This repository has been archived. Please refer to the tutorial on quantum classification with Q# for the latest version of the tutorial.
This repository contains the materials for the "Introduction to Quantum Classification" lab presented at Spring 2020 MLADS Conference. In this lab you will experiment with a simple circuit-centric quantum classifier using the Microsoft Quantum Development Kit.
You can run the lab online on Binder.
Running this lab on Binder is very slow, so if you prefer to run the lab online we recommend you to read through the notebook using saved cell outputs before attempting to run the cells.
Alternatively, 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 that you can run the tutorial locally by navigating to the QuantumClassification folder and starting the notebook from command line using the following command:
jupyter notebook ExploringQuantumClassificationLibrary.ipynb
The Q# project in this folder contains the back-end of the tutorial and is not designed for direct use.
Here are some resources to get you started:
- Install Microsoft Quantum Development Kit and Q# Jupyter Notebooks
- Learn the basics of quantum computing and Q# using the Quantum Katas
- Check out Microsoft Quantum documentation, in particular introduction to quantum machine learning
- 'Circuit-centric quantum classifiers', by Maria Schuld, Alex Bocharov, Krysta Svore and Nathan Wiebe describes the original proposal behind this type of classifiers.
This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.
When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.