Quantum Computing and Quantum Machine Learning for Engineers and Developers
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Product details:
- Publisher Springer Nature Switzerland
- Date of Publication 2 October 2025
- Number of Volumes 1 pieces, Book
- ISBN 9783031982446
- Binding Hardback
- No. of pages675 pages
- Size 235x155 mm
- Language English
- Illustrations XXXVII, 675 p. 73 illus., 67 illus. in color. Illustrations, black & white 700
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Long description:
This book guides readers from the foundations of quantum mechanics through advanced quantum algorithms (such as Shor’s and Grover’s) and state-of-the-art machine learning methods. By illustrating how these concepts apply to everyday engineering challenges, ranging from complex optimization and cryptography to high-fidelity simulations, the authors equip readers with the tools they need to develop and deploy quantum-based solutions. Incorporating practical case studies, industry-standard platforms, and tested pedagogical approaches, this resource speaks to both academic researchers and industry professionals, enabling them to seamlessly integrate quantum technologies into their projects and workflow
MoreTable of Contents:
Introduction to Quantum Computing.- Fundamentals of Quantum Mechanics.- Quantum Algorithms.- Quantum Computing Hardware.- Introduction to Quantum AI.- Quantum Data Structures and Encoding.- Quantum Neural Networks.- Quantum Optimization Techniques.- Quantum Communication and Cryptography.- Tools and Platforms for Quantum Computing.- Industry Applications of Quantum Computing.- Future Trends in Quantum AI and Engineering.
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