Quantum Machine Learning

Revolutionizing Data Analysis and Optimization
1. Auflage 2026
ISBN: 978-1-041-08375-7
Verlag: Taylor & Francis Ltd

Buch, Englisch, 380 Seiten, Format (B × H): 156 mm x 234 mm

This work offers a structured and in-depth exploration of Quantum Machine Learning (QML), beginning with foundational quantum principles and progressing to advanced QML algorithms such as Quantum SVMs, quantum kernels, and quantum neural networks. It bridges theory with real-world implementation through domain-focused chapters covering finance, healthcare, taxation systems, mobile networks, supply chains, cybersecurity, augmented reality dashboards, and e-commerce. By integrating conceptual clarity with applied frameworks, the book presents practical pathways for leveraging quantum-enhanced intelligence across industries.

The book is intended for researchers, academicians, postgraduate students, industry professionals, data scientists, technology strategists, and policymakers seeking to understand and apply Quantum Machine Learning in advanced research, enterprise systems, and next-generation digital infrastructures.

Key Features:

- Comprises Comprehensive Coverage: Balances foundational theory with practical applications.

- Comprises Cutting-Edge Content: Features the latest research and emerging trends in QML.

- Provides Practical Insights: Includes real-world case studies and examples for applying QML techniques.

- Comprises Expert Authorship: Written by a leading expert with strong academic and industry experience.

Zielgruppe

Postgraduate, Professional Practice & Development, Undergraduate Advanced, and Undergraduate Core

Autoren/Hrsg.

Dwivedi, Jaiprakash Narain

Shukla, Parag

Joshi, Herat

Tripathi, Pankaj

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsarchitektur
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Mustererkennung, Biometrik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Datenbankdesign & Datenbanktheorie

Inhaltsverzeichnis

Preface. 1. Quantum Roots of Modern Computing. 2. Intersection of Quantum Computing and Machine Learning. 3. Harnessing Quantum Kernels for Supervised Learning: A Deep Dive into Quantum SVMs. 4. Quantum Support Vector Machines (QSVMs) and Their Applications. 5. Quantum Neural Networks and Deep Learning in the Era of Quantum-Enhanced Artificial Intelligence. 6. Quantum Leaps in Finance: Integrating Quantum Computing and Machine Learning. 7. Financial Modeling and Quantum Computing Economics. 8. Quantum Machine Learning Applications in Healthcare. 9. AI-Enabled Standalone Device for Early Breast Cancer Detection: Advancing Diagnosis and Healthcare. 10. Harnessing Quantum Computing for Supply Chain Transformation: The PRABAX Framework. 11. Quantum Algorithmic Threats and Countermeasures in Cloud and IoT Security. 12. Application of Quantum Machine Learning in Goods and Services Tax: Toward Better Compliance and Fraud Detection. 13. A Quantum-Enabled Framework for Enhancing Service Quality in India’s Mobile Networks. 14. Augmented-Reality-Driven IT Operations Dashboards Powered by Quantum Machine Learning. 15. Next-Generation Product Categorization in E-commerce using Quantum Machine Learning Approach over Virtualized Data Environment.

Über Autor(innen)

Jaiprakash Narain Dwivedi, Ph.D., is currently working as an Associate professor, IT Department, Parul Institute of Engineering and Technology, Faculty of Engineering and Technology, Parul University, Vadodara, Gujarat, India. He possesses B.E. (Electronics and Communication Engineering), M. Tech. (Signal Processing), and Ph. D. (Machine Learning from Kyushu Institute of Technology Japan). He has more than 15 years of experience (including academia, industry and research) and his professional activities include roles as associate editor, editorial board member and reviewer of various International Journals. His research publication includes patents, books, book chapters, journals and conference proceedings. He has received, young scientist award and Lifetime achievement awards and his interest in research includes Machine Learning, Artificial Neural Network, Pattern Recognition, Classification, CNN, DNN, Deep Learning and Signal Processing.

Dr. Parag Shukla is an Assistant Professor in Commerce at Maharaja Sayajirao University of Baroda, India, specializing in Marketing Management. He earned his bachelor's and master's degrees from the same university, focusing on Marketing Management. Dr. Shukla's research centers on Retailing, and he has a background in content analysis within the television and media research industry. He teaches management courses at various levels and has published extensively in national and international journals and conferences. His current research project titled "An Empirical Investigation of Experiential Value vis-a-vis Usage Attitude of Selected Mobile Shoppers in Gujarat.” Dr. Shukla is notable for receiving the Silver Medal at the 68th International All India Commerce Conference for his research, earning the Best Business Academic of the Year Award, a significant recognition in Indian Education and Retail Industry.

Herat Joshi is a distinguished expert in healthcare technology and informatics with more than 14 years of professional experience, currently serving at the Analytics & Decision Support at Great River Health Systems in Burlington, IA, USA. Apart from that he is member of following, FACHDM - Fellow American College of Health Data Management, Sr. Member of IEEE, Member AHIMA - American Health Information Management Association, Member of AMIA - American Medical Informatics Association,) He is also serving as Vice Chair IEEE IA-IL Section, Chair at two workgroups in AMIA. Herat has led numerous AI-driven projects, significantly enhancing healthcare delivery and operational efficiency. He has been recognized with multiple awards for his contributions to healthcare informatics, including the Outstanding Leadership Award at the Health 2.0 Conference. He is dedicated to advancing the field of healthcare AI and mentoring the next generation of professionals. His work has been well-received by the healthcare industry and research community.

Pankaj Tripathi is working as an Assistant Professor in the Department of Accounting and Financial Management, Faculty of Commerce, The Maharaja Sayajirao University of Baroda, Vadodara. He has vast experience in academics, worked in different states of India adding varied multicultural experience to his career. He holds PhD in Finance and Accounting. He is recognized PhD guide and 3 scholars are pursuing PhD under his supervision. His areas of expertise include financial accounting, financial economics, business economics and business administration. He has various papers in National and international journals. He is a life member of the Indian Commerce Association and Indian Accounting Association.