IBM Federated Learning
Federated Learning provides the tools for multiple remote parties to collaboratively train a single machine learning model without sharing data. Each party trains a local model with a private data set. Only the local model is sent to the aggregator to improve the quality of the global model that benefits all parties.
- Federated Learning tutorials and samples
- Get started
- Frameworks, fusion methods, and Python versions
- Creating a Federated Learning experiment
- Configure the party yml file
Parent topic: Analyzing data and building models