Quantum Machine Learning (QML): Platform, Tools and Applications
Language: English
Published by Elsevier Science & Technology, Academic Press Feb 2026, 2026
- Hardcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Condition: New
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Add to basketItem description from seller
Neuware - Quantum Machine Learning (QML): Platform, Tools and Applications, Volume 140 in the Advances in Computers series, explores the intersection of quantum computing and artificial intelligence, highlighting advances that promise to revolutionize computational science. The book introduces foundational concepts in quantum computing and circuits, building toward the practical implementation of quantum machine learning (QML) algorithms. Chapters address challenges such as the gradient vanishing problem in variational quantum circuits and explore powerful optimization methods enabled by quantum mechanics. The volume also covers advanced applications, including quantum approaches to smart grid management, quantum Monte Carlo simulations, and predictive modeling in numerical solvers using quantum neural networks.Real-world relevance is underscored through discussions of transformative quantum algorithms and their potential to reshape machine learning, enabling unprecedented performance in data analysis, optimization, and beyond.…
Seller Inventory # 9780443223822
- Title
- Quantum Machine Learning (QML): Platform, Tools and Applications
- Author
- Shiho Kim
- Publisher
- Elsevier Science & Technology, Academic Press Feb 2026
- Publication year
- 2026
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 0443223823
- ISBN 13
- 9780443223822
- Item weight
- 450 grams
- Dimensions
- 228x152x34 mm
Quantum Machine Learning (QML): Platform, Tools and Applications, Volume 140 in the Advances in Computers series, explores the intersection of quantum computing and artificial intelligence, highlighting advances that promise to revolutionize computational science. The book introduces foundational concepts in quantum computing and circuits, building toward the practical implementation of quantum machine learning (QML) algorithms. Chapters address challenges such as the gradient vanishing problem in variational quantum circuits and explore powerful optimization methods enabled by quantum mechanics. The volume also covers advanced applications, including quantum approaches to smart grid management, quantum Monte Carlo simulations, and predictive modeling in numerical solvers using quantum neural networks.
Real-world relevance is underscored through discussions of transformative quantum algorithms and their potential to reshape machine learning, enabling unprecedented performance in data analysis, optimization, and beyond.
- Contains novel subject matter that is relevant to computer science
- Includes the expertise of contributing authors
- Presents an easy to comprehend writing style
"Synopsis" may belong to another edition of this title.
About the Author
Ganesh Chandra Deka is currently Deputy Director (Training) at Directorate General of Training, Ministry of Skill Development and Entrepreneurship, Government of India, New Delhi-110001, India. His research interests include e-Governance, Big Data Analytics, NoSQL Databases and Vocational Education and Training.
He has 2 books on Cloud Computing published by LAP Lambert, Germany. He is the Co-author for 4 text books on Fundamentals of Computer Science (3 books published by Moni Manik Prakashan, Guwahati, Assam, India and 1 IGI Global, USA). As of now he has edited 14 books (6 IGI Global, USA, 5 CRC Press, USA, 2 Elsevier & 1 Springer) on Big data, NoSQL and Cloud Computing and authored 10 Book Chapters.
He has published around 47 research papers in various IEEE conferences. He has organized 08 IEEE International Conferences as Technical Chair in India. He is the Member of the editorial board and reviewer for various Journals and International conferences. Member of IEEE, the Institution of Electronics and Telecommunication Engineers, India and Associate Member, the Institution of Engineers, India
"About the title" may belong to another edition of this title.
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