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The Federated Learning module in MEDomicsLab is the third component of the development layer, responsible for conducting federated learning training. Federated learning allows multiple parties to collaboratively train a shared machine learning model without sharing their raw data. This module facilitates decentralized model training across distributed datasets while preserving data privacy and security. It enables researchers and developers to build, optimize, and deploy federated learning models efficiently within the MEDomicsLab platform.
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For more information on federated learning, you can read more here and explore this article from Google AI Blog.