An Introduction To Quantum Machine Learning Techniques
Subodh Nath Pushpak, Sarika Jain
Abstract
This paper presents an overview of quantum machine learning (QML) techniques, their approach, and their landscape. QML is a rapidly evolving field of study which has recently generated lots of interest due to improvements it promises over the classical machine learning approaches. This paper presents an overview of the application of quantum information theory on machine learning algorithms. It also discusses various designs, techniques, and algorithms of classical machine learning and quantum information theory and how they can be fused with each other. The goal of this paper is to analyze algorithms and techniques used in QML. The paper also presents some of the promising algorithms used in QML, which can be executed on a real quantum computer over cloud computing platforms with the aim to evaluate its performance based on given parameters.