Deep learning : from algorithmic essence to industrial practice /
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 netwo...
| Main Authors: | , |
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| Corporate Author: | |
| Format: | eBook |
| Language: | English |
| Published: |
Amsterdam, Netherlands ; Oxford, United Kingdom ; Cambridge MA :
Elsevier,
[2025]
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| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Summary: | 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. |
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| Physical Description: | 1 online resource (250 pages) |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 0443439559 9780443439551 |