Welcome!

Sprint

sponsored by

AGENDA 🗓️

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• 18.30: Welcome, networking, pizza and drinks
• 18.45: Sponsor presentation, scikit-learn presentation
• 19.00: Coding
• 21.30: End of the event (or pub/drinks nearby)

Who are we?

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A community open to anyone who wants to contribute to Python open source projects.

This is our 1st sprint in Zürich! 🥳

LinkedIn

Website

Why?

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source: “Scikit-learn sprint instructions” by Andreas Mueller

SPONSOR ✨

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Experts in building data, ML and analytics solutions

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Want to become a part of our team?

• Platform engineer
• Data & software engineer
• Data architect
• Cloud engineer
• Meetup organizer 🤓

scigility.com/en/jobs

scikit-learn

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Scikit-learn is an open source machine learning library that supports supervised and unsupervised learning. It also provides various tools for model fitting, data preprocessing, model selection, model evaluation, and many other utilities.

https://github.com/scikit-learn-inria-fondation/EuroSciPy22

CODING! 💻

💡 Beginners’ corner�Build the dev environment, git basics, playground repo for 1st PR, …

Feel free to ask questions at any time!

Selecting an Issue

Easy:

• https://github.com/scikit-learn/scikit-learn/issues/24862
• https://github.com/scikit-learn/scikit-learn/issues/17568
• https://github.com/scikit-learn/scikit-learn/issues/17295

Medium:

• https://github.com/scikit-learn/scikit-learn/issues/21504

Hard:

• https://github.com/scikit-learn/scikit-learn/issues/11000
• https://github.com/scikit-learn/scikit-learn/issues/22881
• https://github.com/scikit-learn/scikit-learn/issues/22827
• https://github.com/scikit-learn/scikit-learn/issues/25484
• https://github.com/scikit-learn/scikit-learn/issues/24875

Please link @adrinjalali and @glemaitre as reviewers