Technology · Library
scikit-learn
Library · Catalog tech@1
Machine learning in Python.
- Matched as
- scikit-learn
- sklearn
Momentum
Each signal is ranked as a percentile among the technologies that have it. A signal without enough history is not counted, and never shown as zero. How momentum works
Momentum
Collecting0 of 5 signalsNo score yet. Momentum is published only when at least 2 of the 5 signals have history. scikit-learn has 0, so there is no single number: each signal is shown on its own below. It is not a zero, and nothing is estimated in its place.
Snapshot OCT 24, 2026 · Scoring tech@1
- Official repository stars
- Collecting
- Star growth needs repository snapshots 30 days apart.67,452 stars now
- Member repository stars
- Collecting
- Star growth needs repository snapshots 30 days apart.0 new members in 30 days
- Package adoption
- Not published by its registries
- Its packages’ registries publish no adoption figure, so there is nothing to grow.
- Open models
- No official models
- No official model on Hugging Face, so this signal does not apply.
- News
- Collecting
- News counts once there are 3 events across the last 60 days; it has 0.0 in the last 30 days · 0 in the 30 before
Adoption by registry
The growth of scikit-learn’s own packages, one row per registry in that registry’s own unit. Registries count different things over different windows, so they are never added together.
No registry has two observations of scikit-learn’s own packages about 30 days apart yet, so there is no growth to show. Nothing is estimated in its place.
News activity
- Events · 7 days
- 0published events that mention it
- Events · 30 days
- 0published events that mention it
- Previous 30 days
- 0events in the 30 days before
Momentum history
Momentum history starts OCT 8, 2026. A chart appears once two daily snapshots carry a score; none does so far.
Repositories
Official 1
- scikit-learn/scikit-learn
scikit-learn: machine learning in Python
67.5K stars
Members 62repositories tagged with one of its aliases, most-starred first
- ggeop/Python-ai-assistant
Python AI assistant 🧠
1K stars
- giotto-ai/giotto-tda
A high-performance topological machine learning toolbox in Python
1K stars
Packages
“Is” packages are scikit-learn itself; ecosystem packages depend on them. The two are counted separately and never added together. Adoption is each registry’s own figure, with its percentile within that registry.
Is 1the technology itself, most-adopted first
- scikit-learn
A set of python modules for machine learning and data mining
Not published by PyPI
Ecosystem 392packages that depend on it, most-adopted first
- hypertools
A python package for visualizing and manipulating high-dimensional data
Not published by PyPI - hyppo
A comprehensive independence testing package
Not published by PyPI - iflow-mcp-memoryos
Intelligence Begins with Memory
Not published by PyPI - imagededup
Package for image deduplication
Not published by PyPI - imbalance-xgboost
XGBoost for label-imbalanced data: XGBoost with weighted and focal loss functions
Not published by PyPI - imbalanced-learn
Toolbox for imbalanced dataset in machine learning
Not published by PyPI - imcui
Image Matching Webui: A tool for matching images using sota algorithms with a Gradio UI
Not published by PyPI - imitation
Implementation of modern reward and imitation learning algorithms.
Not published by PyPI - imitation-qjm
Implementation of modern reward and imitation learning algorithms.
Not published by PyPI - imodels
Implementations of various interpretable models
Not published by PyPI - interpret-core
Fit interpretable models. Explain blackbox machine learning.
Not published by PyPI - iterative-stratification
Package that provides scikit-learn compatible cross validators with stratification for multilabel data
Not published by PyPI
Latest news the 0 latest events that mention it
No published news event mentions scikit-learn yet.