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Cracking the Machine Learning Code: Technicality or Innovation? - Studies in Computational Intelligence KC Santosh
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Cracking the Machine Learning Code: Technicality or Innovation? - Studies in Computational Intelligence
KC Santosh
It typically includes model selection, parameter tuning and optimization, use of pre-trained models and transfer learning, right use of limited data, model interpretability and explainability, feature engineering and autoML robustness and security, and computational cost – efficiency and scalability.
| Medios de comunicación | Libros Paperback Book (Libro con tapa blanda y lomo encolado) |
| Publicado | 10 de mayo de 2025 |
| ISBN13 | 9789819727223 |
| Editores | Springer Verlag, Singapore |
| Páginas | 127 |
| Dimensiones | 150 × 220 × 10 mm · 236 g |
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