Design and implement the Decentralized Federated Learning solution employing a FedAvg of a Linear Regression machine learning model that classifies hand-written images of numbers in the MNIST dataset using PyTorch and Ray Train. This DFL solution will be deployed on a Data Mesh of CATs’ Data Products:

• Report a classification performance of Federated Averaged Linear Regression model (e.g. Accuracy, Precision, etc.)
• Integration test the CAT Factory using the CAT Invoice produced as a result of this Milestone to execute a CAT with a deterministic process confirming the idempotency of CATs by reproducing the same dataset

This deliverable involves the design and implementation of a Decentralized Federated Learning (DFL) solution employing a FedAvg of a Linear Regression machine learning model that classifies hand-written images of numbers in the MNIST dataset using PyTorch and Ray Train. This DFL solution will be deployed on a Data Mesh of CATs’ Data Products.
0. Design DFL Solution

1. Performance report of Federated Averaged Linear Regression machine learning model using Accuracy and Precision
2. Documentation: Provide installation and execution examples with descriptions