A Quick Introduction to Quantum Machine Learning for Non-Practitioners

Understand

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 basic quantum mechanics principles, including superposition, phase space, and entanglement, and introduces the concept of quantum gates that exploit these properties.