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:

🎉 We are very happy to celebrate our 11th external contributor on skore!. Check out: .👉 the repo: ⭐.👉 or the docs: 📑

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:

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:

⌛ 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:

To register, you can use the following link:

Are you looking for a team building event where the play is somehow related to your job of data scientist? We have your back! .📆 We are organizing an ML Challenge using skore on April 29th, in Paris. Bonus: the view is not too bad.

@scikit_learn @skrub_data @glemaitre58 @MarieSacksick Thank you Luca Baggi for the invitation at PyData Milan!.Check the full video here:

For this recipe, you will need: .- 4 open source libraries,.- 3 vibrant colors,.- 2 enthusiastic speakers,.- 1 welcoming host,.Mix it all, expose to some Milan's sun, and you will get. a talk on @scikit_learn, @skrub_data, skops, and skore, by @glemaitre58 and @MarieSacksick.

It's possible that you've been building classifiers for years without ever having heard of variable thresholds. But oh my! They make an existing classifier ✨better✨! . Our latest whiteboard video explains why it's one of our most favourite techniques.

Tuning a threshold of a classifier tends to have a big impact, maybe even more impact than tuning a hyperparameter. And as of recently, you can even automate this tuning in scikit-learn. Our YouTube channel gives a demo:.

Metadata routing is a recent addition to the scikit-learn library that will allow for a lot more advanced pipelines and machine learning systems. Our latest YouTube video gives you all the details:.