Titlebook: Quantum Machine Learning: An Applied Approach; The Theory and Appli Santanu Ganguly Book 2021 Santanu Ganguly 2021 Quantum Mechanics.machin

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Neural Networks,Chapter . looked at machine learning (ML), which emerged as a subfield of research in artificial intelligence. Deep learning (DL) is a subset of ML. It attempts to solve specific problems in areas of artificial intelligence, such as reasoning, planning, and knowledge representation.

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QML Algorithms II,Quantum machine learning provides unprecedented scope in computing the techniques done in classical machine learning on a quantum computer. The entanglement and superposition of the basic qubit states promise to provide an edge over the performance and scope of classical machine learning.

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QML: Way Forward,Quantum machine learning (QML) is a cross-disciplinary subject made up of two of the most exciting research areas: quantum computing and classical machine learning.

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Machine Learning, ., ., and .. There are several others, including ., ., and .. Deep learning (DL) is a special subset that includes these various types of ML. It extends them to solve other problems in artificial intelligence, such as reasoning, planning, and knowledge representation.

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QML Algorithms I,n certain areas. Applications can benefit from quantum computing. You just need to find the right device. When developing an application, it is important to know which device serves the purpose best for the solution of a specific problem and which algorithms are best supported on the same platform.