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Mathematical Aspects of Deep Learning New edition
Mathematical Aspects of Deep Learning
The development of a theoretical foundation for deep learning methods constitutes one of the most active and exciting research topics in applied mathematics. Written by leading experts in the field, this book acts as a mathematical introduction to deep learning for researchers and graduate students trying to get into the field.
485 pages, Worked examples or Exercises
| Medios de comunicación | Libros Hardcover Book (Libro con lomo y cubierta duros) |
| Publicado | 22 de diciembre de 2022 |
| ISBN13 | 9781316516782 |
| Editores | Cambridge University Press |
| Páginas | 492 |
| Dimensiones | 250 × 177 × 29 mm · 1,07 kg |
| Lengua | Inglés |
| Editor | Grohs, Philipp (Universitat Wien, Austria) |
| Editor | Kutyniok, Gitta (Ludwig-Maximilians-Universitat Munchen) |