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Da: GreatBookPricesUK, Woodford Green, Regno Unito
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Da: Books Puddle, New York, NY, U.S.A.
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Da: Biblios, Frankfurt am main, HESSE, Germania
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Aggiungi al carrelloCondizione: New. Dr. Syed Nisar Hussain Bukhari is an accomplished academician and researcher, currently serving as Scientist D at the National Institute of Electronics and Information Technology (NIELIT), Srinagar, an institute under the Ministry of Electronics a.
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Aggiungi al carrelloHardcover. Condizione: Brand New. 348 pages. 9.18x6.12x9.45 inches. In Stock.
Lingua: Inglese
Editore: Taylor & Francis Ltd Apr 2026, 2026
ISBN 10: 1041136625 ISBN 13: 9781041136620
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 375,45
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Aggiungi al carrelloBuch. Condizione: Neu. Neuware - In the exploration of new frontiers in data-driven solutions, the potential of quantum-enhanced machine learning has become too important to overlook. Quantum machine learning, though still in its formative stages, holds the promise to tackle some of the most complex problems that lie beyond the reach of classical computing. Quantum Machine Learning: Concepts, Algorithms, and Applications is a guide to understanding such quantum principles as superposition and entanglement and how they can enhance learning algorithms and data-processing capabilities. The book features a carefully structured progression from foundational concepts and core algorithms to application-driven case studies and emerging directions for future exploration.
Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2026
ISBN 10: 1041136625 ISBN 13: 9781041136620
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condizione: new. Hardcover. In the exploration of new frontiers in data-driven solutions, the potential of quantum-enhanced machine learning has become too important to overlook. Quantum machine learning, though still in its formative stages, holds the promise to tackle some of the most complex problems that lie beyond the reach of classical computing. Quantum Machine Learning: Concepts, Algorithms, and Applications is a guide to understanding such quantum principles as superposition and entanglement and how they can enhance learning algorithms and data-processing capabilities. The book features a carefully structured progression from foundational concepts and core algorithms to application-driven case studies and emerging directions for future exploration.The book provides a broad and in-depth treatment of topics ranging from quantum data encoding and quantum neural networks to hybrid models and optimization frameworks. Emphasis has also been placed on real-world use cases and the practical tools available for implementation, thereby ensuring that this book serves not only as a reference but also as a springboard for experimentation and innovation. Highlights include the following:Implementing quantum neural networks on near-term quantum hardwareQuantum variational optimization for machine learningQuantum-accelerated neural imputations with large language modelsEmerging trends, addressing hardware limitations, algorithm optimization, and ethical considerationsThis book serves as both a primer and an advanced guide by providing essential knowledge for understanding and implementing quantum-enhanced AI solutions in various professional contexts. It equips readers to become active participants in the quantum revolution transforming machine learning. The book explores quantum computing's transformative impact on artificial intelligence and machine learning. Beyond theoretical knowledge, the book emphasizes practical implementation and offers code samples and real-world case studies. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2026
ISBN 10: 1041136625 ISBN 13: 9781041136620
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Aggiungi al carrelloHardcover. Condizione: new. Hardcover. In the exploration of new frontiers in data-driven solutions, the potential of quantum-enhanced machine learning has become too important to overlook. Quantum machine learning, though still in its formative stages, holds the promise to tackle some of the most complex problems that lie beyond the reach of classical computing. Quantum Machine Learning: Concepts, Algorithms, and Applications is a guide to understanding such quantum principles as superposition and entanglement and how they can enhance learning algorithms and data-processing capabilities. The book features a carefully structured progression from foundational concepts and core algorithms to application-driven case studies and emerging directions for future exploration.The book provides a broad and in-depth treatment of topics ranging from quantum data encoding and quantum neural networks to hybrid models and optimization frameworks. Emphasis has also been placed on real-world use cases and the practical tools available for implementation, thereby ensuring that this book serves not only as a reference but also as a springboard for experimentation and innovation. Highlights include the following:Implementing quantum neural networks on near-term quantum hardwareQuantum variational optimization for machine learningQuantum-accelerated neural imputations with large language modelsEmerging trends, addressing hardware limitations, algorithm optimization, and ethical considerationsThis book serves as both a primer and an advanced guide by providing essential knowledge for understanding and implementing quantum-enhanced AI solutions in various professional contexts. It equips readers to become active participants in the quantum revolution transforming machine learning. The book explores quantum computing's transformative impact on artificial intelligence and machine learning. Beyond theoretical knowledge, the book emphasizes practical implementation and offers code samples and real-world case studies. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
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Aggiungi al carrelloHRD. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Da: PBShop.store US, Wood Dale, IL, U.S.A.
EUR 294,32
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Aggiungi al carrelloHRD. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2026
ISBN 10: 1041136625 ISBN 13: 9781041136620
Da: AussieBookSeller, Truganina, VIC, Australia
EUR 373,65
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Aggiungi al carrelloHardcover. Condizione: new. Hardcover. In the exploration of new frontiers in data-driven solutions, the potential of quantum-enhanced machine learning has become too important to overlook. Quantum machine learning, though still in its formative stages, holds the promise to tackle some of the most complex problems that lie beyond the reach of classical computing. Quantum Machine Learning: Concepts, Algorithms, and Applications is a guide to understanding such quantum principles as superposition and entanglement and how they can enhance learning algorithms and data-processing capabilities. The book features a carefully structured progression from foundational concepts and core algorithms to application-driven case studies and emerging directions for future exploration.The book provides a broad and in-depth treatment of topics ranging from quantum data encoding and quantum neural networks to hybrid models and optimization frameworks. Emphasis has also been placed on real-world use cases and the practical tools available for implementation, thereby ensuring that this book serves not only as a reference but also as a springboard for experimentation and innovation. Highlights include the following:Implementing quantum neural networks on near-term quantum hardwareQuantum variational optimization for machine learningQuantum-accelerated neural imputations with large language modelsEmerging trends, addressing hardware limitations, algorithm optimization, and ethical considerationsThis book serves as both a primer and an advanced guide by providing essential knowledge for understanding and implementing quantum-enhanced AI solutions in various professional contexts. It equips readers to become active participants in the quantum revolution transforming machine learning. The book explores quantum computing's transformative impact on artificial intelligence and machine learning. Beyond theoretical knowledge, the book emphasizes practical implementation and offers code samples and real-world case studies. 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.