Abstract

Quantum Machine Learning is a subfield of quantum computing that focuses on applying machine learning techniques to quantum algorithms and quantum systems. Quantum machine learning is an active area of research, with many scientists and engineers exploring its potential for solving complex problems. The goal of quantum machine learning is to explore the unique features of quantum systems that can be used to solve problems that are intractable for classical machine learning algorithms. Quantum algorithms can offer significant speedups over classical algorithms in certain cases, and this property can be leveraged in machine learning algorithms to achieve faster training and improved accuracy. In this research paper, a brief review of the recent techniques and algorithms of quantum machine learning and its scope in solving real world problem are analysed.