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Federated Machine Learning
Federated machine learning aims at training a machine learning (ML) algorithm on multiple local datasets contained in local nodes without the explicit sharing of data samples. Federated ML helps to protect privacy, enables ML and specifically deep neural networks (DNNs) to use more data, resolves data transfer bottlenecks, and empowers collaborative learning for better accuracy.
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