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HPE Swarm Learning is a decentralized, privacy-preserving Machine Learning framework. This ML framework utilizes the computing power at, or near, the distributed data sources to run the Machine Learning algorithms that train the models. It uses the security of a blockchain platform to share learnings with peers in a safe and secure manner. In HPE Swarm Learning, training of the model occurs at the edge, where data is most recent, and where prompt, data-driven decisions are mostly necessary. In this completely decentralized architecture, only the insights learned are shared with the collaborating ML peers, not the raw data. This tremendously enhances data security and privacy.
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With HPE Swarm Learning v2.0.0 release, user can now extend Swarm client to support other machine learning platforms as well. Currently Swarm client supports machine learning platforms like PyTorch and Keras (based on Tensorflow 2 in backend). Please find the instructions to extend Swarm client [here](https://github.com/HewlettPackard/swarm-learning/blob/master/lib/src/README.md).
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## Articles
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<iframewidth="560"height="315"src="https://www.youtube.com/embed/ORujFJ1lVVw"title="YouTube video player"frameborder="0"allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"allowfullscreen></iframe>
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**\- HPE Swarm Learning Demo**
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In this around the IT Block demo, see HPE Swarm Learning in action, bringing machine learning model training to the data source and enabling collaboration across data silos. The example shown in this use case is cred card fraud detection.
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<iframewidth="560"height="315"src="https://www.youtube.com/embed/_LQsalXojSg"title="YouTube video player"frameborder="0"allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"allowfullscreen></iframe>
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## Listen to what the experts are saying
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