Like a failed communist state traditional machine learning centralises training of a model on a single machine. Centralising data in a single central location is not always possible for a variety of reasons such as slow network connections, and legal constraints. These limitations have produced a series of techniques that allow the decentralised training of a model. This collection of techniques is referred to as Federated Machine Learning. Read More

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