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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: eu1.hubs.ly/H0lXszB0

“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. ⭐ eu1.hubs.ly/H0lz0c30 📜 eu1.hubs.ly/H0lz1BD0

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. eu1.hubs.ly/H0lk5kY0

🖌️ 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. 📚 eu1.hubs.ly/H0lfgz60

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: eu1.hubs.ly/H0kZ0cK0 🔗 GitHub repo: eu1.hubs.ly/H0kZ0vv0 📘 Docs: eu1.hubs.ly/H0kZ00F0

⌛ 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: eu1.hubs.ly/H0kVC040

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: eu1.hubs.ly/H0j-Qpq0

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: eu1.hubs.ly/H0j-zxV0

🎉 We are very happy to celebrate our 11th external contributor on skore! Check out: 👉 the repo: eu1.hubs.ly/H0jJSC-0 ⭐ 👉 or the docs: eu1.hubs.ly/H0jJVb80 📑

New in skore 0.8.2! You can now access directly to the prediction inside your reports. Still in the direction to be all included, easily accessible and stored together. ⭐ To be posted of skore's releases, you can star the repo: eu1.hubs.ly/H0jJSFP0

Friday is a great day to take a step back and learn new skills, isn't it? 📖 To learn more about the difference between metrics & scorers in scikit-learn and to use them more easily, check out with short and instructive video: eu1.hubs.ly/H0jypwL0

⌛ Enriching our metrics! In the new version 0.8.2 of skore, we added some metrics: you can now access to fit (on the train set only, obviously) and predict time (on whatever dataset you want). To know more about it, you can check the docs: eu1.hubs.ly/H0j4Qbn0