scikit-learn

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

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

  Official repositoryPython

  67.5K stars

Members 62repositories tagged with one of its aliases, most-starred first

• BayesWitnesses/m2cgen

  Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies

  Tagged scikit-learnPython

  3K stars

• mars-project/mars

  Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.

  Tagged scikit-learnPython

  2.7K stars

• unslothai/hyperlearn

  2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.

  Tagged scikit-learnJupyter Notebook

  2.5K stars

• skfolio/skfolio

  Python library for portfolio optimization built on top of scikit-learn

  Tagged scikit-learnPython

  2.5K stars

• reiinakano/scikit-plot

  An intuitive library to add plotting functionality to scikit-learn objects.

  Tagged scikit-learnPython

  2.4K stars

• modAL-python/modAL

  A modular active learning framework for Python

  Tagged scikit-learnPython

  2.4K stars

• benedekrozemberczki/karateclub

  Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)

  Tagged sklearnPython

  2.3K stars

• feature-engine/feature_engine

  Feature engineering and selection open-source Python library compatible with sklearn.

  Tagged scikit-learnPython

  2.3K stars

• AutoViML/AutoViz

  Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

  Tagged scikit-learnPython

  1.9K stars

• trevorstephens/gplearn

  Genetic Programming in Python, with a scikit-learn inspired API

  Tagged scikit-learnPython

  1.9K stars

• ScottfreeLLC/AlphaPy

  Python AutoML for Trading Systems and Sports Betting

  Tagged scikit-learnPython

  1.8K stars

• kubeflow/katib

  Automated Machine Learning on Kubernetes

  Tagged scikit-learnPython

  1.7K 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

  Listed in the catalogPyPI

  —Not published by PyPI

Ecosystem 392packages that depend on it, most-adopted first

• fastai

  fastai simplifies training fast and accurate neural nets using modern best practices

  Depends on scikit-learnPyPI

  —Not published by PyPI
• feature-engine

  Feature engineering and selection package with Scikit-learn's fit transform functionality

  Depends on scikit-learnPyPI

  —Not published by PyPI
• fedml

  A research and production integrated edge-cloud library for federated/distributed machine learning at anywhere at any scale.

  Depends on scikit-learnPyPI

  —Not published by PyPI
• fg-data-synthetic

  Synthetic data generation methods with different synthetization methods.

  Depends on scikit-learnPyPI

  —Not published by PyPI
• fiftyone

  FiftyOne: the open-source tool for building high-quality datasets and computer vision models

  Depends on scikit-learnPyPI

  —Not published by PyPI
• fiftyone-brain

  FiftyOne Brain

  Depends on scikit-learnPyPI

  —Not published by PyPI
• finmarketpy

  finmarketpy is a Python based library for backtesting trading strategies

  Depends on scikit-learnPyPI

  —Not published by PyPI
• finrl-trading

  A modern quantitative trading platform with ML strategies and live trading capabilities

  Depends on scikit-learnPyPI

  —Not published by PyPI
• fklearn

  Functional machine learning

  Depends on scikit-learnPyPI

  —Not published by PyPI
• flagai

  FlagAI aims to help researchers and developers to freely train and test large-scale models for NLP/CV/VL tasks.

  Depends on scikit-learnPyPI

  —Not published by PyPI
• flair

  A very simple framework for state-of-the-art NLP

  Depends on scikit-learnPyPI

  —Not published by PyPI
• flair-pos

  A very simple framework for state-of-the-art NLP

  Depends on scikit-learnPyPI

  —Not published by PyPI

Latest news the 0 latest events that mention it

No published news event mentions scikit-learn yet.