Rich with insights into the ethical and social implications of federated learning, this book addresses the pressing challenges and future directions that are critical for its evolution. Topics such as privacy preservation, bias mitigation, and regulatory compliance are thoroughly examined, offering a holistic view of how federated learning can be applied responsibly and effectively. Whether you're a researcher, practitioner, or policy-maker, "Essential Federated Learning: AI at the Edge" offers the essential knowledge needed to harness the advantages of this cutting-edge technology, ensuring readers are well-equipped to navigate the rapidly expanding landscape of AI and edge computing.
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