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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

One-Shot Learning

One-Shot learning is an AI approach that enables models to learn from only one or a few examples. This approach is advantageous in tasks…

Ensemble Learning

Ensemble Learning involves combining multiple Machine Learning models to achieve superior performance and accuracy. By leveraging the “wisdom of the crowd,” Ensemble Learning mitigates…

Transfer Learning

Transfer Learning is a technique that allows AI models to apply knowledge gained from one task to another related task. By leveraging pre-trained models…

Recommender Systems

Recommender Systems are AI systems that provide personalised recommendations to users based on their preferences and previous behaviour. These systems analyse large amounts of…
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