Quantum machine learning is an interdisciplinary research field that investigates the integration of quantum computing principles and devices with machine learning algorithms and techniques. It explores the potential for quantum computers to enhance or enable new approaches to data analysis, pattern recognition, and model training by leveraging quantum phenomena such as superposition, entanglement, and interference. This field aims to develop novel algorithms and hardware architectures that could offer computational advantages, such as speedups or the ability to process quantum data, over classical methods for certain tasks, addressing problems currently intractable for classical machine learning.