QizGloria

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Qiskit Camp Europe 2019 (winning project)

QizGloria 최신버젼 다운로드

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# QizGloria: hybrid quantum-classical ML with full Qiskit & PyTorch capabilities

Winning contribution for Qiskit Camp Europe 2019

Team: Amira Abbas (@amyami187), Isaac Turtletaub (@iturtle100), Patrick Huembeli (@patrickhuembeli), Karel Dumon (@dumkar), Samuel Bosch (@BoschSamuel).

IBM Coach: Christa Zoufal (@Zoufalc)

We are building a tight integration of Qiskit capabilities with PyTorch. One may seamlessly use tools from both frameworks with integrated functionality. We have included some basic tutorials to illustrate the framework.

Our "Hello World!" notebook involves training parameters for a 1-qubit rotation, in order to attain a target expectation value. The specified cost function is the mean squared error and the chosen torch optimiser is Adam.

UPDATE: this project has been integrated in the Qiskit Open Source Textbook. Have a look over [there](https://qiskit.org/textbook/ch-machine-learning/machine-learning-qiskit-pytorch.html) for cleaned code and extended explanations!

![qizgloria-front](https://raw.githubusercontent.com/BoschSamuel/QizGloria/master/qizgloria-front.JPG)

QizGloria

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