Tiny Machine Learning: Design Principles and Applications



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Wiley-IEEE Press


Paru le : 2026-01-05



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Description

An expert compilation of on-device training techniques, regulatory frameworks, and ethical considerations of TinyML design and development
In Tiny Machine Learning: Design Principles and Applications, a team of distinguished researchers delivers a comprehensive discussion of the critical concepts, design principles, applications, and relevant issues in Tiny Machine Learning (TinyML). Expert contributors introduce a new low power resource, offering vast applications in IoT devices with system-algorithm co-design.
Tiny Machine Learning explores TinyML paradigms and enablers, TinyML for anomaly detection, and the learning panorama under TinyML. Readers will find explanations of TinyML devices and tools, power consumption and memory in IoT microcontrollers, and lightweight frameworks for TinyML. The book also describes TinyML techniques for real-time and environmental applications.
Additional topics covered in the book include: A thorough introduction to security and privacy techniques for TinyML devices, including the implementation of novel security schemesIncisive explorations of power consumption and memory in IoT MCUs, including ultralow-power smart IoT devices with embedded TinyMLPractical discussions of TinyML research targeting microcontrollers for data extraction and synthesis
Perfect for industry and academic researchers, scientists, and engineers, Tiny Machine Learning will also benefit lecturers and graduate students interested in machine learning.
Pages
784 pages
Collection
n.c
Parution
2026-01-05
Marque
Wiley-IEEE Press
EAN papier
9781394294541
EAN PDF
9781394294565

Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
784
Taille du fichier
10906 Ko
Prix
135,88 €
EAN EPUB
9781394294558

Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
784
Taille du fichier
34683 Ko
Prix
135,88 €

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