Quantum Machine Learning: A Survey

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Pramoda Medisetty, Poorna Chand Evuru, Veda Manohara Sunanda Vulavalapudi, Leela Krishna Kumar Pallapothu, Bala Annapurna

Abstract

Quantum Machine Learning (QML) is an emergent discipline that integrates the principles of quantum computing with traditional machine learning techniques, aiming to enhance the capabilities of data analysis and decision-making processes. Leveraging the unique properties, QML promises to revolutionize machine learning by offering superior processing power and computational efficiency. The synergistic approach followed by each Quantum Machine Learning Algorithm allows for the management of large databases and the execution of complex computational tasks more efficiently than classical algorithms. The integration of QML into machine learning workflows can lead to the development of advanced AI systems capable of personalized treatment recommendations, scientific discovery, and data-driven decision-making, thereby transforming the landscape of artificial intelligence and decision-making processes.

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