:probabl.

Open-source data science and machine learning

[:probabl. @probabl_ai]

Do you want to have fun, compete with your peers, evaluate your knowledge, and... have a chance to win a scikit-learn hat?
Look no further!
We are organizing a live learning quiz on March 11th, at 4:30PM UTC
👉 subscribe here: https://t.co/tzgemicza9
See you soon!

[:probabl. @probabl_ai]

🔮 What can you see in scikit-learn ecosystem future?

We offer you a perfect Friday short break activity.

📥 drop a note to have a say!
https://t.co/S6DAJvlbdC

[:probabl. @probabl_ai]

Using Skore in your ML workflows? We'd love to hear about your experience. Book 30 minutes with Nicolas, our PM, to share feedback, discuss pain points, or influence our roadmap.
https://t.co/lELEVknApY

[:probabl. @probabl_ai]

👮Thanks to Skops, you can safely load persisted models: it will block any unknow piece of code.
But what happens if you want to add you own transformer? Easy: you can extend the sources trusted by skops with a parameter when loading.
📖 To learn more: https://t.co/nCVgNjqnFX

[:probabl. @probabl_ai]

🎣Are you using ML models fitted by others? How do you make sure that there is no threat when opening a persisted model?
👮Thanks to Skops, you can safely load models. If there is anything fishy, you will be alerted before being infested.
📖To learn more: https://t.co/6PIarz25jC

[:probabl. @probabl_ai]

🎣Are you using ML models fitted by others? How do you make sure that there is no threat when opening a persisted model?
👮Thanks to Skops, you can safely load models. If there is anything fishy, you will be alerted before being infested.
📖To learn more: https://t.co/6PIarz25jC

[:probabl. @probabl_ai]

🎁 We have a gift for you!
You've heard about skrub and would like to discover more? Or you never heard about it, but struggle with data preprocessing?
📽️ Riccardo Cappuzzo did an awesome video at PyData that has been recorded: you can have a look here 👉 https://t.co/Cgm8r6wLxH

[:probabl. @probabl_ai]

Probabl Raises €13M in Seed to accelerate Enterprise Grade AI
https://t.co/HXXK9mJvBG

[:probabl. @probabl_ai]

@SuryaanshAwa114 Congrats! Seems like you are ready for the official @scikit_learn certification. https://t.co/ICbH96RGK5

[:probabl. @probabl_ai]

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

[:probabl. @probabl_ai]

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: https://t.co/q6yXyxmI5Y

Take advantage of the summer to learn more about skore and boost your machine learning workflow!

[:probabl. @probabl_ai]

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: https://t.co/AtWrfJ5edl

[:probabl. @probabl_ai]

🚀 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: https://t.co/GnolmFXmE7

[:probabl. @probabl_ai]

@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

[:probabl. @probabl_ai]

(Re)-watch our session at @PyData Milan in March 2025 where we discussed the latest developments in the @scikit_learn ecosystem: https://t.co/wsb8Lfpvhf

We explore what scikit-learn allows you to do and introduce powerful tools like @skrub_data, skops, and skore.

[:probabl. @probabl_ai]

☀️ 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: https://t.co/iByJBBf8bF

[:probabl. @probabl_ai]

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!

[:probabl. @probabl_ai]

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: https://t.co/HXQGXj5HYk

[:probabl. @probabl_ai]

“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.

⭐ https://t.co/J1oTGvrJVe
📜 https://t.co/ZxzvcXRZtR

[:probabl. @probabl_ai]

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!