Quantum Machine Learning

<P>This book presents the research into and application of machine learning in quantum computation, known as quantum machine learning (QML). It presents a comparison of quantum machine learning, classical machine learning, and traditional programming, along with the usage of quantum computing, toward improving traditional machine learning algorithms through case studies.</P><P>In summary, the book:</P><UL><P><LI>Covers the core and fundamental aspects of statistics, quantum learning, and quantum machines.</LI><P></P><P><LI>Discusses the basics of machine learning, regression, supervised and unsupervised machine learning algorithms, and artificial neural networks.</LI><P></P><P><LI>Elaborates upon quantum machine learning models, quantum machine learning approaches and quantum classification, and boosting.</LI><P></P><P><LI>Introduces quantum evaluation models, deep quantum learning, ensembles, and QBoost.</LI><P></P><P><LI>Presents case studies to demonstrate the efficiency of quantum mechanics in industrial aspects.</LI><P></P></UL><P></P><P>This reference text is primarily written for scholars and researchers working in the fields of computer science and engineering, information technology, electrical engineering, and electronics and communication engineering.</P><P></P><P></P>