Quantum Machine Learning (QML) refers to the field that explores the intersection of quantum computing and machine learning. It involves applying principles and techniques from quantum mechanics to enhance and develop machine learning algorithms.
QML aims to leverage the unique properties of quantum systems, such as superposition and entanglement, to improve the performance and efficiency of machine learning tasks. By harnessing quantum algorithms and quantum data representation, QML seeks to overcome limitations encountered in classical machine-learning approaches.