Explore the Quantum machine algorithms in deep and explore the hybrid systems where quantum computing meets artificial intelligence.
Quantum Computing Algorithms for Artificial Intelligence by Dr. Sri Amit Ray is a guide to the algorithms, learning models, and hybrid systems at the intersection of quantum computing and AI. It builds from quantum foundations to current research, with a practical focus on data access, classical baselines, resource costs, sampling, compilation, and noise.
Inside the book:
Who this book is for:
Learn through worked examples. Numerical results, from Grover search and QAOA to molecular energies, barren-plateau analysis, and reservoir computing, are accompanied by code in Appendix C so you can reproduce and adapt the book's figures and examples. The book also includes exercises with selected answers, a mathematical workshop, an algorithm selection guide, a glossary, and references.
Written for graduate students, researchers, engineers, and technically minded practitioners with a background in linear algebra, probability, and basic machine learning. No prior quantum mechanics is assumed.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
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