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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, a...
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This book aims at providing an introduction to key concepts, algorithms, and theoretical frameworks in machine learning, including supervised and unsupervised learning, statistical learning theory, probabilistic graphica...
