A Quick Introduction to Quantum Machine Learning for Non-Practitioners

arXiv:2402.14694v1 Announce Type: cross
Abstract: This paper provides an introduction to quantum machine learning, exploring the potential benefits of using quantum computing principles and algorithms that may improve upon classical machine learning approaches. Quantum computing utilizes particles governed by quantum mechanics for computational purposes, leveraging properties like superposition and entanglement for information representation and manipulation. Quantum machine learning applies these principles to enhance classical machine learning models, potentially reducing network size and training time on quantum hardware. The paper covers …

abstract algorithms arxiv benefits computational computing cs.et cs.lg entanglement introduction machine machine learning paper quant-ph quantum quantum computing quantum mechanics superposition type