Data checks for estimators

Before an estimator in scikit-learn learns from data it first checks to see if it is appropriate for the model. Different estimators have different requirements which is why scikit-learn ships with some utilities to help double-check these properties. This video dives into that because it might also help you write better custom estimators yourself.
This whiteboard video is part of the open efforts over at probabl. To learn more you can check out website or reach out to us on social media.
Website: probabl.ai/
LinkedIn: / probabl
Twitter: x.com/probabl_ai
We also host a podcast called Sample Space, which you can find on your favourite podcast player. All the links can be found here:
rss.com/podcas...

[@abc_cba]

You're my favorite Python Data Analyst tutor not just on TH-cam but the entire virtual world.
Best wishes from Sunny/Rainy India 🇮🇳

[@probabl_ai]

Thanks for the kind words.
Small note, while you may hear Vincents voice in these videos, rest assured that it is a team effort to get these videos made. Not just because somebody had to actually write the code in scikit-learn in the first place, but also because the open-source team reviews every video here as well.

[@probabl_ai]

If folks are curious by the way, we have a Discord channel these days. If you are keen to be in touch and ... maybe be involved with some previews of new tools ... feel free to consider joining here:
discord.gg/b3FKDUvA