http://www.shogun-toolbox.org) and
indicate that you have done so. In addition, it is required to contribute at
least a small patch to get you set up (e.g. by attacking one of the entry tasks
from https://github.com/shogun-toolbox/shogun/issues?la... )
and to be considered.
Please note that we have an application template that following will
incredibly help us to process your application. It is at the bottom of
the website (link follows below). This webpage also has the register for
GSoC application link
http://www.google-melange.com/gsoc/org/google/gsoc...
If you have further questions don't hesitate to ask on the shogun
mailinglist (shogun-list-AT-shogun-toolbox.org, please note that you have
to be subscribed in order to post) or on irc.freenode.net channel
#shogun.
Additional Resources
=====================
- In case you are unsure if you are good enough or have other questions
check out the student FAQ.
http://www.booki.cc/gsocstudentguide/am-i-good-eno...
- Some general guidelines how to make a good impression :)
http://google-opensource.blogspot.com/2011/03/dos-...