qiskit-machine-learning and pyRiemann-qiskit
These are ecosystem siblings within the Qiskit ecosystem: qiskit-machine-learning provides core quantum ML algorithms built directly on Qiskit, while pyRiemann-qiskit is a specialized extension that brings Riemannian geometry methods from pyRiemann to quantum circuits via Qiskit's infrastructure.
About qiskit-machine-learning
qiskit-community/qiskit-machine-learning
An open-source library built on Qiskit for quantum machine learning tasks at scale on quantum hardware and classical simulators
This library helps quantum machine learning researchers and practitioners design and experiment with machine learning models that leverage quantum computing principles. It takes classical datasets as input and produces classification or regression models that can run on quantum hardware or simulators. Users are typically quantum algorithm developers or scientists exploring the cutting edge of quantum AI.
About pyRiemann-qiskit
pyRiemann/pyRiemann-qiskit
A library for machine learning and quantum programming based on pyRiemann and Qiskit projects
This tool helps researchers and engineers in Brain-Computer Interfaces (BCI) and EEG analysis by applying quantum machine learning to interpret brainwave data. It takes in EEG signals, processes them using advanced mathematical techniques, and outputs classifications that can reveal patterns related to brain states or responses. The end-users are scientists and practitioners working with neural data who want to explore cutting-edge quantum algorithms for complex pattern recognition.
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