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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

Cloud Computing

Cloud computing provides on-demand access to shared computing resources, including storage, processing power, and software applications, over the internet. By leveraging cloud computing, businesses…

Deep Reinforcement Learning

Deep Reinforcement Learning is a subset of Machine Learning that combines Deep Learning and Reinforcement Learning. It involves training AI models to make decisions…

Word Embeddings

Word Embeddings are a technique in NLP that represent words as continuous vectors in a high-dimensional space. These vectors capture semantic and syntactic relationships…

Adversarial Machine Learning

Adversarial machine learning involves studying and defending AI models against attacks or adversarial examples designed to deceive the system. By understanding vulnerabilities and deploying…
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