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

Knowledge Graphs are a structured representation of knowledge that captures relationships between entities. They organise information in a way that allows machines to understand…
Neural Networks are a type of Machine Learning model inspired by the human brain. They are composed of interconnected nodes, or “neurons,” that process…
Backpropagation is a technique used in training Artificial Neural Networks. It involves propagating error information backward through the network, allowing adjustments to be made…
Decision networks, also known as Probabilistic Graphical Models, are a type of AI model that represents uncertain knowledge using a graph structure. Decision Networks…