Upcoming Coding Sprints!
Over the past few months, I have gotten involved in organizing a few upcoming coding sprints. Out of the Berkeley Institute for Data Science, we will be launching a Docathon the week of March 6th, 2017! There will be a few events going on at Berkeley but the event is largely remote, which means you can participate in it from all the corners of the globe!
The aim of this coding sprint is to encourage the development of great documentation for open-source projects. Great APIs and docs are the unsung heroes of open-source projects. They allow users to adopt your package more readily and help attract more users and new developers.
The second coding sprint to look out for is focused on Supervised Neural Time Series. This event will take place in New York City out of NYU Center for Data Science, which is housed in the newly renovated old Forbes building. Put it in your calendar, folks!: March 27–31th, 2017. There will be a talk series open to the broader community on the advances in machine learning for brain data, what types of insights can be found using these techniques, and how it is being applied to research.
The aim of this coding sprint is to develop a clean API that seamlessly integrates different neurophysiological data (e.g. animal electrophysiology, EEG, ECoG, MEG) with sckit-learn. Several Python-based projects, MNE, spykes, pyRiemann, pyGLMnet, will come together to exchange ideas and improve their packages.
If you’re interested in contributing, participating, or donating, hit me up on Twitter: @teonbrooks, or leave a comment below.