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Article Dans Une Revue Mesopotamian Journal of Big Data Année : 2022

An Overview on Deep Leaning Application of Big Data

Résumé

Big data refers to the large volumes of structured and unstructured data that are generated by businesses, organizations, and individuals on a daily basis. Deep learning is a type of machine learning that involves the use of artificial neural networks to learn patterns and relationships in data. In this paper, we discuss the applications of deep learning in the field of big data analysis. We provide an overview of deep learning and big data, and then delve into specific examples of how deep learning has been used in various domains to extract value from big data. These domains include predictive analytics, image and video analysis, natural language processing, and recommendation systems. We also discuss some of the challenges and limitations of using deep learning for big data analysis, as well as future directions for research and development in this field. Overall, deep learning has proven to be a powerful tool for extracting insights from big data, and is likely to play an increasingly important role in the field of data science.

Dates et versions

hal-04123651 , version 1 (09-06-2023)

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Rofia Abada, Abdulhalim Musa Abubakar, Muhammad Tayyab Bilal. An Overview on Deep Leaning Application of Big Data. Mesopotamian Journal of Big Data, 2022, pp.31-35. ⟨10.58496/MJBD/2022/004⟩. ⟨hal-04123651⟩
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