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Regularization in Deep Learning
Liu Peng
Regularization in Deep Learning delivers practical techniques to help you build more adaptable deep learning model. Along with exploring strategies for architecture, objective function, and optimisation, you will get just enough of the theory and mathematics behind regularisation to understand the new research emerging in this important area.
275 pages
| Media | Books Paperback Book (Book with soft cover and glued back) |
| Released | October 2, 2023 |
| ISBN13 | 9781633439610 |
| Publishers | Manning Publications |
| Pages | 275 |
| Dimensions | 187 × 235 × 18 mm · 326 g |
| Language | English |
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