Recap:.v0.6: Introducing the EstimatorReport.v0.7: Introducing the ComparisonReport.v0.8: Introducing the feature_importance accessor of the EstimatorReport.v0.9: Introducing the search feature.v0.10: Introducing the data accessor of the EstimatorReport.

With each release of skore, we have been sharing a short demo video highlighting the main new feature. Check out our handy YouTube playlist here: Take advantage of the summer to learn more about skore and boost your machine learning workflow!.

Join millions who have switched to Grok.

With skore v0.10, you now have a data accessor in the EstimatorReport! It consists in a @skrub_data TableReport that allows you to interactively explore your data and gain precious insights before your modelling!. 🎬 Check out our short demo video:

🚀 Save time on ML evaluations with skore! 🚀 No more recomputing predictions for each metric. Skore caches predictions, enabling instant metric calculations and fast plots. Check out this example for more information:

@PyData @scikit_learn @skrub_data Timeline:.0:00: Intro of PyData Milan.7:30: Presentations of speakers.9:25: What scikit-learn allows you to do.21:15: skrub - less wrangling, more machine learning.32:54: skops - scikit-learn models in production.43:51: skore - an abstraction to ease data science projects.

(Re)-watch our session at @PyData Milan in March 2025 where we discussed the latest developments in the @scikit_learn ecosystem: We explore what scikit-learn allows you to do and introduce powerful tools like @skrub_data, skops, and skore.

☀️ It’s summer time! .Isn’t it a great moment to take a step back, and learn new things?.Check out our whiteboard videos to learn about the quantile trick, why tree gradients give you a boost, or the optimizer curse, etc:

What is the difference between good and bad data scientists?.Good ones know the data they work with. Perfectly understanding the data can be time-consuming. Yet, some basic analysis can pave the way for high-value insights. Now in skore’s release 0.10, with a data accessor!

Born from the scikit-learn initiative, Skore is designed to support not just scikit-learn models but a wide array of machine learning models, including foundational models, such as TabICL, a tabular foundation model!. Check our full example:

“Let’s improve this model in production !”.Skore can help you to know how the release of a new model will impact the business with its objects EstimatorReport and ComparisonReport. ⭐ 📜

Last week, the team organized a workshop for Saint-Gobain. We presented skore and skrub in the morning, and did an open source sprint in the afternoon. Thank you Mojdeh Rastgoo for preparing everyone!. Check skore and skrub's good first issues to participate too!

Launching Skolar: a new platform for hands-on, structured and certified training in open-source data science.

🖌️ There is that plot provided by skore that you like. It quickly gives an idea of the performances. You would like to see the underlying numbers to investigate further. 🔍 .That’s why we created the Displays, that can either return a frame, or a plot. 📚

Did you ever felt lost among all the experiments tried in the model development phase? Skore has your back!. 🎉 Check out the demo video of our new release with the search feature: 🔗 GitHub repo: 📘 Docs:

@glemaitre58 Join him on Paris demo night this Thursday! .To save a seat -->

LLMs & co are good tools for generating code. What about solving data science problems?.@glemaitre58 will show that there is a need for fundamental core libraries to leverage GenAI tools to get maintainable and methodologically correct solutions for data science problems.

⌛ Enriching our metrics!. In the new version 0.9 of Skore, we added some metrics: you can now access the confusion matrix!. Just a couple of lines, everything easily accessible from the same object. To know more about it, you can check the docs:

We have an event every week these days! 🍕.After the machine learning challenge, we organized a sprint with Unaite to onboard students to open source. Open source is a great way to showcase their skills, as would a personal project!

🎤 Next week, our product engineer Marie Sacksick will be presenting how to extend scikit-learn with skore, but also with skrub and skops. Thanks Pyladies Paris for this opportunity!. To book your seat:

Last week, we hosted an exciting challenge bringing together data scientists for an exciting team-building event! Participants predicted bike counter data in Paris, diving into real-world data science with tools like skore and skrub. Check out skore: