Overview
- Introduces readers to deep learning models and algorithms in both theory and practice
- Explores how deep learning methods can be used in various applications and their performance in this regard
- Combines theory and practical applications to explain how to implement high-performance deep learning models and achieves effective learning with MindSpore, Huawei's self-developed deep learning computing framework
Part of the book series: Cognitive Intelligence and Robotics (CIR)
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Table of contents (14 chapters)
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Front Matter
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Back Matter
Keywords
About this book
This book systematically introduces readers to the theory of deep learning and explores its practical applications based on the MindSpore AI computing framework. Divided into 14 chapters, the book covers deep learning, deep neural networks (DNNs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), unsupervised learning, deep reinforcement learning, automated machine learning, device-cloud collaboration, deep learning visualization, and data preparation for deep learning. To help clarify the complex topics discussed, this book includes numerous examples and links to online resources.
Authors and Affiliations
About the author
Chen Lei is a Chair Professor of the Department of Computer Science and Engineering and the Director of the Big Data Institute at Hong Kong University of Science and Technology (HKUST). His research focuses on data-driven AI, human-powered machine learning, knowledge graphs, and data mining on social media. He has published more than 400 papers in world-renowned journals and conference proceedings and won the 2015 SIGMOD Test of Time Award. Currently, he serves as the Editor-in-Chief of the VLDB 2019 Journal, the Associate Editor-in-Chief of the IEEE TKDE Journal, and an executive member of the VLDB Endowment. He is also IEEE Fellow and ACM Distinguished Scientist.
Bibliographic Information
Book Title: Deep Learning and Practice with MindSpore
Authors: Lei Chen
Translated by: Yunhui Zeng
Series Title: Cognitive Intelligence and Robotics
DOI: https://doi.org/10.1007/978-981-16-2233-5
Publisher: Springer Singapore
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Tsinghua University Press 2021
Hardcover ISBN: 978-981-16-2232-8Published: 18 August 2021
Softcover ISBN: 978-981-16-2235-9Published: 19 August 2022
eBook ISBN: 978-981-16-2233-5Published: 17 August 2021
Series ISSN: 2520-1956
Series E-ISSN: 2520-1964
Edition Number: 1
Number of Pages: XVIII, 394
Number of Illustrations: 344 b/w illustrations, 13 illustrations in colour
Topics: Machine Learning, Artificial Intelligence