This thesis is mainly focused on the study of Quantum Support Vector Machine
(QSVM), a very important member of the recent and innovative Quantum Machine Learning
field, and its comparison with conventional Support Vector Machine (SVM).
In this paper, I have worked on the application of Quantum Support Vector Machine
algorithm, that runs on near term quantum processors from I.B.M., through IBM Quantum
Experience cloud service, to a set of supervised machine learning case studies and
I compared its performance with classical Support Vector Machine algorithm; net of the
enormous hype surrounding the proliferation of quantum technologies in recent years, are
we beginning to glimpse an application of real interest in which quantum systems, albeit
with limitations, offer concrete improvements already now?