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Cracking the Machine Learning Code: Technicality or Innovation? - Studies in Computational Intelligence KC Santosh 2024 edition
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其他版本:
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.
127 pages, 103 Illustrations, color; 7 Illustrations, black and white; XIX, 127 p. 110 illus., 103 i
| 介质类型 | 图书 Hardcover Book (精装硬皮书) |
| 已发行 | 2024年5月9日 |
| ISBN13 | 9789819727193 |
| 出版商 | Springer Verlag, Singapore |
| 页数 | 127 |
| 商品尺寸 | 150 × 220 × 20 mm · 385 g |