https://github.com/davitacols/building-a-variational-quantum-classifier-in-python-with-qiskit
This project demonstrates how to build a Variational Quantum Classifier (VQC) using Qiskit. VQCs combine parameterized quantum circuits with classical optimization to classify data into categories. The workflow includes quantum data encoding, circuit design (using the RyRz ansatz), hybrid optimization, and result evaluation.
https://github.com/davitacols/building-a-variational-quantum-classifier-in-python-with-qiskit
classifier qiskit quantum-computing variational variational-autoencoder
Last synced: 10 months ago
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This project demonstrates how to build a Variational Quantum Classifier (VQC) using Qiskit. VQCs combine parameterized quantum circuits with classical optimization to classify data into categories. The workflow includes quantum data encoding, circuit design (using the RyRz ansatz), hybrid optimization, and result evaluation.
- Host: GitHub
- URL: https://github.com/davitacols/building-a-variational-quantum-classifier-in-python-with-qiskit
- Owner: davitacols
- License: apache-2.0
- Created: 2023-04-16T05:41:31.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2024-12-09T14:07:51.000Z (over 1 year ago)
- Last Synced: 2024-12-09T15:22:04.774Z (over 1 year ago)
- Topics: classifier, qiskit, quantum-computing, variational, variational-autoencoder
- Language: Python
- Homepage: https://github.com/davitacols/Building-a-Variational-Quantum-Classifier-in-Python-with-Qiskit.git
- Size: 22.5 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files: