The role of big data in driving advancements in deep learning: Opportunities, challenges, and future directions
1 Research and Data Department, Veriv Africa Limited, Abuja, Nigeria.
2 Mechanical Engineering, University of Florida, Gainesville, FL, USA.
3 Mathematics, The University of Alabama at Birmingham, Alabama, USA.
4 Computer Science, Maharishi International University (MIU), Fairfield, IA, USA.
5 Marketing Department, Tower Base Technologies, Ile-Ife, Osun State. Nigeria.
6 Information Technology Department, Avosoft UK, Crewe, England, UK.
Review Article
World Journal of Advanced Research and Reviews, 2024, 24(02), 690–696
Publication history:
Received on 27 August 2024; revised on 15 October 2024; accepted on 17 October 2024
Abstract:
The advent of big data has significantly shaped the trajectory of machine learning, particularly in the field of deep learning. The vast amounts of data generated every day across various sectors—from healthcare to finance—have provided unprecedented opportunities for training more powerful and accurate deep learning models. This review paper explores the critical role big data plays in driving advances in deep learning, analyzing how these two fields intersect and fuel each other. The paper also examines the challenges associated with leveraging big data in deep learning, including data quality, scalability, and computational constraints. Finally, the paper discusses future directions in the convergence of big data and deep learning, emphasizing emerging trends and the potential of this intersection to revolutionize industries.
Keywords:
Big Data; Machine Learning; Artificial Intelligence; Convolutional Neural Networks (CNNs); Real-Time Learning; Electronic-Health Records
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Copyright information:
Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0