Understanding Dimensionality Reduction in Quantum Machine Learning

This chapter explores dimensionality reduction techniques in quantum machine learning, highlighting their ability to enhance pattern recognition in high-dimensional data. The discussion includes practical applications using the ARIS dataset and addresses the challenges of model training with excessive dimensions.