How quantum computing can accelerate machine learning models for massive datasets.
Introduction The rapid growth of data in the digital age has pushed traditional computing to its limits, particularly in the realm of machine learning (ML) where massive datasets are common. Quantum computing, an emerging paradigm leveraging the principles of quantum mechanics, offers the potential to revolutionize ML by accelerating computations that are infeasible for classical computers. This chapter explores how quantum computing can enhance the training, optimization, and deployment of ML models for massive datasets, focusing on its unique capabilities, current advancements, and future implications. The Challenge of Massive Datasets in Machine Learning Machine learning models, especially deep learning architectures, thrive on large datasets to achieve high accuracy and generalization. However, processing massive datasets—often containing billions of data points across high-dimensional spaces—presents significant computational challenges: Computational Bottlenecks : Traini...