SMILELab-FL/FedLab-benchmarks
Standard federated learning implementations in FedLab and FL benchmarks.
This project provides standard implementations of federated learning algorithms, allowing researchers and practitioners to compare different approaches using common datasets. It takes in various decentralized datasets and outputs benchmark results and performance metrics for different federated learning models. Researchers and machine learning engineers working on privacy-preserving or distributed AI would use this.
155 stars. No commits in the last 6 months.
Use this if you are a researcher or engineer who needs to evaluate and compare federated learning algorithms across standard datasets.
Not ideal if you are looking for a standalone solution for deploying federated learning models in a production environment, as this is a research benchmarking tool.
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155
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44
Language
Jupyter Notebook
License
Apache-2.0
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Last pushed
Jan 29, 2024
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