Wang / Xu Deep Learning

From Algorithmic Essence to Industrial Practice
1. Auflage 2025
ISBN: 978-0-443-43955-1
Verlag: Elsevier Science & Techn.
Format: EPUB
Kopierschutz: 6 - ePub Watermark

E-Book, Englisch, 250 Seiten

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

Dr Shuhao Wang received his from Tsinghua University; he is a fellow at the Institute for Interdisciplinary Information Sciences at Tsinghua University and is currently the co-founder and CTO of 'Thorough Future.' He has conducted research on data science and artificial intelligence at Baidu, NovuMind, and JD.com. He holds over 20 national patents. Dr. Wang has received several key accolades, such as the '30 New Generation Digital Economy Talents' award at the 2019 Wuzhen Internet Summit and the Year 2022 Fall Asia-Pacific Signal and Information Processing Association Industrial Distinguished Leaders award, and was named one of Alibaba Cloud's 'Seeing New Power' figures of 2022

Autoren/Hrsg.

Wang, Shuhao

Xu, Gang