A library for quantum machine learning following the sklearn standard.
Project description
sQUlearn 0.2.0
Note: This is an early access version! Not everything that is described is already working 100%.
Prerequisites
The package requires at least Python 3.9.
Installation
Stable Release
To install the stable release version of sQUlearn, run the following command:
pip install squlearn
Alternatively, you can install sQUlearn directly from GitHub via
pip install git+ssh://git@github.com:sQUlearn/squlearn.git
Examples
There are several more elaborate examples available in the folder ./examples
which display the features of this package.
Tutorials for beginners can be found at ./examples/tutorials
.
To install the required packages, run
pip install .[examples]
Contribution
Thanks for considering to contribute to sQUlearn! Please read our contribution guidelines before you submit a pull request.
License
Imprint
This project is maintained by the quantum computing group at the Fraunhofer Institute for Manufacturing Engineering and Automation IPA. It started as a collection of implementations of quantum machine learning methods.
http://www.ipa.fraunhofer.de/quantum
Project details
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