Quantum Machine Learning and Recent Advancements
This paper introduces quantum computing over classical computation, followed by the recent tools and techniques developed in the area, and looks at multiple QML models like quantum kernel, quantum support vector machine (QSVM), etc.
Abstract
Quantum Computing is a fastly growing area with many applications, including quantum machine learning (QML). Due to the rapid increase of computational power, machine learning models based on artificial neural networks (ANN) have become highly effective. Even though classical machine learning models have been performing well, quantum computing with machine learning enhances the performance in multiple ways. This paper studies different aspects of quantum machine learning. It introduces quantum computing over classical computation, followed by the recent tools and techniques developed in the area. We look at multiple QML models like quantum kernel, quantum support vector machine (QSVM), etc. Finally, we present the literature survey to encourage researchers and academicians.