Tiny Machine Learning Techniques for Constrained Devices - - Books - Taylor & Francis Ltd - 9781032897523 - January 29, 2026
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Tiny Machine Learning Techniques for Constrained Devices

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Tiny Machine Learning Techniques for Constrained Devices explores the cutting-edge field of TinyML, enabling intelligent machine learning on highly resource-limited devices such as microcontrollers and edge IoT nodes. It is a guide to designing, optimizing, securing, and applying TinyML models in real-world constrained environments.

Media Books     Hardcover Book   (Book with hard spine and cover)
Released January 29, 2026
ISBN13 9781032897523
Publishers Taylor & Francis Ltd
Pages 224
Dimensions 150 × 220 × 20 mm   ·   590 g
Language English  
Editor Abd El-Latif, Ahmed A.
Editor El-Makkaoui, Khalid
Editor Lamaakal, Ismail
Editor Maleh, Yassine
Editor Ouahbi, Ibrahim