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

• flwrlabs/flower

  Flower: A Friendly Federated AI Framework

  Tagged scikit-learnPython

  7.2K stars

• interpretml/interpret

  Fit interpretable models. Explain blackbox machine learning.

  Tagged scikit-learnC++

  7K stars

• biolab/orange3

  🍊 :bar_chart: :bulb: Orange: Interactive data analysis

  Tagged scikit-learnPython

  5.7K stars

• dusty-nv/jetson-containers

  Machine Learning Containers for NVIDIA Jetson and JetPack-L4T

  Tagged scikit-learnJupyter Notebook

  4.9K stars

• DistrictDataLabs/yellowbrick

  Visual analysis and diagnostic tools to facilitate machine learning model selection.

  Tagged scikit-learnPython

  4.4K stars

• microsoft/FLAML

  A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

  Tagged scikit-learnJupyter Notebook

  4.4K stars

• astroautomata/PySR

  Symbolic Learning in Python and Julia

  Tagged scikit-learnPython

  3.8K stars

• christianversloot/machine-learning-articles

  🧠💬 Articles I wrote about machine learning, archived from MachineCurve.com.

  Tagged scikit-learn

  3.7K stars

• microsoft/hummingbird

  Hummingbird compiles trained ML models into tensor computation for faster inference.

  Tagged scikit-learnPython

  3.5K stars

• fnnx-ai/scikit-llm

  Seamlessly integrate LLMs into scikit-learn.

  Tagged scikit-learnPython

  3.5K stars

• mljar/mljar-supervised

  Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

  Tagged scikit-learnPython

  3.3K stars

• nidhaloff/igel

  a delightful machine learning tool that allows you to train, test, and use models without writing code

  Tagged scikit-learnPython

  3.1K 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

  Listed in the catalogPyPI

  —Not published by PyPI

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

• semantica

  Graph-Native Infrastructure for Context and Accountable AI Systems: context graphs, decision intelligence, full provenance tracking, and explainable reasoning engines — every AI decision traceable, every output auditable.

  Depends on scikit-learnPyPI

  —Not published by PyPI
• semilearn

  Unfied Semi-Supervised Learning Benchmark

  Depends on scikit-learnPyPI

  —Not published by PyPI
• sentence-transformers

  Embeddings, Retrieval, and Reranking

  Depends on scikit-learnPyPI

  —Not published by PyPI
• setfit

  Efficient few-shot learning with Sentence Transformers

  Depends on scikit-learnPyPI

  —Not published by PyPI
• shap

  A unified approach to explain the output of any machine learning model.

  Depends on scikit-learnPyPI

  —Not published by PyPI
• shap-gpu

  A unified approach to explain the output of any machine learning model.

  Depends on scikit-learnPyPI

  —Not published by PyPI
• shinka-evolve

  Automated Scientific Evolution

  Depends on scikit-learnPyPI

  —Not published by PyPI
• simpletransformers

  An easy-to-use wrapper library for the Transformers library.

  Depends on scikit-learnPyPI

  —Not published by PyPI
• simpletuner

  Stable Diffusion 2.x and XL tuner.

  Depends on scikit-learnPyPI

  —Not published by PyPI
• skfolio

  Portfolio optimization, factor model construction, and risk management built on top of scikit-learn

  Depends on scikit-learnPyPI

  —Not published by PyPI
• skforecast

  Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models.

  Depends on scikit-learnPyPI

  —Not published by PyPI
• skl2onnx

  Convert scikit-learn models to ONNX

  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.