Give us a star ⭐️ on GitHub to support the project!
🚀 Join us November 30 for the Evidently monthly demo and Q&A. Register now →

Data Scientists + Hacktoberfest = ❤️

Are you a data scientist who wants to contribute to open source?

Join us for Hacktoberfest to add new data drift metrics and tests to the Evidently open-source library.

I WANT TO PARTICIPATE
Evidently Hacktoberfest 2022

Sign up to join us!

Hacktoberfest 2022 is over.
Leave your email, and we'll let you know when the next fest begins.

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.

How to participate?

In the Evidently GitHub repository, we added a special set of issues labeled “hacktoberfest."

step 1
Check out the guide

Head to Evidently Hacktoberfest guide for clear steps and detailed examples.

step 2
Pick an issue

Check out the issues we prepared for Hacktoberfest. You can pick one of them or propose a different metric.

step 3
Submit pull request

Choose the drift method you want to implement and submit your pull request!

step 4
Get feedback

Wait for your pull request to be reviewed.

What is Evidently?

Evidently is an open-source Python library for data scientists and ML engineers. It helps evaluate, test, and monitor the performance of ML models from validation to production. You can check it out on GitHub or explore the documentation.

What is Hacktoberfest?

Hacktoberfest is an annual event to celebrate open-source and encourage contributions. It runs for the 9th time this year. Eligible participants will get prizes from DigitalOcean. But first and foremost, it is a great reason to create your first (or hundredth) pull request! You can check out the complete rules here.

How can I contribute?

Evidently is an open-source project, and is always open for contributions. For Hacktoberfest, we added a special set of issues labeled “hacktoberfest” to the Evidently GitHub repository. We invite data scientists to dip their toes into open-source contribution and help us add new statistical metrics and tests to detect data drift for production ML models. Check out Hacktoberfest issues on our GitHub. Head to the Evidently Hacktoberfest guide for clear steps and detailed examples. Sign up to receive the kick-off newsletter.

Don’t forget to register for Hacktoberfest by October 31! If you register and have 4 pull requests accepted among the first 40000 participants, you can get a prize. Read more here.

By clicking “Accept”, you agree to the storing of cookies on your device to enhance site navigation, analyze site usage, and assist in our marketing efforts. View our Privacy Policy for more information.