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
- jesse
A trading framework for cryptocurrencies
Not published by PyPI - kangas
Tool for exploring columnar data, including multimedia
Not published by PyPI - kditransform
Kernel density integral transformation
Not published by PyPI - keybert
KeyBERT performs keyword extraction with state-of-the-art transformer models.
Not published by PyPI - keyphrase-vectorizers
Set of vectorizers that extract keyphrases with part-of-speech patterns from a collection of text documents and convert them into a document-keyphrase matrix.
Not published by PyPI - kmodes
Python implementations of the k-modes and k-prototypes clustering algorithms for clustering categorical data.
Not published by PyPI - ktrain
ktrain is a wrapper for TensorFlow Keras that makes deep learning and AI more accessible and easier to apply
Not published by PyPI - laion-clap
Contrastive Language-Audio Pretraining Model from LAION
Not published by PyPI - lazyllm-magic-pdf
A practical tool for converting PDF to Markdown
Not published by PyPI - lazypredict
Lazy Predict helps build a lot of basic models without much code and helps understand which models work better without any parameter tuning
Not published by PyPI - lftakakura-mage-ai
Mage is a tool for building and deploying data pipelines.
Not published by PyPI - libpysal
Core components of PySAL - A library of spatial analysis functions
Not published by PyPI
Latest news the 0 latest events that mention it
No published news event mentions scikit-learn yet.