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 Title: An Introduction to Quantum Machine Learning for Engineers
 Author(s) Osvaldo Simeone
 Publisher: Now Publishers (July 27, 2022); eBook (arxiv.org, 2022)
 License(s): arXiv.org  Nonexclusive license to distribute
 Hardcover/Paperback: N/A
 eBook: PDF (240 pages), PostScript. DVI, etc.
 Language: English
 ISBN10: 1638280584
 ISBN13: 9781638280583
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Book Description
This monograph provides a selfcontained introduction to Quantum Machine Learning for an audience of engineers with a background in probability and linear algebra. It first describes the necessary background, concepts, and tools necessary to describe quantum operations and measurements. Then, it covers parametrized quantum circuits, the variational quantum eigensolver, as well as unsupervised and supervised quantum machine learning formulations.
About the Authors Osvaldo Simeone is a Professor of Information Engineering in the Department of Informatics, King's College, London, UK.
 Machine Learning
 Quantum Computing
 Neural Networks and Deep Learning
 Artificial Intelligence
 Data Analysis and Data Mining
 An Introduction to Quantum Machine Learning for Engineers (Osvaldo Simeone)
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