We introduced a new tool last week that helps you immediately grab all the right metrics and charts for your pipeline. It comes with many sensible defaults and can be customised too.
If you're keen to save some time, feel free to check the demo on YT:
youtu.be/2rjkrR7CjHc
We will be going live in a bit, if you're keen to learn about prefect, feel free to join!
youtube.com/live/hkm5Ofi...
There is a subtle, but important, difference between metrics and scorers in scikit-learn. Understanding this difference really matters, especially when you want to apply ML in business with custom metrics.
So we made a new tutorial on the topic, viewable here:
youtu.be/67KMDSitw1M
Another week, another livestream.
This time we will have a look at prefect. It's a modern scheduling tool for Python that seems to have some nice features for ML training. Join us here on Friday:
youtube.com/live/hkm5Ofi...
We have a new whiteboard video! This one is all about the classification report and we explain how it works in detail by leveraging a custom widget to change some of the values by hand.
You can watch it on our YT channel here:
youtu.be/765qaIk30Rs
The page for the `train_test_split` function is the most visited page on the scikit-learn documention. It's because people always forget the order of the output.
So we figured it might make sense to make a video that helps you remember:
youtu.be/wb4bKSHiDik
When you cross-validate, you're usually using stratified sampling. It's a default that comes with scikit-learn, and it certainly has an upside ... but also a downside.
We try to explain why in our latest whiteboard video on YouTube.
www.youtube.com/watch?v=EpK9...
Demo time! 2mn of your time to get a flavor of skore 😉 youtu.be/2rjkrR7CjHc
🚀 Meet skore—the @scikit-learn.org sidekick!
🔹 Offers guidance on modeling
🔹 Automated reports & key metrics
💡 Built by scikit-learn maintainers. Open-source & ready to use!
Try it 👉 tinyurl.com/bdhszwtn
