Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing 1

Data & IT

Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing

Sudeep Pasricha • Muhammad Shafique

Pocket

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571 sidor
2024

This book presents recent advances towards thegoal ofenabling efficient implementation ofmachine learning models onresource-constrained systems, covering different application domains. Thefocus is onpresenting interesting and new use cases ofapplying machine learning toinnovative application domains, exploring theefficient hardware design ofefficient machine learning accelerators, memory optimization techniques, illustrating model compression and neural architecture search techniques forenergy-efficient and fast execution on resource-constrained hardware platforms, and understanding hardware-software codesign techniques forachieving even greater energy, reliability, and performance benefits. Discusses efficient implementation ofmachine learning in embedded, CPS, IoT, and edge computing; Offers comprehensive coverage ofhardware design, software design, and hardware/software co-design and co-optimization; Describes real applications todemonstrate how embedded, CPS, IoT, and edge applications benefit frommachine learning.

Författare: Sudeep Pasricha, Muhammad Shafique
Format: Pocket/Paperback
ISBN: 9783031406799
Språk: Engelska
Antal sidor: 571
Utgivningsdatum: 2024-10-08
Förlag: Springer International Publishing AG