quantum-machine-learning

quantum-machine-learning

maximer-v

This is an exploration using synthetic data in CSV format to apply QML models for the sake of binary classification. You can find here three different approaches. Two with Qiskit (VQC and QK/SVC) and one with Pennylane (QVC).

14 Stars
5 Forks
14 Watchers
Jupyter Notebook Language
Cost to Build
$2.6K
Market Value
$2.6K

Growth over time

4 data points  ·  2022-05-01 → 2023-07-01
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What is the maximer-v/quantum-machine-learning GitHub project? Description: "This is an exploration using synthetic data in CSV format to apply QML models for the sake of binary classification. You can find here three different approaches. Two with Qiskit (VQC and QK/SVC) and one with Pennylane (QVC).". Written in Jupyter Notebook. Explain what it does, its main use cases, key features, and who would benefit from using it.

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