sQUlearn/squlearn
scikit-learn interface for quantum algorithms
This project helps quantum machine learning researchers and practitioners experiment with and prototype quantum algorithms. It takes various quantum data encoding strategies and machine learning models as input, and outputs trained quantum models ready for evaluation. This is for users exploring quantum kernel methods and quantum neural networks for practical machine learning applications.
103 stars. Available on PyPI.
Use this if you are a QML researcher or practitioner looking to integrate quantum algorithms seamlessly with classical machine learning tools like scikit-learn.
Not ideal if you need a production-ready, validated, or verified software for commercial applications, as this is for research and experimental purposes only.
Stars
103
Forks
26
Language
Python
License
Apache-2.0
Category
Last pushed
Feb 23, 2026
Commits (30d)
0
Dependencies
15
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