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Nerlnet is an open-source framework for researching distributed machine learning algorithms on IoT devices. It provides comprehensive insights into both edge devices that run neural network models and network performance and statistics. Nerlnet can simulate distributed ML clusters on a single or multiple machines and deploy these clusters, with minor changes, on various kinds of IoT devices.
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Nerlnet is an open-source framework for research and deployment of distributed machine learning algorithms on IoT devices. It provides comprehensive insights into both edge devices that run neural network models and network performance and statistics. Nerlnet can simulate distributed ML clusters on a single or multiple machines and deploy these clusters, with minor changes, on various kinds of IoT devices.
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Nerlnet simplifies the setup of a distributed cluster that consists of many models on its edge, communication flow can be fully controlled and monitored, and Nerlnet's Python API allows users to manage and gather data from the distributed cluster throughout the experiment.
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