Get Started

Technology · Library

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

  • apachecn/ailearning

    AiLearning：数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2

    Tagged scikit-learnPython

    42.6K

  • donnemartin/data-science-ipython-notebooks

    Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

    Tagged scikit-learnPython

    29.4K

  • microsoft/onnxruntime

    ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

    Tagged scikit-learnC++

    22K

  • onnx/onnx

    Open standard for machine learning interoperability

    Tagged scikit-learnPython

    21.6K

  • dask/dask

    Parallel computing with task scheduling

    Tagged scikit-learnPython

    13.9K

  • MorvanZhou/tutorials

    机器学习相关教程

    Tagged sklearnPython

    13.1K

  • autogluon/autogluon

    Fast and Accurate ML in 3 Lines of Code

    Tagged scikit-learnPython

    10.8K

  • Yorko/mlcourse.ai

    Open Machine Learning Course

    Tagged scikit-learnPython

    10.7K

  • sktime/sktime

    A unified framework for machine learning with time series

    Tagged scikit-learnPython

    10.1K

  • pycaret/pycaret

    Open-source, low-code AutoML platform for Python. PyCaret 4.0: sklearn-native engine + React control plane.

    Tagged scikit-learnPython

    9.9K

  • automl/auto-sklearn

    Automated Machine Learning with scikit-learn

    Tagged scikit-learnPython

    8.1K

  • alteryx/featuretools

    An open source python library for automated feature engineering

    Tagged scikit-learnPython

    7.7K

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

  • mseep-pyserini

    A Python toolkit for reproducible information retrieval research with sparse and dense representations

    Depends on scikit-learnPyPI

    Not published by PyPI
  • mteb

    Massive Text Embedding Benchmark

    Depends on scikit-learnPyPI

    Not published by PyPI
  • nannyml

    NannyML, Your library for monitoring model performance.

    Depends on scikit-learnPyPI

    Not published by PyPI
  • nemo-toolkit

    NeMo - a toolkit for Conversational AI

    Depends on scikit-learnPyPI

    Not published by PyPI
  • neural-compressor-jax

    Repository of Intel® Neural Compressor

    Depends on scikit-learnPyPI

    Not published by PyPI
  • neurokit2

    The Python Toolbox for Neurophysiological Signal Processing.

    Depends on scikit-learnPyPI

    Not published by PyPI
  • neuromancer

    Neural Modules with Adaptive Nonlinear Constraints and Efficient Regularization

    Depends on scikit-learnPyPI

    Not published by PyPI
  • ngboost

    Library for probabilistic predictions via gradient boosting.

    Depends on scikit-learnPyPI

    Not published by PyPI
  • nilearn

    Statistical learning for neuroimaging in Python

    Depends on scikit-learnPyPI

    Not published by PyPI
  • nncf

    Neural Networks Compression Framework

    Depends on scikit-learnPyPI

    Not published by PyPI
  • nnunetv2

    nnU-Net is a framework for out-of-the box image segmentation.

    Depends on scikit-learnPyPI

    Not published by PyPI
  • nnunetv2-neuropoly

    NeuroPoly fork of nnU-Net

    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.