9789819512836 - a gentle introduction to quantum machine learning de du, yuxuan; wang, xinbiao; guo, naixu; yu, zhan; qian, yang; zhang, kaining; hsieh, min-hsiu; rebentrost, patrick; tao, dacheng (30 resultados)
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Hardback or Cased Book. Condición: New. A Gentle Introduction to Quantum Machine Learning. Book.
A Gentle Introduction to Quantum Machine Learning
Du, Yuxuan; Wang, Xinbiao; Guo, Naixu; Yu, Zhan; Qian, Yang; Zhang, Kaining; Hsieh, Min-Hsiu; Rebentrost, Patrick; Tao, Dacheng
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Hardcover. Condición: new. Hardcover. Quantum machine learning (QML) is revolutionizing artificial intelligence by leveraging the power of quantum computing to access previously unimaginable computational possibilities. However, the field remains fragmentedbalancing rigorous quantum theory with practical AI applications remains…a challenge. This book bridges this gap, offering a systematic, hands-on guide for AI researchers, ML practitioners, and computer scientists eager to explore this emerging frontier. It provides a cohesive roadmap, covering everything from fundamental quantum computing principles to state-of-the-art QML techniques. Readers will explore quantum kernel methods, quantum neural networks, and quantum Transformers, gaining insight into their theoretical foundations, performance advantages, and practical implementations. The books code demonstrations offer hands-on experience, ensuring that readers can move beyond theory to real-world applications.Designed for those with an AI or ML background, this tutorial does not assume prior expertise in quantum computing. Instead, it presents complex concepts with clarity, making it an essential resource for researchers, graduate students, and industry professionals eager to stay ahead in the quantum AI revolution. Whether you seek to understand quantum speedups, develop quantum-based models, or explore future research directions, this book provides the foundation you need to engage with QML and shape the future of intelligent computing. Readers will explore quantum kernel methods, quantum neural networks, and quantum Transformers, gaining insight into their theoretical foundations, performance advantages, and practical implementations. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Hardback. Condición: New. Quantum machine learning (QML) is revolutionizing artificial intelligence by leveraging the power of quantum computing to access previously unimaginable computational possibilities. However, the field remains fragmented-balancing rigorous quantum theory with practical AI applications remains a challenge…. This book bridges this gap, offering a systematic, hands-on guide for AI researchers, ML practitioners, and computer scientists eager to explore this emerging frontier. It provides a cohesive roadmap, covering everything from fundamental quantum computing principles to state-of-the-art QML techniques. Readers will explore quantum kernel methods, quantum neural networks, and quantum Transformers, gaining insight into their theoretical foundations, performance advantages, and practical implementations. The book's code demonstrations offer hands-on experience, ensuring that readers can move beyond theory to real-world applications.Designed for those with an AI or ML background, this tutorial does not assume prior expertise in quantum computing. Instead, it presents complex concepts with clarity, making it an essential resource for researchers, graduate students, and industry professionals eager to stay ahead in the quantum AI revolution. Whether you seek to understand quantum speedups, develop quantum-based models, or explore future research directions, this book provides the foundation you need to engage with QML and shape the future of intelligent computing.
A Gentle Introduction to Quantum Machine Learning
Du, Yuxuan; Wang, Xinbiao; Guo, Naixu; Yu, Zhan; Qian, Yang; Zhang, Kaining; Hsieh, Min-Hsiu; Rebentrost, Patrick; Tao, Dacheng
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A Gentle Introduction to Quantum Machine Learning
Du, Yuxuan; Wang, Xinbiao; Guo, Naixu; Yu, Zhan; Qian, Yang; Zhang, Kaining; Hsieh, Min-Hsiu; Rebentrost, Patrick; Tao, Dacheng
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A Gentle Introduction to Quantum Machine Learning
Du, Yuxuan; Wang, Xinbiao; Guo, Naixu; Yu, Zhan; Qian, Yang; Zhang, Kaining; Hsieh, Min-Hsiu; Rebentrost, Patrick; Tao, Dacheng
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Hardback. Condición: New. Quantum machine learning (QML) is revolutionizing artificial intelligence by leveraging the power of quantum computing to access previously unimaginable computational possibilities. However, the field remains fragmented-balancing rigorous quantum theory with practical AI applications remains a challenge…. This book bridges this gap, offering a systematic, hands-on guide for AI researchers, ML practitioners, and computer scientists eager to explore this emerging frontier. It provides a cohesive roadmap, covering everything from fundamental quantum computing principles to state-of-the-art QML techniques. Readers will explore quantum kernel methods, quantum neural networks, and quantum Transformers, gaining insight into their theoretical foundations, performance advantages, and practical implementations. The book's code demonstrations offer hands-on experience, ensuring that readers can move beyond theory to real-world applications.Designed for those with an AI or ML background, this tutorial does not assume prior expertise in quantum computing. Instead, it presents complex concepts with clarity, making it an essential resource for researchers, graduate students, and industry professionals eager to stay ahead in the quantum AI revolution. Whether you seek to understand quantum speedups, develop quantum-based models, or explore future research directions, this book provides the foundation you need to engage with QML and shape the future of intelligent computing.
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Hardcover. Condición: new. Hardcover. Quantum machine learning (QML) is revolutionizing artificial intelligence by leveraging the power of quantum computing to access previously unimaginable computational possibilities. However, the field remains fragmentedbalancing rigorous quantum theory with practical AI applications remains…a challenge. This book bridges this gap, offering a systematic, hands-on guide for AI researchers, ML practitioners, and computer scientists eager to explore this emerging frontier. It provides a cohesive roadmap, covering everything from fundamental quantum computing principles to state-of-the-art QML techniques. Readers will explore quantum kernel methods, quantum neural networks, and quantum Transformers, gaining insight into their theoretical foundations, performance advantages, and practical implementations. The books code demonstrations offer hands-on experience, ensuring that readers can move beyond theory to real-world applications.Designed for those with an AI or ML background, this tutorial does not assume prior expertise in quantum computing. Instead, it presents complex concepts with clarity, making it an essential resource for researchers, graduate students, and industry professionals eager to stay ahead in the quantum AI revolution. Whether you seek to understand quantum speedups, develop quantum-based models, or explore future research directions, this book provides the foundation you need to engage with QML and shape the future of intelligent computing. Readers will explore quantum kernel methods, quantum neural networks, and quantum Transformers, gaining insight into their theoretical foundations, performance advantages, and practical implementations. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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A Gentle Introduction to Quantum Machine Learning
Du, Yuxuan; Wang, Xinbiao; Guo, Naixu; Yu, Zhan; Qian, Yang; Zhang, Kaining; Hsieh, Min-Hsiu; Rebentrost, Patrick; Tao, Dacheng
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Hardcover. Condición: new. Hardcover. Quantum machine learning (QML) is revolutionizing artificial intelligence by leveraging the power of quantum computing to access previously unimaginable computational possibilities. However, the field remains fragmentedbalancing rigorous quantum theory with practical AI applications remains…a challenge. This book bridges this gap, offering a systematic, hands-on guide for AI researchers, ML practitioners, and computer scientists eager to explore this emerging frontier. It provides a cohesive roadmap, covering everything from fundamental quantum computing principles to state-of-the-art QML techniques. Readers will explore quantum kernel methods, quantum neural networks, and quantum Transformers, gaining insight into their theoretical foundations, performance advantages, and practical implementations. The books code demonstrations offer hands-on experience, ensuring that readers can move beyond theory to real-world applications.Designed for those with an AI or ML background, this tutorial does not assume prior expertise in quantum computing. Instead, it presents complex concepts with clarity, making it an essential resource for researchers, graduate students, and industry professionals eager to stay ahead in the quantum AI revolution. Whether you seek to understand quantum speedups, develop quantum-based models, or explore future research directions, this book provides the foundation you need to engage with QML and shape the future of intelligent computing. Readers will explore quantum kernel methods, quantum neural networks, and quantum Transformers, gaining insight into their theoretical foundations, performance advantages, and practical implementations. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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A Gentle Introduction to Quantum Machine Learning
Du, Yuxuan; Wang, Xinbiao; Guo, Naixu; Yu, Zhan; Qian, Yang; Zhang, Kaining; Hsieh, Min-Hsiu; Rebentrost, Patrick; Tao, Dacheng
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Quantum machine learning (QML) is revolutionizing artificial intelligence by leveraging the power of quantum computing to access previously unimaginable computational possibilities. However, the field remains fragmented balancing rigorous…quantum theory with practical AI applications remains a challenge. This book bridges this gap, offering a systematic, hands-on guide for AI researchers, ML practitioners, and computer scientists eager to explore this emerging frontier.It provides a cohesive roadmap, covering everything from fundamental quantum computing principles to state-of-the-art QML techniques. Readers will explore quantum kernel methods, quantum neural networks, and quantum Transformers, gaining insight into their theoretical foundations, performance advantages, and practical implementations. The book s code demonstrations offer hands-on experience, ensuring that readers can move beyond theory to real-world applications.Designed for those with an AI or ML background, this tutorial does not assume prior expertise in quantum computing. Instead, it presents complex concepts with clarity, making it an essential resource for researchers, graduate students, and industry professionals eager to stay ahead in the quantum AI revolution. Whether you seek to understand quantum speedups, develop quantum-based models, or explore future research directions, this book provides the foundation you need to engage with QML and shape the future of intelligent computing. 228 pp. Englisch.
A Gentle Introduction to Quantum Machine Learning
Du, Yuxuan; Wang, Xinbiao; Guo, Naixu; Yu, Zhan; Qian, Yang; Zhang, Kaining; Hsieh, Min-Hsiu; Rebentrost, Patrick; Tao, Dacheng
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Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Quantum machine learning (QML) is revolutionizing artificial intelligence by leveraging the power of quantum computing to access previously unimaginable computational possibilities. However, the field remains fragmentedbalancing rigorous quant…um theory with practical AI applications remains a challenge. This book bridges this gap, offering a systematic, hands-on guide for AI researchers, ML practitioners, and computer scientists eager to explore this emerging frontier.It provides a cohesive roadmap, covering everything from fundamental quantum computing principles to state-of-the-art QML techniques. Readers will explore quantum kernel methods, quantum neural networks, and quantum Transformers, gaining insight into their theoretical foundations, performance advantages, and practical implementations. The book's code demonstrations offer hands-on experience, ensuring that readers can move beyond theory to real-world applications.Designed for those with an AI or ML background, this tutorial does not assume prior expertise in quantum computing. Instead, it presents complex concepts with clarity, making it an essential resource for researchers, graduate students, and industry professionals eager to stay ahead in the quantum AI revolution. Whether you seek to understand quantum speedups, develop quantum-based models, or explore future research directions, this book provides the foundation you need to engage with QML and shape the future of intelligent computing.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 228 pp. Englisch.
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Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Quantum machine learning (QML) is revolutionizing artificial intelligence by leveraging the power of quantum computing to access previously unimaginable computational possibilities. However, the field remains fragmented balancing rigorous quant…um theory with practical AI applications remains a challenge. This book bridges this gap, offering a systematic, hands-on guide for AI researchers, ML practitioners, and computer scientists eager to explore this emerging frontier.It provides a cohesive roadmap, covering everything from fundamental quantum computing principles to state-of-the-art QML techniques. Readers will explore quantum kernel methods, quantum neural networks, and quantum Transformers, gaining insight into their theoretical foundations, performance advantages, and practical implementations. The book s code demonstrations offer hands-on experience, ensuring that readers can move beyond theory to real-world applications.Designed for those with an AI or ML background, this tutorial does not assume prior expertise in quantum computing. Instead, it presents complex concepts with clarity, making it an essential resource for researchers, graduate students, and industry professionals eager to stay ahead in the quantum AI revolution. Whether you seek to understand quantum speedups, develop quantum-based models, or explore future research directions, this book provides the foundation you need to engage with QML and shape the future of intelligent computing.
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Buch. Condición: Neu. A Gentle Introduction to Quantum Machine Learning | Yuxuan Du (u. a.) | Buch | xvi | Englisch | 2025 | Springer | EAN 9789819512836 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
