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| .. | ||
| img | ||
| Backend.qs | ||
| ExploringQuantumClassificationLibrary.ipynb | ||
| InsideQuantumClassifiers.ipynb | ||
| QuantumClassification.csproj | ||
| QuantumClassification.sln | ||
| QuantumClassificationWithFeatureEngineering.ipynb | ||
| README.md | ||
README.md
Welcome!
This folder contains a Notebook tutorial that introduces circuit-centric quantum classification and the QML library included in the Microsoft Quantum Development Kit.
The paper 'Circuit-centric quantum classifiers', by Maria Schuld, Alex Bocharov, Krysta Svore and Nathan Wiebe describes the original proposal behind this type of classifiers.
To run this tutorial, you can install Jupyter and Q# and
qsharp package for Python.
Note that this tutorial requires matplotlib and numpy Python packages to be installed.
After this you can run the tutorial locally by navigating to this folder and starting the notebook from command line using the following command:
jupyter notebook ExploringQuantumClassificationLibrary.ipynb
Alternatively, you can run the tutorial online here. Be warned that this tutorial includes some heavy computations, so we recommend to run it locally and to use the online version only for reading.
The Q# project in this folder contains the back-end of the tutorial and is not designed for direct use.