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A Survey of Machine Learning for Big Data Processing

Reem Almutiri*, Sarah Alhabeeb, Sarah Alhumud, Rehan Ullah Khan

Department of Information Technology, College of Computer, Qassim University, Buraydah, Saudi Arabia

* Corresponding Author: Reem Almutiri. Email: email

Journal on Big Data 2022, 4(2), 97-111. https://doi.org/10.32604/jbd.2022.028363

Abstract

Today’s world is a data-driven one, with data being produced in vast amounts as a result of the rapid growth of technology that permeates every aspect of our lives. New data processing techniques must be developed and refined over time to gain meaningful insights from this vast continuous volume of produced data in various forms. Machine learning technologies provide promising solutions and potential methods for processing large quantities of data and gaining value from it. This study conducts a literature review on the application of machine learning techniques in big data processing. It provides a general overview of machine learning algorithms and techniques, a brief introduction to big data, and a discussion of related works that have used machine learning techniques in a variety of sectors to process big amounts of data. The study also discusses the challenges and issues associated with the usage of machine learning for big data.

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Cite This Article

R. Almutiri, S. Alhabeeb, S. Alhumud and R. U. Khan, "A survey of machine learning for big data processing," Journal on Big Data, vol. 4, no.2, pp. 97–111, 2022.



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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