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First-order and Stochastic Optimization Methods for Machine Learning - Springer Series in the Data Sciences Guanghui Lan 2020 edition
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First-order and Stochastic Optimization Methods for Machine Learning - Springer Series in the Data Sciences
Guanghui Lan
This book covers not only foundational materials but also the most recent progresses made during the past few years on the area of machine learning algorithms.
582 pages, 12 Tables, color; 16 Illustrations, color; 2 Illustrations, black and white; XIII, 582 p.
| Médias | Livres Paperback Book (Livre avec couverture souple et dos collé) |
| Validé | 16 mai 2021 |
| ISBN13 | 9783030395704 |
| Éditeurs | Springer Nature Switzerland AG |
| Pages | 582 |
| Dimensions | 235 × 155 × 35 mm · 888 g |
| Langue et grammaire | Allemand |
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