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An Introduction to Quantum Machine Learning for Engineers
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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 - Non-exclusive license to distribute
  • Hardcover/Paperback: N/A
  • eBook: PDF (240 pages), PostScript. DVI, etc.
  • Language: English
  • ISBN-10: 1638280584
  • ISBN-13: 978-1638280583
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Book Description

This monograph provides a self-contained 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.
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