vantage6

A privacy preserving federated learning solution

Release PyPI vantage6 Unittests Coverage Status Codacy Badge DOI

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to learn more!

📚 Documentation

This repository is home to 4 PyPi packages:

Note that when using vantage6 you do not install the server and node packages. These are delivered to you in Docker images.

Two docker images are published which contain the Node and Server applications:

  • harbor2.vantage6.ai/infrastructure/node:VERSION
  • harbor2.vantage6.ai/infrastructure/server:VERSION

These docker images are used by the vantage6 CLI package, which can be installed by running:

pip install vantage6

This will install the CLI which enables you to use the commands:

  • vnode CMD [OPTIONS]
  • vserver CMD [OPTIONS]

You can find more (user) documentation at Gitbook (docs.vantage6.ai). If you have any questions, suggestions or just want to chat about federated learning: join our Dircord (https://discord.gg/yAyFf6Y) channel.

💝 Contributing

We hope to continue developing, improving, and supporting vantage6 with the help of the federated learning community. If you are interested in contributing, first of all, thank you! Second, please take a look at our contributing guidelines

✒️ References

If you are using vantage6, please cite this repository as well as the accompanying paper as follows:

  • Frank Martin, Melle Sieswerda, Hasan Alradhi, et al. vantage6. Available at https://doi.org/10.5281/zenodo.3686944. Accessed on [MONTH, 20XX].
  • Arturo Moncada-Torres, Frank Martin, Melle Sieswerda, Johan van Soest, Gijs Gelijnse. VANTAGE6: an open source priVAcy preserviNg federaTed leArninG infrastructurE for Secure Insight eXchange. AMIA Annual Symposium Proceedings, 2020, p. 870-877. [BibTeX, PDF]

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GitHub

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