• 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.

• Osvaldo Simeone is a Professor of Information Engineering in the Department of Informatics, King's College, London, UK.

• Amazon

• 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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