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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.
| Media | Książki Hardcover Book (Książka z twardym grzbietem i okładką) |
| Wydane | 29 stycznia 2026 |
| ISBN13 | 9781032897523 |
| Wydawcy | Taylor & Francis Ltd |
| Strony | 224 |
| Wymiary | 150 × 220 × 20 mm · 500 g |
| Język | Angielski |
| Redaktor | Abd El-Latif, Ahmed A. |
| Redaktor | El-Makkaoui, Khalid |
| Redaktor | Lamaakal, Ismail |
| Redaktor | Maleh, Yassine |
| Redaktor | Ouahbi, Ibrahim |