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GSoC 2020
DFFML is hoping to participate in Google Summer of Code under the Python Software Foundation umbrella. You can read all about what GSoC is at http://python-gsoc.org/ and https://summerofcode.withgoogle.com/how-it-works/#timeline
Please make sure you are ready for a 30+ hour a week time commitment. The scope of your proposal should reflect this. See https://developers.google.com/open-source/gsoc/faq#how_much_time_does_gsoc_participation_take for more details.
DFFML is a plugin based library / framework for machine learning. It allows users to wrap high or low level implementations of models that use various machine learning libraries, so as to interact will lots of different model implementations in the same way.
DFFML is also a tool for dataset generation. DFFML ues directed graphs to generate datasets.
Read more on the about page: https://intel.github.io/dffml/about.html
We currently have three project ideas:
If you've got a idea you'd like to propose, please make a new issue with the gsoc: project: prefix to discuss it! We're open to all sorts of ideas. Students are also welcome to add "stretch goal" ideas to their application, which don't have to be related to their main proposal (but still have to result in contributions to DFFML). Stretch goals are for if you finish your proposed project before the end of the summer, and have more that you want to do.
- Read the contributing page
- Go through the tutorials on the documentation site, make sure you're familiar with the command line interface.
- Run the tests. DFFML has unit tests which are at about 90% coverage (amount of lines of code tested). Make sure you know how to run them, and if you've never done Python unittests before you might want to read up on python's unittest library. Figure out how to run a single test! Running one test instead of all of them will speed up your workflow when you are writing your tests! (hint, it's in the contributing docs!)
- Make your first contribution!
- Doesn't have to be related to your project. Just make sure we know that you understand how to interact with the community, codebase, and GitHub. If you're not familiar that's okay! We'll show you the ropes, but you have to jump in the pool if you want to learn how to swim.
- You could start with some small and extra small issues (time wise).
- You could help us increase the test coverage in any of the packages (check out the python package
coverageto learn how to do this). - You could write a new model! Models are wrappers around any machine learning implementation or library, see the new model tutorial for more info. Make sure to include tests!
- You could write a new operation to do something! Anything! Operations to grab weather and stock data have been suggested by people as good ideas.
Instructions on How to apply can be found on the Python GSoC website. Please don't forget to use our name (dffml) in your application title!
In your proposal, we're looking to see:
- What work you want to get done.
- How long you think it will take you.
- Why you think it will take you that long.
- When estimating how long it will take you it helps to think about any contributions to DFFML you've done up until now and compare what you're proposing to what you've done.
- Remember, Google expects students to work 30+ hours a week on their GSoC projects.
Here's a template
Most of our communication takes place on the Gitter channel you can also check out the Community page in the docs for more ways to get in touch.
Big thanks to Terri her work organizing GSoC and letting us copy her format she used for CVE Binary Tool, another awesome project with a security focus that was a part of GSoC 2019 as well. Check them out too!