DEEP LEARNING AND DATA MINING INTEGRATION FOR LARGE-SCALE CLOUD ANALYTICS

Abstract

This research examines the potential of deep learning and data mining to enhance datadriven insights in large-scale cloud analytics. The proposed approach integrates deep learning and data mining to analyse diverse and extensive datasets. The cloud's real-time big data processing and storage capabilities are facilitated by its scalable architecture and computing capacity. In addition to enhancing predictive accuracy and decision-making, its integration resolves data complexity, high dimensionality, and rapid data production. The significance of this hybrid framework in contemporary cloud-based analytics systems for fraud detection, intelligent forecasting, and recommendation systems is underscored in the paper.