This book provides a holistic overview of all aspects of federated AI, which allows creation of real-world applications in contexts where data is dispersed in many different locations.
This book provides a holistic overview of all aspects of federated AI, which allows creation of real-world applications in contexts where data is dispersed in many different locations.
Dinesh C. Verma is an IBM Fellow, a UK Fellow of the Royal Academy of Engineering and an IEEE Fellow. He leads the Distributed AI area at IBM Watson Research Center. He has authored ten books, 150+ technical papers and been granted 185+ U.S. patents. He has led an international consortium of scientists for fifteen years, and supervised many business solutions using AI. More details about Dinesh are available at ibm.biz/dineshverma
Inhaltsangabe
1. Introduction to Artificial Intelligence. 2. Scenarios for Federated AI. 3. Naive Federated Learning Approaches. 4. Addressing Data Mismatch Issues in Federated AI. 5. Addressing Data Skew Issues in Federated Learning. 6. Addressing Trust Issues in Federated Learning. 7. Addressing Synchronization Issues in Federated Learning. 8. Addressing Vertical Partitioning Issues in Federated Learning. 9. Use Cases.
