Efficient Deep Learning for Big Data: A Review - Leelavathi, MV; Sahana Devi, KJ (International Journal of Computer Sciences and Engineering, 2025)
The data science is composed of Big Data Analytics (BDA) and Deep Learning (DL). Apart from this Big Data (BD) has got popularity due to its importance in the present genre for both the public and private organizations, as this applies to collection of huge data. Basically, the BD is composed of many national intelligence applications, medical technology, cyber security data, etc. Many of the companies are analyzing the BD for its business purpose. The DL is the sequential or active learning process which collects the complex data and high-level data. This DL has its own beneficial key functions like learning and analysis of the enormous volume of unsupervised data (UD). This performs as the most valuable data analytics tool for BDA. In this paper, a brief overview of Deep learning in Big Data Analytics is presented with the challenges of DL in BD. The statistical survey is formulated by using IEEExplore. Finally, the paper future study requirements in Deep learning are discussed.