<ul><li>Federated Learning is a decentralized approach to machine learning that allows models to be trained across multiple devices.</li><li>Federated learning addresses concerns around privacy, data security, and regulatory compliance.</li><li>It enhances privacy by keeping raw data on users' devices, minimizing the risk of data breaches.</li><li>Federated learning reduces data transfer costs and enables personalized machine learning models without compromising privacy.</li></ul>

Federated Learning: The Future of Privacy-Preserving Machine Learning

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