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Opis

This book will present recent advances towards the goal of enabling efficient implementation of machine learning models on resource-constrained systems, covering different application domains. The focus will be 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.

Szczegóły książki

Kategoria Książki po angielsku Computing & information technology Computer hardware Embedded systems

• Pełny tytuł: Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing
• Autor: Sudeep Pasricha, Muhammad Shafique
• Język: Angielski
• Oprawa: Twarda
• Liczba stron: 592
• EAN: 9783031195679
• ID: 41551453
• Wydawca: Springer, Berlin
• Wymiary: 235 × 155 mm
• Rok wydania: 2023

Ulubione w innej kategorii

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