scikit-learn
@scikit-learn.org
📤 2071
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📝 5
Machine learning in Python • Open Source
https://scikit-learn.org
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
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PyData Paris 2025
https://pydata.org/paris2025
4 months ago
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reposted by
scikit-learn
Rémi Flamary
4 months ago
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.
add a skeleton here at some point
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❄️ 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
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scikit-learn Version 1.6.0 Release Highlights
YouTube video by scikit-learn
https://youtu.be/7wiHChpwJe8
about 1 year ago
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reposted by
scikit-learn
about 1 year ago
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
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GitHub - glemaitre/sklearn-compat
Contribute to glemaitre/sklearn-compat development by creating an account on GitHub.
https://github.com/glemaitre/sklearn-compat
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reposted by
scikit-learn
Tim Head
about 1 year ago
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
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reposted by
scikit-learn
Olivier Grisel
about 1 year ago
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...
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reposted by
scikit-learn
Olivier Grisel
about 1 year ago
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...
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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...
https://github.com/scikit-learn/scikit-learn/issues/30257
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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.
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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...
https://scikit-learn.org/1.6/whats_new/v1.6.html
about 1 year ago
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