Google Summer of Code 2016 Projects

Heiko Strathmann edited this page Nov 25, 2016 · 54 revisions
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Google Summer of Code 2016

Thanks everyone for a great summer. See the follow up blog posts for how it went.

Main focus

This year's GSoC is about improving Shogun, rather than extending it (exceptions allowed). We also want to recruit new long-term developers.

  • Focus on existing algorithms: We want to improve our algorithms - easier use, efficiency, better documentation and more applications - rather than just adding more algorithms.
  • Focus on students: We want to have fewer students - more intense mentoring, interaction between students, blogging and documenting for individual students.


In addition to the technical project, all students will:

  • work on a joint GSoC project: a Shogun cookbook
  • peer-review a fellow student's work
  • jointly help with the 5.0 release
  • contribute to our GSoC blog

GSoC 2016 deliverables.

Easy Installation on Major Platforms

link to project page

Shogun Detox

link to project page

New Parameter Framework and Plugin Architecture

link to project page

Fundamental ML: the usual suspects

link to project page

(outdated) - project ideas

Project Ideas below are roughly ordered by priority and projects in bold type are more likely to happen.

Improving Shogun's infrastructure

Projects improving Shogun are the main focus of this year's GSoC. They are roughly ordered by priority and most of them do not focus on Machine Learning but rather on software engineering.

Extending Shogun

Note that projects extending Shogun have a lower priority than projects improving Shogun. If algorithms related projects will happen, they are likely to be based around improvements rather than adding new ones.



Other ideas:

We are also open for your ideas: If you have a cool idea for an application or collaboration with another project, let us know! To add your project, please create a new wiki page for each project that you describe. Name them as "GSoC_2016_project_XXX" etc. Here is a template.

  • Cool pipelines:
    • A kaggle pipeline for supervised prediction.
    • Spectrometer (there is an open-source hardware project on this)
    • Music brainz predictions (The cool hair guy at GSoC is the one we should talk to here)
    • Some biology thing?
    • Collaboration with MLPack for toolkit wide performance/accuracy testing. See their GSoC 2013 project


Our list of projects is a growing list.