What is Federated Learning?

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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.

Other Definitions

Unsupervised Learning is a Machine Learning technique where models learn patterns and structures within data without labelled examples. By uncovering hidden relationships and clustering…
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Regression Analysis is a statistical technique used to determine the relationship between independent variables and a dependent variable. By analysing historical data, businesses can…
Expert Systems are AI systems that emulate human expertise in specific domains. By capturing and codifying human knowledge, Expert Systems assist businesses in decision-making,…