Deep Learning: From Algorithmic Essence to Industrial Practice (Paperback) (ISBN-13: 9780443439544)

Deep Learning: From Algorithmic Essence to Industrial Practice introduces the fundamental theories of deep learning, engineering practices, and their deployment and application in the industry. This book provides a detailed explanation of classic convolutional neural networks, recurrent neural networks, and transformer networks based on self-attention mechanisms, along with their variants, combining code demonstrations. Additionally, this book covers the applications of these models in areas including image classification, object detection, and semantic segmentation. This book also considers advancements in deep reinforcement learning and generative adversarial networks making it suitable for graduate and senior undergraduate students with backgrounds in computer science, automation, electronics, communications, mathematics, and physics, as well as professional technical personnel who wish to work or are preparing to transition into the field of artificial intelligence
The code for book may be accessed by visiting the companion website: https: //www.
elsevier.com/books-and-journals/book-companion/9780443439544

Author: Shuhao Wang, Gang Xu
ISBN-10: 0443439540
ISBN-13: 9780443439544
Publisher: Elsevier
Language: English
Published: 07/28/2025
Pages: 472
Format: Paperback