Titlebook: Machine Learning with Quantum Computers; Maria Schuld,Francesco Petruccione Book 2021Latest edition The Editor(s) (if applicable) and The

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https://doi.org/10.1007/978-3-030-83098-4Hidden Markov Models; Deep Belief Network; Grover Search; Hopfield Model; Artificial Neural Network; Qsam

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Variational Circuits as Machine Learning Models,We explain how parametrised quantum circuits—quantum algorithms that are popular in near-term quantum computing—can be used as machine learning models, and review techniques to analyse and train such quantum models in a deep-learning fashion, including measures of expressivity and trainability, as well as parameter-shift rules.

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978-3-030-83100-4The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

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Machine Learning with Quantum Computers978-3-030-83098-4Series ISSN 2364-9054 Series E-ISSN 2364-9062

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2364-9054 me in the literature.Focuses on the developments in near-ter.This book offers an introduction into quantum machine learning research, covering approaches that range from "near-term" to fault-tolerant quantum machine learning algorithms, and from theoretical to practical techniques that help us under

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