Tiny Machine Learning by Agbotiname Lucky Imoize (.ePUB)+
File Size: 45.3 MB
Tiny Machine Learning: Design Principles and Applications by Agbotiname Lucky Imoize, Dinh-Thuan Do, Houbing Herbert Song
Requirements: .ePUB, .PDF reader, 45.3 MB | True PDF, True EPUB
Overview: 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. Perfect for industry and academic researchers, scientists, and engineers, Tiny Machine Learning will also benefit lecturers and graduate students interested in machine learning.
Genre: Non-Fiction > Tech & Devices
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