Quantum Machine Learning : Concepts, Algorithms, and Applications (Paperback)

1. Introduction to Quantum Computing 2. Principles, Algorithms, and Technologies behind Quantum Computing 3. An Overview of Machine Learning: Concepts, Algorithms, and Practices 4. Quantum Information Theory 5. Quantum Machine Learning from Theory to Data-Driven Implementations 6. A Mathematical Perspective on Quantum Information Theory 7. Quantum Neural Networks 8. Implementing Quantum Neural Networks on Near-Term Quantum Hardware 9. A Comparative Analysis of Classical and Quantum Approaches for Heart Attack Prediction 10. Quantum Optimization for Machine Learning 11. Quantum Variational Optimization for Machine Learning 12. Latest Developments in Quantum Optimization for Machine Learning 13. Quantum Generative Adversarial Networks 14. Heart Disease Prediction Analysis using Quantum-Enhanced Features with Classical and Quantum Machine Learning Models 15. Quantum-Accelerated Neural Imputation with Large Language Models (LLMs) 16. Quantum Key Distribution Beyond 5G and 6G: Hybrid Integrations, Testbeds, and Future Directions ?