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scikit-learn

Library · Catalog tech@1

Machine learning in Python.

Categories
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 signals

No 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

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

  • uxlfoundation/scikit-learn-intelex

    Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application

    Tagged scikit-learnPython

    1.4K

  • sebp/scikit-survival

    Survival analysis built on top of scikit-learn

    Tagged scikit-learnPython

    1.3K

  • nok/sklearn-porter

    Transpile trained scikit-learn estimators to C, Java, JavaScript and others.

    Tagged scikit-learnPython

    1.3K

  • nicodv/kmodes

    Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data

    Tagged scikit-learnPython

    1.3K

  • benedekrozemberczki/CapsGNN

    A PyTorch implementation of "Capsule Graph Neural Network" (ICLR 2019).

    Tagged sklearnPython

    1.3K

  • reiinakano/xcessiv

    A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python.

    Tagged scikit-learnPython

    1.3K

  • onnx/onnxmltools

    ONNXMLTools enables conversion of models to ONNX

    Tagged scikit-learnPython

    1.2K

  • oneapi-src/oneAPI-samples

    Samples for Intel® oneAPI Toolkits

    Tagged scikit-learnC++

    1.2K

  • lensacom/sparkit-learn

    PySpark + Scikit-learn = Sparkit-learn

    Tagged scikit-learnPython

    1.2K

  • microsoft/Windows-Machine-Learning

    Samples and Tools for Windows ML.

    Tagged scikit-learnC++

    1.1K

  • ryfeus/lambda-packs

    Precompiled packages for AWS Lambda

    Tagged sklearnPython

    1.1K

  • khuangaf/CryptocurrencyPrediction

    Predict Cryptocurrency Price with Deep Learning

    Tagged sklearnJupyter Notebook

    1.1K

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

  • econml

    This package contains several methods for calculating Conditional Average Treatment Effects

    Depends on scikit-learnPyPI

    Not published by PyPI
  • eli5

    Debug machine learning classifiers and explain their predictions

    Depends on scikit-learnPyPI

    Not published by PyPI
  • emerge-viz

    Visualize source code structure and dependencies in an interactive d3 application

    Depends on scikit-learnPyPI

    Not published by PyPI
  • emotivoice

    EmotiVoice 😊: a Multi-Voice and Prompt-Controlled TTS Engine

    Depends on scikit-learnPyPI

    Not published by PyPI
  • empirical-calibration

    Package for empirical calibration

    Depends on scikit-learnPyPI

    Not published by PyPI
  • esda

    Exploratory Spatial Data Analysis in PySAL

    Depends on scikit-learnPyPI

    Not published by PyPI
  • evidently

    Open-source tools to analyze, monitor, and debug machine learning model in production.

    Depends on scikit-learnPyPI

    Not published by PyPI
  • executorch

    On-device AI across mobile, embedded and edge for PyTorch

    Depends on scikit-learnPyPI

    Not published by PyPI
  • explainerdashboard

    Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.

    Depends on scikit-learnPyPI

    Not published by PyPI
  • factor-analyzer

    A Factor Analysis tool written in Python

    Depends on scikit-learnPyPI

    Not published by PyPI
  • fairlearn

    A Python package to assess and improve fairness of machine learning models.

    Depends on scikit-learnPyPI

    Not published by PyPI
  • fast-hdbscan

    A fast multicore version of HDBSCAN and PLSCAN clustering algorithms.

    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.