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    Quantum Computing Solutions: Solving Real-World Problems Using Quantum Computing and Algorithms

    Posted By: Free butterfly
    Quantum Computing Solutions: Solving Real-World Problems Using Quantum Computing and Algorithms

    Quantum Computing Solutions: Solving Real-World Problems Using Quantum Computing and Algorithms by Bhagvan Kommadi
    English | December 21, 2020 | ISBN: 1484265157 | 320 pages | MOBI | 8.59 Mb

    Know how to use quantum computing solutions involving artificial intelligence (AI) algorithms and applications across different disciplines.

    Quantum solutions involve building quantum algorithms that improve computational tasks within quantum computing, AI, data science, and machine learning. As opposed to quantum computer innovation, quantum solutions offer automation, cost reduction, and other efficiencies to the problems they tackle.

    Starting with the basics, this book covers subsystems and properties as well as the information processing network before covering quantum simulators. Solutions such as the Traveling Salesman Problem, quantum cryptography, scheduling, and cybersecurity are discussed in step-by-step detail.

    The book presents code samples based on real-life problems in a variety of industries, such as risk assessment and fraud detection in banking. In pharma, you will look at drug discovery and protein-folding solutions. Supply chain optimization and purchasing solutions are presented in the manufacturing domain. In the area of utilities, energy distribution and optimization problems and solutions are explained. Advertising scheduling and revenue optimization solutions are included from media and technology verticals.

    What You Will LearnUnderstand the mathematics behind quantum computing
    Know the solution benefits, such as automation, cost reduction, and efficiencies
    Be familiar with the quantum subsystems and properties, including states, protocols, operations, and transformations
    Be aware of the quantum classification algorithms: classifiers, and support and sparse support vector machines
    Use AI algorithms, including probability, walks, search, deep learning, and parallelism

    Who This Book Is For

    Developers in Python and other languages interested in quantum solutions. The secondary audience includes IT professionals and academia in mathematics and physics. A tertiary audience is those in industry verticals such as manufacturing, banking, and pharma.

    Feel Free to contact me for book requests, informations or feedbacks.
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