Research Oriented Reviewing of Quantum Machine Learning

Abstract

Quantum machine learning is an interdisciplinary research domain that seeks to merge the concepts of quantum computing and machine learning. Owing to the computational complexity and time constraints of certain scientific challenges, classical computation is often inadequate, and quantum computation offers a promising alternative. Notable algorithms in quantum machine learning include quantum versions of classical machine learning algorithms, such as support vector machines, and classical deep learning techniques, such as quantum neural networks. The primary aim of quantum machine learning is to improve the performance of machine learning by leveraging quantum computing. While there have been promising advances, quantum machine learning still requires significant advancements in quantum hardware to fully realize its potential.