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## Implementation of [Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge](https://arxiv.org/abs/1804.08333)
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- Implemented paper - “Client selection strategy for Federated Learning with Heterogeneous Resources on mobile edge”
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- It is a decentralised learning framework that enables privacy preserving training of ML models for heterogeneous clients on practical networks.
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- Wrote unit tests for various components of Envisedge - a deployment library for recommendation engines with Edge Computing. [github](https://github.com/NimbleEdge/EnvisEdge)
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