MetisFL
Visit ToolMetisFL is an open Federated Learning framework implemented in C++ and Python. It supports scalable, efficient, and secure federated learning workflows for developers.
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MetisFL is an open Federated Learning framework implemented in C++ and Python. It supports scalable, efficient, and secure federated learning workflows for developers.
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About
MetisFL is an open-source Federated Learning framework designed for scalable, efficient, and secure machine learning workflows. Implemented in both C++ and Python, it provides a robust platform for developers to build and deploy federated learning solutions. The framework addresses challenges like library inconsistencies across operating systems by recommending Docker for project execution, offering pre-built Docker images for Ubuntu and RockyLinux, including CUDA-enabled versions. MetisFL emphasizes collaborative AI and federated analytics, making it suitable for scenarios where data privacy and distributed model training are crucial. Its architecture supports advanced machine learning and deep learning applications, providing a foundational tool for researchers and engineers in the AI domain.
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Open Source
Free
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