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Flower Makes Federated Learning Shockingly Simple
The framework provides a simple, lightweight and developer friendly programming model for implementing federated learning pipelines in a few lines of code.
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Federated learning is one of the dominant machine learning architectures for distributed systems such as mobile or IOT technologies. Despite its popularity, implementing federated learning applications remains a challenge involving very complex models and interactions between nodes. Recently, a new open source framework called Flower was released with a shockingly simple programming model for federated learning architectures.
