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

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

Software Optimizations and Hardware/Software Codesign

Limbă: engleză
Legare: Carte broșată
Editura: Springer, Berlin
Disponibilitate: În depozitul extern
Expediem în 5-8 zile
756.63 lei
This book presents recent advances towards the goal of enabling efficient implementation of machine...

Informații despre carte

Limbă
engleză
Legare
Carte - Carte broșată
Publicat
2024
Pagini
477
EAN
9783031399343
Enbook ID
46677792
Greutate
739
Dimensiuni
155 x 235

Descriere completă

This book presents recent advances towards the goal of enabling efficient implementation of machine learning models on resource-constrained systems, covering different application domains. The focus is on presenting interesting and new use cases of applying machine learning to innovative application domains, exploring the efficient hardware design of efficient machine learning accelerators, memory optimization techniques, illustrating model compression and neural architecture search techniques for energy-efficient and fast execution on resource-constrained hardware platforms, and understanding hardware-software codesign techniques for achieving even greater energy, reliability, and performance benefits.

  • Discusses efficient implementation of machine learning in embedded, CPS, IoT, and edge computing;
  • Offers comprehensive coverage of hardware design, software design, and hardware/software co-design and co-optimization;
  • Describes real applications todemonstrate how embedded, CPS, IoT, and edge applications benefit from machine learning.

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