Isbn: 9781032552323 - quantum machine learning: a modern approach (7 resultados)

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Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
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Quantum Machine Learning: A Modern Approach
Karthikeyan, S (Editor)/ Poongodi, T (Editor)/ Akila, M (Editor)/ Sumathi, D. (Editor)
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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Paperback. Condición: Brand New. 288 pages. 6.14x0.63x9.21 inches. In Stock.

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Condición: New. Dr. Karthikeyan Saminathan is currently working as an Associate Professor(Research) in the Department of Cyber Security at Sri Venkateshwara College of Engineering, Bengaluru, Karnataka, India and He is associated with Bluechip CyberTech.

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Taschenbuch. Condición: Neu. Neuware - 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.In summary, the book: - Covers the core and fundamental aspects of statistics, quantum learning, and quantum machines. - Discusses the basics of machine learning, regression, supervised and unsupervised machine learning algorithms, and artificial neural networks. - Elaborates upon quantum machine learning models, quantum machine learning approaches and quantum classification, and boosting. - Introduces quantum evaluation models, deep quantum learning, ensembles, and QBoost. - Presents case studies to demonstrate the efficiency of quantum mechanics in industrial aspects. 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.…

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Paperback. Condición: new. Paperback. 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.In summary, the book: Covers the core and fundamental aspects of statistics, quantum learning, and quantum machines. Discusses the basics of machine learning, regression, supervised and unsupervised machine learning algorithms, and artificial neural networks. Elaborates upon quantum machine learning models, quantum machine learning approaches and quantum classification, and boosting. Introduces quantum evaluation models, deep quantum learning, ensembles, and QBoost. Presents case studies to demonstrate the efficiency of quantum mechanics in industrial aspects.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. This text 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. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…