A Brief Review of Big Data Analytics Based on Machine Learning

Ahmed Hussein Ali; Mahmood Zaki Abdullah; Shams N. Abdul-wahab; Mohammad Alsajri

doi:10.52866/ijcsm.2020.01.01.002

A Brief Review of Big Data Analytics Based on Machine Learning

Authors

Ahmed Hussein Ali Department of computer, College of Education, AlIraqia University, Baghdad, Iraq https://orcid.org/0000-0002-9968-3125
Mahmood Zaki Abdullah Department of computer engineering, Baghdad, Iraq
Shams N. Abdul-wahab Department of Computer Technical Engineering, Alsalam University College, Baghdad, Iraq
Mohammad Alsajri Faculty of Computing, College of Computing and Applied Sciences, Universiti Malaysia Pahang, Malaysia https://orcid.org/0000-0002-5790-6669

DOI:

https://doi.org/10.52866/ijcsm.2020.01.01.002

Keywords:

Machine Learning; Bigdata; Classification.

Abstract

Owing to the exponential expansion in the data size, fast and efficient systems of analysis are
extremely needed. The traditional algorithms of machine learning face the challenge of learning bottlenecks such
as; human participation, time, and the accuracy of prediction. But, the efficient and fast methods of dynamic
learning offer considerable advantages like lower human participation, rapid algorithms of learning, and easiness
implementation. This review paper presents the researches with a brief display for recently existing works in big data
analytics and the effective algorithms of machine learning, furthermore, the issues of resources allocation in big data

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Published

2020-07-30

How to Cite

[1]

Ahmed Hussein Ali, Mahmood Zaki Abdullah, Shams N. Abdul-wahab, and Mohammad Alsajri, “A Brief Review of Big Data Analytics Based on Machine Learning”, Iraqi Journal For Computer Science and Mathematics, vol. 1, no. 2, pp. 13–15, Jul. 2020.