What is the IBM Federated Learning Tool Assembly?
IBM Federated Learning is an open-source framework developed by IBM Research. It is highly configurable and extensible, supporting a wide range of machine learning techniques and a comprehensive library of fusion algorithms. IBM FL is designed for enterprise environments with needs for data privacy in supervised, unsupervised, and reinforcement learning projects.
What can you use the IBM Federated Learning Tool Assembly for?
- Enterprise federated learning across diverse ML techniques
- Privacy-preserving supervised, unsupervised, and reinforcement learning
- Customizable fusion algorithms for complex deployments
Limitations/Remarks
- Significant setup and configuration required
- Broad applicability may introduce complexity
Specific Use Cases/Applications
- Enterprise data privacy in ML projects
- Complex, large-scale federated learning deployments
How to access the IBM Federated Learning Tool Assembly?
- Official Documentation
- GitHub Repository
- Install via pip:
pip install ibmfl
References
Original Framework Contributors
- IBM Research
- IBM FL Community
For a full list, see the IBM FL GitHub contributors.
More information
Training
Affiliations Contributors
Editor
KU Leuven / University of UHasselt