What is the FedML Tool Assembly?
FedML is an open-source federated learning library designed for research and production. It supports a wide range of FL scenarios, including cross-device, cross-silo, and edge-cloud federated learning. FedML provides flexible APIs, comprehensive benchmarks, and promotes open, collaborative development across domains such as NLP, computer vision, and IoT.
What can you use the FedML Tool Assembly for?
- Research and development in federated learning across diverse domains
- Benchmarking FL algorithms and systems
- Edge-to-cloud FL deployments
- Collaborative, open-source FL projects
Limitations/Remarks
- Complexity for beginners
- Resource-intensive for large-scale experiments
- Dependent on active community engagement
Specific Use Cases/Applications
- FL research in NLP, CV, IoT, and healthcare
- Edge device and cloud-based federated learning
- Large-scale FL benchmarking and simulation
How to access the FedML Tool Assembly?
- Official Documentation
- GitHub Repository
- FedML Platform
- Install via pip:
pip install fedml
References
- FedML Documentation
- He, C. et al. (2020). FedML: A Research Library and Benchmark for Federated Machine Learning. arXiv:2007.13518. PDF
- FedML GitHub
Original Framework Contributors
- Chaoyang He
- FedML Community
For a full list, see the FedML GitHub contributors.
More information
Training
Affiliations Contributors
Editor
KU Leuven / University of UHasselt