Read through our how-to-get-started guide.
If you haven't done so already, watch our online tutorial at PyData Amsterdam to become familiar with sktime. Alternatively, work through our tutorial notebooks.
If you get stuck or have a question, please comment on the relevant issue, chat with us on Gitter or the PyData discord server.
Read our contributing guidelines.
It's always good to raise an issue or leave a comment on an existing issue before you start working to describe what you would like to change or implement.
We suggest a few topics to work on, but please don't hesitate to propose your own topic!
- 🔬 User testing: play around with the tutorial notebooks, try to understand the code, and give us feedback! For example, which time series classifier achieves the best performance on the arrow head problem? Which forecaster achieves the best performance on the airline data set?
- 📚 Improve our online documentation - many classes and methods have missing doc strings!
- 📖 Improve our example notebooks - make them more engaging and instructive.
- ⚙️ Take a look at our good-first issues and pick one that interests you.
- 🚧 Improve our dev ops, see #241 (dev ops skills)
- 💻 Enhance our website (web development skills)
- 🧰 Create interfaces to other toolboxes like gluon-ts or fbprophet
- 🎨 Pick a topic from our development roadmap and propose an API design - for examples, see our design notes on forecasting and annotation
- 🐼 Data container, check out our introductory notebook and design discussion
Our goal, apart from improving sktime, is to onboard new contributors and we would really like you to stay around after the sprint. We're actively looking for new contributors and your help is extremely welcome!
We have an active community of researchers and students who work on sktime, and we offer an informal mentorship programme over the summer in which we help you become more familiar with machine learning, time series analysis and open-source software development. The programme would involve weekly calls with your mentor.
You can choose a project to work on and we can help you to find an interesting topic. In addition to the individual project work, all students will be expected to:
- peer-review fellow contributors' work,
- write a blog post about your contribution,
- socialise with other students and contributors.
Please get in touch if you're interested!