Isbn: 9783030830977 - machine learning with quantum computers (quantum science and technology) (21 resultados)

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Hardback. Condición: New. Second Edition 2021. 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 understand how quantum computers can learn from data. Among the topics discussed are parameterized quantum circuits, hybrid optimization, data encoding, quantum feature maps and kernel methods, quantum learning theory, as well as quantum neural networks. The book aims at an audience of computer scientists and physicists at the graduate level onwards. The second edition extends the material beyond supervised learning and puts a special focus on the developments in near-term quantum machine learning seen over the past few years.…

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 understand how quantum computers can learn from data. Among the topics discussed are parameterizedquantum circuits, hybrid optimization, data encoding, quantum feature maps and kernel methods, quantum learning theory, as well as quantum neural networks.The book aimsat an audience of computer scientists and physicists at the graduate level onwards.The second edition extends the material beyond supervised learning and puts a special focus on the developments in near-term quantum machine learning seen over the past few years.…

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Hardcover. Condición: Brand New. 2nd edition. 326 pages. 9.25x6.10x0.91 inches. In Stock.

Hardback. Condición: New. Second Edition 2021. 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 understand how quantum computers can learn from data. Among the topics discussed are parameterized quantum circuits, hybrid optimization, data encoding, quantum feature maps and kernel methods, quantum learning theory, as well as quantum neural networks. The book aims at an audience of computer scientists and physicists at the graduate level onwards. The second edition extends the material beyond supervised learning and puts a special focus on the developments in near-term quantum machine learning seen over the past few years.…

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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 understand how quantum computers can learn from data. Among the topics discussed are parameterizedquantum circuits, hybrid optimization, data encoding, quantum feature maps and kernel methods, quantum learning theory, as well as quantum neural networks.The book aimsat an audience of computer scientists and physicists at the graduate level onwards.The second edition extends the material beyond supervised learning and puts a special focus on the developments in near-term quantum machine learning seen over the past few years. 328 pp. Englisch.…

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 understand how quantum .…

Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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 understand how quantum computers can learn from data. Among the topics discussed are parameterized quantum circuits, hybrid optimization, data encoding, quantum feature maps and kernel methods, quantum learning theory, as well as quantum neural networks. The book aims at an audience of computer scientists and physicists at the graduate level onwards.The second edition extends the material beyond supervised learning and puts a special focus on the developments in near-term quantum machine learning seen over the past few years.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 328 pp. Englisch.…