Deep Learning

From Algorithmic Essence to Industrial Practice

Shuhao Wang, Gang Xu

• Publisher: Elsevier
• Year: 2025
• eBook ISBN: 9780443439551
• Edition: 0
• Topic: Technology & Engineering
• Subtopic: Engineering General
• Index: Technology & Engineering

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 intelligenceThe code for book may be accessed by visiting the companion website: https://www.elsevier.com/books-and-journals/book-companion/9780443439544 - Provides in-depth explanations and practical code examples for the latest deep learning architectures, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformers - Examines theoretical concepts and the engineering practices required for deploying deep learning models in real-world scenarios - Covers the use of distributed systems for training and deploying models - Includes detailed case studies and applications of deep learning models in various domains including image classification, object detection, and semantic segmentation

Table of contents

• Front Cover
• Deep Learning: From Algorithmic Essence to Industrial Practice
• Deep Learning: From Algorithmic Essence to Industrial Practice
• Copyright
• Contents
• About the authors
• Preface
• Overview
• 1 - Neural networks∗
• 2 - Convolutional neural networks—Image classification and object detection∗
• 3 - Convolutional neural networks—Semantic segmentation∗
• 4 - Recurrent neural networks∗
• 5 - Distributed deep learning systems∗
• 6 - Frontiers of deep learning∗
• 7 - Special lectures∗
• 8 - Transformer and its companions∗
• 9 - Core practices∗
• 10 - Deep learning inference systems∗
• Index
• Back Cover