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<p>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. &#xa0;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</p>

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Quantum Computing and Quantum Machine Learning for Engineers and Developers

  • 教材

  • 发表日期：

    2025年

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  • Jesse Van Griensven Thé,
  • Roydon Andrew Fraser,
  • Jose Rosas-Bustos

摘要

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