Introduction to quantum machine learning, its applications and advantages

In this article, we delve into the emerging field of quantum machine learning (QML) and its innovative applications. We provide an overview of the fundamentals of quantum mechanics relevant to machine learning, highlighting how quantum principles can be harnessed to process information more efficiently than classical approaches. We discuss the step-by-step process of a quantum algorithm example using Qiskit, comparing it with its classical counterpart. We address the advantages of QML, including the potential for acceleration in large-scale problems and the ability to handle highly dimensional data. Finally, current challenges and future prospects of the field are discussed, emphasizing its role in transforming various technological sectors. This article serves as a comprehensive introduction for those interested in exploring the intersection of machine learning and quantum mechanics, highlighting the promising opportunities that this combination offers.

Keywords:
Machine Learning; Quantum Computing; Algorithms