Dive into Deep Learning
| Verlag | Cambridge University Press |
| Auflage | 2023 |
| Seiten | 574 |
| Format | 22,7 x 2,4 x 25,4 cm |
| Gewicht | 1380 g |
| Artikeltyp | Englisches Buch |
| EAN | 9781009389433 |
| Bestell-Nr | 00938943UA |
An approachable text combining the depth and quality of a textbook with the interactive multi-framework code of a hands-on tutorial.
Klappentext:
Deep learning has revolutionized pattern recognition, introducing tools that power a wide range of technologies in such diverse fields as computer vision, natural language processing, and automatic speech recognition. Applying deep learning requires you to simultaneously understand how to cast a problem, the basic mathematics of modeling, the algorithms for fitting your models to data, and the engineering techniques to implement it all. This book is a comprehensive resource that makes deep learning approachable, while still providing sufficient technical depth to enable engineers, scientists, and students to use deep learning in their own work. No previous background in machine learning or deep learning is required-every concept is explained from scratch and the appendix provides a refresher on the mathematics needed. Runnable code is featured throughout, allowing you to develop your own intuition by putting key ideas into practice.
Inhaltsverzeichnis:
Installation; Notation; 1. Introduction; 2. Preliminaries; 3. Linear neural networks for regression; 4. Linear neural networks for classification; 5. Multilayer perceptrons; 6. Builders guide; 7. Convolutional neural networks; 8. Modern convolutional neural networks; 9. Recurrent neural networks; 10. Modern recurrent neural networks; 11. Attention mechanisms and transformers; Appendix. Tools for deep learning; Bibliography; Index.
Rezension:
'In less than a decade, the AI revolution has swept from research labs to broad industries to every corner of our daily life. Dive into Deep Learning is an excellent text on deep learning and deserves attention from anyone who wants to learn why deep learning has ignited the AI revolution: the most powerful technology force of our time.' Jensen Huang, Founder and CEO, NVIDIA