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Cracking the Machine Learning Code: Technicality or Innovation? - Studies in Computational Intelligence KC Santosh
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.
| Médias | Livres Paperback Book (Livre avec couverture souple et dos collé) |
| Validé | 10 mai 2025 |
| ISBN13 | 9789819727223 |
| Éditeurs | Springer Verlag, Singapore |
| Pages | 127 |
| Dimensions | 150 × 220 × 10 mm · 236 g |
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