Leveraging Quantum Computing for Supervised Classification

Enhancing quantum computing for supervised machine learning is an innovative application in the field of smart computing. With recent advancements in quantum computing, and it is rising to coalesce with Artificial Intelligence, quantum computers can revolutionize the way to address previously untenable problems. As quantum computers can succeed in producing various intuitive patterns that are strenuous for a classical system to implement, it is reasonable to presume that these quantum machines can outperform a classical computer in various tasks. They can excel at solving problems which involve data crunching with a huge amount of inputs such as machine learning tasks, complex optimization problems, communication system analysis, etc. which require complex parallel computations for an efficient result. This paper attempts to analyze one such aspect of machine learning known as supervised classification with the help of a real Quantum hardware.