Model Optimization Methods for Efficient and Edge AI
Model Optimization Methods for Efficient and Edge AI:
Federated Learning Architectures, Frameworks and Applications
English | 2025 | ISBN: 1394219210 | 398 Pages | PDF, EPUB (True) | 29 MB
Federated Learning Architectures, Frameworks and Applications
English | 2025 | ISBN: 1394219210 | 398 Pages | PDF, EPUB (True) | 29 MB
Model Optimization Methods for Efficient and Edge AI explores AI model engineering, evaluation, refinement, optimization, and deployment across multiple cloud environments (public, private, edge, and hybrid). It presents key applications of the AI paradigm, including computer vision (CV) and Natural Language Processing (NLP), explaining the nitty-gritty of federated learning (FL) and how the FL method is helping to fulfill AI model optimization needs. The book also describes tools that vendors have created, including FL frameworks and platforms such as PySyft, Tensor Flow Federated (TFF), FATE (Federated AI Technology Enabler), Tensor/IO, and more.