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Tiny Machine Learning Techniques for Constrained Devices
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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 | Böcker Inbunden Bok (Inbunden bok med hårda pärmar och skyddsomslag) |
| Releasedatum | 29 januari 2026 |
| ISBN13 | 9781032897523 |
| Utgivare | Taylor & Francis Ltd |
| Antal sidor | 224 |
| Mått | 150 × 220 × 20 mm · 500 g |
| Språk | Engelska |
| Redaktör | Abd El-Latif, Ahmed A. |
| Redaktör | El-Makkaoui, Khalid |
| Redaktör | Lamaakal, Ismail |
| Redaktör | Maleh, Yassine |
| Redaktör | Ouahbi, Ibrahim |
