Ryan CurtinandDirk Eddelbuettel
9fd815144d
* A first attempt at overhauling the documentation job with a cache. * Actually remove files we don't need anymore. * Fix output from local link checks to give it all at once. * Add sparse matrices to the set of detected matrix types. * Fix comparison condition. * Make a pass to try and re-validate cached links that have not yet expired. * Compile and link separately so that ccache can take effect. * Be a little bit smarter about caching. * Ensure libicu$SO is installed so 'stringi' can be used Also collapse to remotes calls into one * Fix style issues that cpplint 2 found (#3884) * Try to workaround the libicu issue for now. * Mention new dependency. --------- Co-authored-by: Dirk Eddelbuettel <edd@debian.org>
80 lines
4.5 KiB
Markdown
80 lines
4.5 KiB
Markdown
# mlpack and Google Summer of Code
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mlpack is a proud participant in Google Summer of Code. We have been a part of
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the program since 2013, with over 50 students accepted over the years for mlpack
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(all of whom succeeded in the program). Each year, we receive very many
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applications and it is a competitive process, so this page exists to help you
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determine if you could be a strong candidate.
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## How to be a good candidate
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The two most important qualities that an mlpack GSoC candidate can possess is
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the ability to be self-sufficient and the willingness to learn.
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Self-sufficiency is key because mentors have limited time and can’t put in as
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much time helping the student as the student is putting in. However, this of
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course does not mean that a student (or a prospective student) can never ask any
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questions! mlpack is a complex library and can sometimes take help and
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explanation to understand.
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A willingness to learn is also important because virtually every potential
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project will require the student to become familiar with a new algorithm or C++
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technique. mlpack is a complex library with many components and it is likely
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during your project that you might have to use or interact with some other part
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of the codebase.
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## Things to be familiar with
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Of course, these are not the only important ingredients for a successful GSoC
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project. A student should ideally be familiar with
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- *open source software development*: opening pull requests, using git, opening
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issues. mlpack uses Github, which has great documentation. You can learn
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about the workflow using [this link](https://docs.github.com/en), if you are
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not already familiar.
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- *using the development toolchain on your computer*: you should be able to
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download and compile mlpack, make changes to the code, and recompile with the
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new changes. There is a [guide](../user/install.md) for how to build mlpack
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and that would be a great place to get started. If you’re on Windows, then
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the [Windows build guide](../user/build_windows.md) could be very useful. See
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also the [Community page](community.md) for more information on getting
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started.
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- *at least intermediate C++ knowledge*: mlpack uses lots of different C++
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paradigms including template metaprogramming, C++ features like rvalue
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references, and other strategies, in order to make the code fast. You should
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be at least familiar with some of these language features and what templates
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are, even if you have not used them in-depth, so that you can understand the
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mlpack codebase. Some examples of patterns that are often used inside of
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mlpack are SFINAE ([example in mlpack, see std::enable_if usages](https://github.com/mlpack/mlpack/blob/565cfd3aad22deec0656b86e801052593a937723/src/mlpack/methods/mean_shift/mean_shift.hpp)),
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[policy-based design](https://www.drdobbs.com/policy-based-design-in-the-real-world/184401861),
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and [compile-time class traits](https://accu.org/xaraya/journals/442.html).
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Here are some [other useful resources](https://en.wikipedia.org/wiki/Template_metaprogramming)
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for learning template metaprogramming, and some useful
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[reference books](https://www.aristeia.com/books.html).
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If some of this sounds new to you, don’t feel overwhelmed; it’s not a
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necessity, but it is helpful. You should at least be prepared to learn about
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it!
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- *project-specific knowledge*: you’ll need to have an in-depth understanding
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of the specific project that you choose. If you’re not sure what project you
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want to work on, see the
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[SummerOfCodeIdeas](https://github.com/mlpack/mlpack/wiki/SummerOfCodeIdeas)
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wiki page, which has ideas for GSoC projects that you might find interesting.
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But you aren’t required to do one of those projects; if you have another
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interesting idea, propose it and see if a mentor is interested in supervising
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the project! If you have any questions about a project, be aware that it’s
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possible that the question has already been answered on Github. Take a look
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through the closed issues or search to see if there’s already an answer to
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your question. Get involved!
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For a strong proposal, it’s important to be a part of the mlpack community, via
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contributions, code reviews, helping others solve their issues, and so forth.
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There are some pointers on the [community page](community.md) on how to start
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contributing and get involved.
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When it comes time to write your proposal, we do have a
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[proposal guide](https://github.com/mlpack/mlpack/wiki/Google-Summer-of-Code-Application-Guide)
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that you can take a look at to guide your application.
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