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Tiny Machine Learning Techniques for Constrained Devices
Tiny Machine Learning Techniques for Constrained Devices
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.
| 介质类型 | 图书 Hardcover Book (精装硬皮书) |
| 已发行 | 2026年1月29日 |
| ISBN13 | 9781032897523 |
| 出版商 | Taylor & Francis Ltd |
| 页数 | 224 |
| 商品尺寸 | 150 × 220 × 20 mm · 590 g |
| 语言 | 英语 |
| 编辑 | Abd El-Latif, Ahmed A. |
| 编辑 | El-Makkaoui, Khalid |
| 编辑 | Lamaakal, Ismail |
| 编辑 | Maleh, Yassine |
| 编辑 | Ouahbi, Ibrahim |