Date of Publication :25th July 2024

Abstract:With the rapid development of Machine Learning (ML) and Artificial Intelligence (AI) and its diverse use cases, training these models has become very difficult and time-consuming, more so because of the huge amount of data required to increase the model's accuracy. With the recent development in the field of Quantum Computing, the hope is that it will solve ML problems efficiently. This paper gives a brief introduction to quantum computing and one of its use cases – Quantum Machine Learning (QML). It also covers some quantum machine learning algorithms like Quantum Support Vector Machine (QSVM), Quantum k-nearest Neighbour (Q-kNN), Quantum K Means Clustering and Quantum Neural Networks (QNN), which can be used to solve various types of problems more efficiently than classical ML algorithms. Further, it discusses some notable use cases of QML in the field of healthcare like image classification and disease detection. Finally, it talks about the challenges and future scope of QML.

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