Federated Learning Client-Side Implementation

The client-side modules of a federated learning (FL) system can be implemented based on the system architecture, sequence, and procedure flow, as discussed in Chapter 3, Workings of the Federated Learning System. FL client-side functionalities can connect distributed machine learning (ML) applications that conduct local training and testing with an aggregator, through a communications module embedded in the client-side libraries.

In the example of using the FL client libraries in a local ML engine, the minimal engine package example will be discussed, with dummy ML models to understand the process of integration with the FL client libraries that are designed in this chapter. By following the example code about integration, you will understand how to actually enable the whole process related to the FL client side, as discussed in Chapter 3, Workings of the Federated Learning System, while an analysis on what will happen with the minimal...