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Añadir al carritoCondición: New. pp.176 Reprint edition NO-PA16APR2015-KAP.
Idioma: Inglés
Publicado por Elsevier Science Publishing Co Inc, 2016
ISBN 10: 0128100400 ISBN 13: 9780128100400
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Añadir al carritoPaperback / softback. Condición: New. New copy - Usually dispatched within 4 working days.
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Añadir al carritoCondición: New. pp.176.
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Publicado por Elsevier Science Publishing Co Inc, US, 2016
ISBN 10: 0128100400 ISBN 13: 9780128100400
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Añadir al carritoPaperback. Condición: New. Quantum Machine Learning bridges the gap between abstract developments in quantum computing and the applied research on machine learning. Paring down the complexity of the disciplines involved, it focuses on providing a synthesis that explains the most important machine learning algorithms in a quantum framework. Theoretical advances in quantum computing are hard to follow for computer scientists, and sometimes even for researchers involved in the field. The lack of a step-by-step guide hampers the broader understanding of this emergent interdisciplinary body of research. Quantum Machine Learning sets the scene for a deeper understanding of the subject for readers of different backgrounds. The author has carefully constructed a clear comparison of classical learning algorithms and their quantum counterparts, thus making differences in computational complexity and learning performance apparent. This book synthesizes of a broad array of research into a manageable and concise presentation, with practical examples and applications.
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Añadir al carritoCondición: New. Bridges the gap between abstract developments in quantum computing with the applied research on machine learning Provides the theoretical minimum of machine learning, quantum mechanics, and quantum computing Gives step-by-step gui.
Idioma: Inglés
Publicado por Elsevier Science Publishing Co Inc, US, 2016
ISBN 10: 0128100400 ISBN 13: 9780128100400
Librería: Rarewaves.com UK, London, Reino Unido
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Añadir al carritoPaperback. Condición: New. Quantum Machine Learning bridges the gap between abstract developments in quantum computing and the applied research on machine learning. Paring down the complexity of the disciplines involved, it focuses on providing a synthesis that explains the most important machine learning algorithms in a quantum framework. Theoretical advances in quantum computing are hard to follow for computer scientists, and sometimes even for researchers involved in the field. The lack of a step-by-step guide hampers the broader understanding of this emergent interdisciplinary body of research. Quantum Machine Learning sets the scene for a deeper understanding of the subject for readers of different backgrounds. The author has carefully constructed a clear comparison of classical learning algorithms and their quantum counterparts, thus making differences in computational complexity and learning performance apparent. This book synthesizes of a broad array of research into a manageable and concise presentation, with practical examples and applications.
Librería: preigu, Osnabrück, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. Quantum Machine Learning | What Quantum Computing Means to Data Mining | Peter Wittek | Taschenbuch | Einband - fest (Hardcover) | Englisch | 2016 | Elsevier Inc | EAN 9780128100400 | Verantwortliche Person für die EU: Zeitfracht Medien GmbH, Ferdinand-Jühlke-Str. 7, 99095 Erfurt, produktsicherheit[at]zeitfracht[dot]de | Anbieter: preigu.
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Añadir al carritoPaperback. Condición: Brand New. reprint edition. 176 pages. 8.75x5.75x0.50 inches. In Stock. This item is printed on demand.
Idioma: Inglés
Publicado por Elsevier Science Publishing Co Inc, 2016
ISBN 10: 0128100400 ISBN 13: 9780128100400
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Añadir al carritoPaperback / softback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
Idioma: Inglés
Publicado por Elsevier Science & Technology, Academic Press, 2016
ISBN 10: 0128100400 ISBN 13: 9780128100400
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Quantum Machine Learning bridges the gap between abstract developments in quantum computing and the applied research on machine learning. Paring down the complexity of the disciplines involved, it focuses on providing a synthesis that explains the most important machine learning algorithms in a quantum framework. Theoretical advances in quantum computing are hard to follow for computer scientists, and sometimes even for researchers involved in the field. The lack of a step-by-step guide hampers the broader understanding of this emergent interdisciplinary body of research. Quantum Machine Learning sets the scene for a deeper understanding of the subject for readers of different backgrounds. The author has carefully constructed a clear comparison of classical learning algorithms and their quantum counterparts, thus making differences in computational complexity and learning performance apparent. This book synthesizes of a broad array of research into a manageable and concise presentation, with practical examples and applications. Englisch.
Idioma: Inglés
Publicado por Elsevier Science & Technology, Academic Press, 2016
ISBN 10: 0128100400 ISBN 13: 9780128100400
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 150,79
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Quantum Machine Learning bridges the gap between abstract developments in quantum computing and the applied research on machine learning. Paring down the complexity of the disciplines involved, it focuses on providing a synthesis that explains the most important machine learning algorithms in a quantum framework. Theoretical advances in quantum computing are hard to follow for computer scientists, and sometimes even for researchers involved in the field. The lack of a step-by-step guide hampers the broader understanding of this emergent interdisciplinary body of research. Quantum Machine Learning sets the scene for a deeper understanding of the subject for readers of different backgrounds. The author has carefully constructed a clear comparison of classical learning algorithms and their quantum counterparts, thus making differences in computational complexity and learning performance apparent. This book synthesizes of a broad array of research into a manageable and concise presentation, with practical examples and applications.