This book provides a comprehensive introduction to continual and reinforcement learning for edge AI, which investigates how to build an AI agent that can continuously solve new learning tasks and enhance the AI at resource-limited edge devices. The authors introduce readers to practical frameworks and in-depth algorithmic foundations. The book surveys the recent advances in the area, coming from both academic researchers and industry professionals. The authors also present their own research findings on continual and reinforcement learning for edge AI. The book also covers the practical applications of the topic and identifies exciting future research opportunities.
This book provides a comprehensive introduction to continual and reinforcement learning for edge AI, which investigates how to build an AI agent that can continuously solve new learning tasks and enhance the AI at resource-limited edge devices. The authors introduce readers to practical frameworks and in-depth algorithmic foundations. The book surveys the recent advances in the area, coming from both academic researchers and industry professionals. The authors also present their own research findings on continual and reinforcement learning for edge AI. The book also covers the practical applications of the topic and identifies exciting future research opportunities.
This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it.This work is in the "public domain in the United States of...
If you want to learn Reinforcement Learning, then this is the book for you!#1 BOOK ABOUT MACHINE LEARNINGDo you struggle to learn and understand how AI learns? Have you watched a...
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