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"item_title" : "Tiny Machine Learning Techniques for Constrained Devices",
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Tiny Machine Learning Techniques for Constrained Devices
Overview
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.
This item is Non-Returnable
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Details
- ISBN-13: 9781032897523
- ISBN-10: 103289752X
- Publisher: CRC Press
- Publish Date: January 2026
- Dimensions: 9.21 x 6.14 x 0.56 inches
- Shipping Weight: 1.11 pounds
- Page Count: 224
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