Quantum Machine Learning: Redefining Computational Boundaries

Machine learning, a subset of AI is moving algorithms in the system which can be learned by data and not programmed explicitly. Various applications of AI across professionals like finance, health-care and automation. With the advancements in Machine Learning, Quantum Machine Learning (QML) or more concretely integrating quantum mechanics into classical machine learning tasks is emerging since QM provides some of the principles to increase efficiency from computational benchmarks. From the most used types of machine learning and algorithms to quantum its usage and applications in Quantum Machine Learning (QML) this paper covers everything. We then articulate some benefits and difficulties of merging quantum computing with machine learning, as well the real-life applications across industry backbones.