03532cam a2200505 i 4500 9781003482000 FlBoTFG 20251030122252.0 m o d cr cnu---unuuu 241119s2025 flua ob 001 0 eng OCoLC-P eng rda OCoLC-P 9781003482000 electronic book 1003482007 electronic book 9781040266694 electronic book 104026669X electronic book 9781032771649 hardcover 9781032772462 paperback (OCoLC)1472989443 (OCoLC-P)1472989443 TA347.A78 A879 2025 Artificial intelligence using federated learning : fundamentals, challenges, and applications / edited by Ahmed A. Elngar, Diego Oliva and Valentina E. Balas. First edition. Boca Raton, FL : CRC Press, 2025. 1 online resource (xiv, 294 pages) : illustrations (chiefly color). text txt rdacontent computer c rdamedia online resource cr rdacarrier Intelligent manufacturing and industrial engineering Blockchain-enhanced federated learning for privacy-preserving collaboration / Pawan Whig, Balaram Yadav Kasula, Nikhitha Yathiraju, Anupriya Jain, Seema Sharma and Ahmed A. Elngar -- In-depth analysis of artificial intelligence practices : robot tutors and federated learning approach in english education / Muthmainnah, Akkarapon Nuemaihom, Ahmad Al Yakin, Prodhan Mahbub Ibna Seraj, Muhammad Mujtaba Asad and Ahmed A. Elngar -- Enabling federated learning in the classroom : sociotechnical ecosystem on artificial intelligence integration in educational practices / Ahmad Al Yakin, Arkas Viddy, Idi Warsah, Ali Said Al Matari, Luís Cardoso, Ahmed A. Elngar, Ahmad J. Obaid and Muthmainnah . "Federated machine learning is a novel approach to combining distributed machine learning, cryptography, security, and incentive mechanism design. It allows organizations to keep sensitive and private data on users or customers decentralized and secure, helping them comply with stringent data protection regulations like GDPR and CCPA. The book is designed for researchers working in Intelligent Federated Learning and its related applications, as well as technology development, and is also of interest to academicians, data scientists, industrial professionals, researchers, and students"-- Provided by publisher. OCLC-licensed vendor bibliographic record. Artificial intelligence Industrial applications. 65268 Artificial intelligence Security measures. 95048 Federated learning (Machine learning) 94903 Privacy-preserving techniques (Computer science) 95049 Elngar, Ahmed A., editor. https://id.oclc.org/worldcat/entity/E39PCjwHFXCGdYr9yxWCHFDtTd 95050 Oliva, Diego, editor. https://id.oclc.org/worldcat/entity/E39PCjGMQ9tcvGpw34yRgm87gX 95051 Balas, Valentina Emilia, editor. https://id.oclc.org/worldcat/entity/E39PBJjCPfdqQJyMpDymx8gdwC 64218 Taylor & Francis https://www.taylorfrancis.com/books/9781003482000 OCLC metadata license agreement http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf E-Books 67957 67957