Quantum Machine Learning: A review of Emerging Concepts
Keywords:
Quantum Machine learning, Artificial intelligence, Noisy Intermediate-Scale Quantum (NISQ), Support Vector Machine, Quanvolutional Neural NetworksAbstract
Machine learning is widely used in many scientific and technological fields as a component of artificial intelligence, such as "computer vision, natural language processing, data mining, biological analysis, and so on". One of the human race's most promising technologies for the near future is the quantum computer. Researchers are contemplating fusing machine learning with quantum computing to optimize the potential advantages of the former. This has led to the creation of a brand-new, interdisciplinary area called quantum machine learning. The current state of the field in “quantum machine learning techniques” is analyzed from a computer science viewpoint, and a research pathway from fundamental quantum data to these techniques is shown. It's possible to argue that QML will soon reach its full potential in resolving practical issues. It increases machine learning's capacity to handle, analyse, and mine massive amounts of data by using the high parallelism of quantum computing.
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