About Quantum Machine Learning: A Review

Abstract

Quantum Machine Learning (QML) is a field which combines the principles from quantum computing with classical machine learning to develop algorithms that can outperform classical approaches. Using quantum computing hardware, re- searchers are exploring how quantum mechanics concepts, like superposition and entanglement, can enhance machine learning techniques. We discuss foundational quantum computing con- cepts, widely used quantum models, and the current challenges in the field. Additionally, we examine potential future directions and the impact of quantum computing on industries such as healthcare, finance, and cryptography. While QML is still in its early stage, research and improvements in quantum hardware may lead to significant breakthroughs in the coming years.