Federated Learning Server Implementation with Python
The server-side implementation of a federated learning (FL) system is critical for realizing authentic FL-enabled applications. We have discussed the basic system architecture and flow in the previous chapter. In this chapter, more hands-on implementation will be discussed so that you can create a simple server and aggregator of the FL system that various machine learning (ML) applications can be connected to and tested on.
This chapter describes an actual implementation aspect of FL server-side components discussed in Chapter 3, Workings of the Federated Learning System. Based on the understanding of how the entire process of the FL system works, you will be able to go one step further to make it happen with example code provided here and on GitHub. Once you understand the basic implementation principles using the example code, it is a fun aspect to be able enhance the FL server functionalities based on your own design.
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