Welcome to our new sponsor @probabl.ai !

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

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...

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...

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

🚀 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

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 are going live in a bit. If you're keen to see some parallel techniques in Python, or want to learn about Modal/joblib, this one is for you. www.youtube.com/live/0SXyIcs...

Looking forward to speaking on the #OpenSourceAI panel at the sold out EU Open Source Policy Summit by @openforumeurope.org in two weeks. Rather than discussing the definition, we’ll focus on how #openness contributes to European competitiveness—or perhaps, how it might help Europe catch up.

The livestream this week will be about joblib and some big time cloud parallelism that it can support these days via a Modal integration. If you want to learn about Modal or joblib, this should be a super fun one. www.youtube.com/live/0SXyIcs...

We're going live in a bit with a new livestream. In this one we're giving ModernBERT a spin. It is very early days for the project, but there are some interesting milestones already. Join here at 12:30 CET: youtube.com/live/ZWo6Q85...

The first whiteboard video of the year talks about dummy models. The name might not imply it, but using these "dumb" models can be a very smart thing to do at times. youtu.be/0553mUt3O-E

We are back with livestreams this week and this Friday we will explore ModernBERT, a new pragmatic BERT model. It is very early for the project, which seems like a fun time to dip our toes! Join us on Friday during lunch here: youtube.com/live/ZWo6Q85...

Rather than predictions, here are my professional wishes for 2025—shaped by a year of profound learning, building mission-driven @probabl.ai and data science commons with and around @scikit-learn.org, and engaging with brilliant minds, both enthusiastic and concerned about AI: #openness

Our Probablrs Starter Pack is up! go.bsky.app/JZXryZd

Our final whiteboard video of the year is about a detail, a tiny tiny detail, that relates to the precision and recall metrics. These two metrics are typically different, but sometimes they are equal. And something interesting is happening when that is the case! youtu.be/Zn2xrf4ijSY

We are going offline during the holiday weeks, which is also why we are going to have a special edition of the livestream to wrap up the year. Feel free to ask us anything about ML as we also review some certification preparations. www.youtube.com/watch?v=f9G7...

Our new handle is @probabl.ai :)

Going live in a bit! www.youtube.com/watch?v=U3Fi...

We're going to dive into some metrics in the next few whiteboard videos. After all, if you are going to use them to judge machine learning models, it is really important to have a good intuition for them. Let's start with precision, recall and F1: youtu.be/3M2Gmuh5mtI

Join us this Friday if you're eager to see what it can be like to design a recommender while limiting ourselves to just a DataFrame API. It is somewhat unconventional, but a great excuse to show off a Polars trick or two. www.youtube.com/watch?v=U3Fi...

At Probabl, together with the wider community, we continue our dedicated efforts to support and enhance @scikit-learn.org and its ecosystem. In this post, we provide a retrospective on the work accomplished over the last 6 months and the roadmap for the next 6: papers.probabl.ai/open-source-...

We're going live later today with a livestream that is all about trying to use Rust to speed up scikit-learn utilities. Feel free to join if you want to ask questions here: youtube.com/live/O6beIxz...

New podcast episode! This one is about imbalanced-learn and how the maintainer looks back with some lessons learned. If you are dealing with imbalanced classification use-cases, like fraud, you'll want to listen in on this one! youtu.be/npSkuNcm-Og

We're back with a livestream on Friday! This time around we will explore Rust as a tool in an attempt to make faster scikit-learn utilities. Feel free to join live here: www.youtube.com/live/O6beIxz...

We have a new whiteboard video! This one is all about the optimisers curse, which is a phenomenon that can take place when you have many (!) hyperparameters. youtu.be/vC9sAD-ymhk

Please help us test the first release candidate for scikit-learn 1.6: pip install scikit-learn==1.6.0rc1 Changelog: scikit-learn.org/1.6/whats_ne... In particular, if you maintain a project with a dependency on scikit-learn, please let us know about any regression.

According to @wang.social, Chief AI Officer at Anaconda, Inc.: "As the founder of Anaconda and a creator of the PyData ecosystem, I believe deeply that the world needs sustainable economic engines behind open source innovation. [...]

The livestream this week will happen on Saturday, not Friday. But we still have a interesting topic: succesive halving! We'lll explore how the technique can speed up hyperparameter search but also why the technique is still experimental. Join here: www.youtube.com/live/U5wbvPz...

It seems that the PyData Paris talks are up. There are lots of good talks in them, but I might recommend starting with this one. The calibration points at the end make a lot sense!

Game on! 👾 for @scikit-learn.bsky.social experts only: the ✨boss level✨ has arrived 🚀 For seasoned pros ready to master ML: 🔹 Custom algorithms 🔹 MLOps & deployment 🔹 Align ML with business projects Be among the first to get certified! 👉https://eu1.hubs.ly/H0dZ18x0 #machinelearning #datascience

With Artefact, we are delighted to invite data leaders to an exclusive Paris masterclass: ✨Aligning Probabilistic Classification with Business Decisions using @scikit-learn.bsky.social ✨ 🚨Limited seats available! Secure your spot now 👉🏻 lu.ma/fopoglzo #MachineLearning #Advanced #AI #Masterclass

⚠️ Launch Alert 🚀 Today, we're launching the very first official and global scikit-learn practitioner certification program, level 1️⃣ Thank you Inria and and Artefact for being our launch partners! Be the among the first to get certified 👉 certification.probabl.ai