scikit-learnvs
PyTorch
PyTorch: Deep learning framework preferred when models need neural networks or GPU acceleration
scikit-learn
Machine learning in Python
As of 30 August 2026, scikit-learn is free to use. scikit-learn is a free, open-source machine learning library for Python. Softwr lists it under Machine Learning. scikit-learn is made by scikit-learn Community, launched in 2007, available on API, Linux, macOS, Windows.
Overview
What scikit-learn does
scikit-learn is a free, open-source machine learning library for Python. It features various classification, regression, and clustering algorithms including support vector machines, random forests, gradient boosting, and k-means. Built on NumPy, SciPy, and matplotlib, it provides simple and efficient tools for data analysis.
What people use it for
- Machine learning
- Data analysis
- Model training
- Predictive analytics
The honest half
Where it falls short
Concrete and checkable, so you can decide whether any of them matter to you. This is the half of a review a vendor will not write about scikit-learn.
- No GPU acceleration by default; limited optional GPU support requires external arrays
- Single-machine only; no built-in distributed computing across clusters
- All datasets must fit entirely in RAM; no out-of-core learning
- No production-grade deep learning; neural network support limited to basic multilayer perceptron
- No reinforcement learning algorithms
Cross-shopped
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Capabilities
Features
Classification algorithms
Regression models
Clustering methods
Dimensionality reduction
Model selection
NumPy
Integration with NumPy
SciPy
Integration with SciPy
Pandas
Integration with Pandas
Matplotlib
Integration with Matplotlib
Linux support
Available on linux
Mac support
Available on mac
Windows support
Available on windows
Answered, with sources
Questions people ask
Each answer names the page it came from, so you can check it rather than take our word for it.
Does scikit-learn support GPU acceleration?
Scikit-learn has no native GPU support by design to keep installation simple and cross-platform. Since 2023, a limited number of estimators can run on GPUs if input data is provided as PyTorch or CuPy arrays, but this requires additional setup.
SourceCan scikit-learn handle datasets larger than RAM?
No. Scikit-learn is built on NumPy which requires all data to fit in memory, and NumPy operates on single-machine CPUs only. For very large datasets, consider Spark MLlib or distributed alternatives.
SourceIs scikit-learn free to use commercially?
Yes. Scikit-learn is open source under the BSD license, which allows free commercial use, modification, and distribution.
SourceWhat neural network capabilities does scikit-learn have?
Scikit-learn includes only a basic multilayer perceptron (MLPClassifier and MLPRegressor) for simple feedforward networks. For serious deep learning, use PyTorch, TensorFlow, or Keras instead.
SourceDoes scikit-learn include natural language processing?
Scikit-learn has minimal NLP support limited to basic text feature extraction and vectorization. For comprehensive text processing, use spaCy or NLTK instead.
SourceWhen was scikit-learn first released?
Scikit-learn's first public release was February 1, 2010, following its start as a Google Summer of Code project in 2007.
SourceBehind it
Who makes scikit-learn
- Company
- scikit-learn Community
- Based in
- Open Source Community
Timeline
scikit-learn over time
- Launch2025-12-10
Version 1.8 released with native Array API support enabling GPU computations via PyTorch and CuPy
Source - Funding2022-01-01
NVIDIA began funding core maintainer Tim Head; Quansight Labs began funding Lucy Liu
Source - Funding2020-01-01
Microsoft began funding core maintainer Andreas Müller
Source - Milestone2019-01-01
Received Inria-French Academy of Sciences-Dassault Systèmes Innovation Prize
Source - Funding2018-01-01
Seven-company Scikit-learn Consortium established including Microsoft, Intel, AXA, and BNP Paribas
Source - Milestone2011-01-01
Published in Journal of Machine Learning Research by Pedregosa et al.
Source - Launch2010-02-01
First public release with leadership from INRIA researchers
Source - Founded2007-01-01
Started as Google Summer of Code project by David Cournapeau
Source
Keep looking
Where to go from scikit-learn
- scikit-learn alternativesEvery product people weigh against it
- scikit-learn pricingPlans, floors and what the tiers exclude
- scikit-learn badgesWhich rules it meets, and the figure behind each
- All Machine Learning softwareThe full category
- Best Machine Learning softwareThe shortlist, and how it was cut
Best Machine Learning software for
Compare scikit-learn with
- Keras
- PyTorch
- Apache Spark MLlib
- H2O.ai
- Weka
- BigQuery ML
- Jupyter
- Python
- Anaconda
- AWS SageMaker
- ClearML
- Cohere
- Dask
- Fal AI
- Groq
- TensorFlow
- Google Vertex AI
- BigQuery ML
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