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Tiny Machine Learning Techniques for Constrained Devices
Tiny Machine Learning Techniques for Constrained Devices
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- Condition: Brand new
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- More about Tiny Machine Learning Techniques for Constrained Devices
Format: Hardback
Length: 224 pages
Publication date: 29 January 2026
Publisher: Taylor & Francis Ltd
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.
Weight: 590g
Dimension: 234 x 156 (mm)
ISBN-13: 9781032897523
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