threadpoolctl 3.7.0 is out. This library is a utility used by @scikit-learn.org and others to coordinate the levels of thread-based parallelism in native libraries such as BLAS implementations and OpenMP runtimes used by Python libraries such as NumPy, SciPy, PyTorch and scikit-learn.

Advanced @scikit-learn.org  from PyData Paris 2024: metadata routing, transformers that actually know what they're doing. These slides reshape how you build production code 👇

PyData Paris 2024 - Olivier Grisel - Keynote

From probabilistic predictions to operational decisions Olivier Grisel @ogrisel September, 2024

docs.google.com

New in sklearn 1.9: set_callbacks(ProgressBar()) on your estimator. A live progress bar on your fit. ScoringMonitor logs accuracy at each iteration. Works with GridSearchCV and Pipeline too. @scikit-learn.org

7. Callbacks

This guide demonstrates how to use scikit-learn’s callbacks on compatible estimators. For information about how to implement the callback API, you can refer to the following sections of the develop...

scikit-learn.org

Metadata routing in @scikit-learn.org changes everything.  Vincent shows how to route columns without manual pipeline tracking, so your transformers actually know what they're doing 👇

Metadata routing in scikit-learn

Metadata routing is a relatively new feature that allows you to, as...

youtube.com

Ever run a long GridSearchCV and had no idea if it was doing anything? sklearn 1.9 adds a callback API. Attach a ProgressBar or ScoringMonitor — and watch it work, iteration by iteration. @scikit-learn.org

7. Callbacks

This guide demonstrates how to use scikit-learn’s callbacks on compatible estimators. For information about how to implement the callback API, you can refer to the following sections of the develop...

scikit-learn.org

scikit-learn 1.9 🎉 The most underrated update category: "existing estimators now faster and better at handling missing values." Boring headline, massive practical difference. Every real-world dataset has missing data. This is the library listening to what practitioners actually need.

scikit-learn@scikit-learn.org · 4mo ago

🎉 Scikit-learn 1.9 released: ■Solid improvements to many existing estimators: faster, more stable, handling missing values, adding GPU support… ■Also, enhanced estimator displays in notebooks, ■And callbacks that enable progress bars or monitoring of convergence blog.scikit-learn.org/updates/rele...

🎉 Scikit-learn 1.9 released: ■Solid improvements to many existing estimators: faster, more stable, handling missing values, adding GPU support… ■Also, enhanced estimator displays in notebooks, ■And callbacks that enable progress bars or monitoring of convergence blog.scikit-learn.org/updates/rele...

Scikit-learn is on the @linuxfoundation.org Open Source Insights board, alongside with many other central projects: insights.linuxfoundation.org/project/scik... What an honor to contribute to the open-source tissue that cements the world!

A bunch of scikit-learn core contributors will attend or speak at @pydataparis.bsky.social 2025 on Tuesday and Wednesday next week. Ticketing, practical infos and schedule at: pydata.org/paris2025

PyData Paris 2025

pydata.org

SKADA is a beautiful software for Domain Adaptation in python with many shallow and deep methods implemented, it is 100% compatible with @scikit-learn.org models and pipelines and with @pytorch.org for deep learning methods.

Compute! Paris@computeparis.bsky.social · last yr.

📢 Talk Announcement "Tackling Domain Shift with SKADA: A Hands-On Guide to Domain Adaptation", by Théo Gnassounou and Antoine Collas. 📜 Talk info: pretalx.com/pydata-paris-2025/talk/MEPTCE 📅 Schedule: pydata.org/paris2025/schedule 🎟 Tickets: pydata.org/paris2025/tickets

❄️ The Christmas release is here! ❄️ Introducing scikit-learn 1.6 with: 🟢 2 major features & 34 improvements 🔵 5 efficiency boosts & 21 enhancements 🟡 14 API changes 🔴 30 fixes 👥 160 amazing contributors youtu.be/7wiHChpwJe8

scikit-learn Version 1.6.0 Release Highlights

YouTube video by scikit-learn

youtu.be

We are working on a small package to ease developer life: github.com/glemaitre/sk.... The idea is that recurrent work could be centralized in a single package. Once we have a minimal version, we will do a first release to support scikit-learn 1.2 to 1.6

GitHub - glemaitre/sklearn-compat

Contribute to glemaitre/sklearn-compat development by creating an account on GitHub.

github.com

Have you ever wanted to unpickle a @scikit-learn.bsky.social model you trained with version X while using a newer version X+1? If yes, why? When? How? I'd be interested to hear about your use cases to see if we can make it less painful

I recently shared some of my reflections on how to use probabilistic classifiers for optimal decision-making under uncertainty at @pydataparis.bsky.social 2024. Here is the recording of the presentation: www.youtube.com/watch?v=-gYn...

3rd-party library maintainers might find it cumbersome to handle the transition to the new estimator tags while keeping backward compatibility with older scikit-learn versions. We will devise a way to smooth out the transition before releasing 1.6.0 final: github.com/scikit-learn...

Estimator creating `_more_tags` and inheriting from `BaseEstimator` will not warn about old tag infrastructure · Issue #30257 · scikit-learn/scikit-learn

While making the code of skrub compatible with scikit-learn 1.6, I found that the following is really surprising: # %% import numpy as np from sklearn.base import BaseEstimator, RegressorMixin clas...

github.com

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.

Version 1.6

Legend for changelogs something big that you couldn’t do before., something that you couldn’t do before., an existing feature now may not require as much computation or memory., a miscellaneous min...

scikit-learn.org