Federated Learning is a privacy-preserving technique where AI models are trained across multiple decentralised devices or systems without sharing raw data. Instead, only aggregated model updates are exchanged, ensuring data privacy and security. Federated Learning enables businesses to harness the collective intelligence of distributed devices while maintaining data confidentiality.
Dimensionality Reduction is the process of reducing the number of variables or features in a dataset while retaining its essential information. By eliminating irrelevant…