qiskit-community/qiskit-machine-learning

Health v2 · maintenance only

Adoption not part of the score

1096 stars · 448 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Qiskit Machine Learning is an open-source Python library built on the Qiskit SDK that provides building blocks for quantum machine learning, including quantum kernels and quantum neural networks. It supports classification, regression, and other ML tasks on both quantum hardware and classical simulators.

Use cases

• train a quantum neural network classifier on a dataset
• run quantum kernel methods like QSVC for classification
• build hybrid quantum-classical models with PyTorch
• prototype quantum machine learning research experiments
• simulate quantum ML algorithms without quantum hardware
• implement a quantum autoencoder or quantum convolutional neural network

When to choose

• you want to experiment with quantum machine learning in Python
• you already use Qiskit and need ML building blocks
• you need quantum kernels or quantum neural networks with simulator or hardware backends
• you want PyTorch integration for hybrid quantum-classical models

When to avoid

• you need classical machine learning with no quantum component
• you need production-scale ML performance today rather than research prototyping
• you work outside the Qiskit/Python quantum ecosystem

Facets

library · maturity active

machine-learning sdk machine-learning quantum-computing python quantum-computing quantum-machine-learning qiskit quantum-neural-networks quantum-kernels

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markdown · JSON · MCP: product_card(name="qiskit-community/qiskit-machine-learning")