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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

  • 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

  • vaex-ml

    Machine learning support for vaex

    Depends on scikit-learnPyPI

    Not published by PyPI
  • vbench

    Video generation benchmark

    Depends on scikit-learnPyPI

    Not published by PyPI
  • vbench-pruna

    Video generation benchmark

    Depends on scikit-learnPyPI

    Not published by PyPI
  • vbench2

    Video generation benchmark

    Depends on scikit-learnPyPI

    Not published by PyPI
  • vectorbt

    Python library for backtesting and analyzing trading strategies at scale

    Depends on scikit-learnPyPI

    Not published by PyPI
  • vectordb-bench

    VectorDBBench is not just an offering of benchmark results for mainstream vector databases and cloud services, it's your go-to tool for the ultimate performance and cost-effectiveness comparison. Designed with ease-of-use in mind, VectorDBBench is devised to help users, even non-professionals, reproduce results or test new systems, making the hunt for the optimal choice amongst a plethora of cloud services and open-source vector databases a breeze.

    Depends on scikit-learnPyPI

    Not published by PyPI
  • vibe-trading-ai

    Natural-language finance research AI agent with backtesting

    Depends on scikit-learnPyPI

    Not published by PyPI
  • vision-agent

    Toolset for Vision Agent

    Depends on scikit-learnPyPI

    Not published by PyPI
  • waymo-open-dataset-tf-2-11-0

    Depends on scikit-learnPyPI

    Not published by PyPI
  • waymo-open-dataset-tf-2-12-0

    Depends on scikit-learnPyPI

    Not published by PyPI
  • weightwatcher

    Diagnostic Tool for Deep Neural Networks

    Depends on scikit-learnPyPI

    Not published by PyPI
  • whereami

    Uses WiFi to tell you where you are

    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.