BigData on Machine Learning – A Review

K. Balasree, Dr. K. Dharmarajan
Big Data; Analytics; Machine Learning; SVM; Decision Tree; Naïve Baye’s; Random Forest.
In rapid development of Big Data technology over the recentyears, this paper discussing about the Machine Learning (ML) playing role that is based on methods and algorithms to Big Data Processing and BigData Analytics. In evolutionary fields and computing fields of developments that both are complementing each other. Big Data: Therapid growth of such data solutions needed to be studied and providedtohandlethentogainthe knowledge fromdatasetsand extractingvaluesdue to the data sets are very high in velocity and variety. The Big dataanalytics are involving and indicating the appropriate data storage and computational outline that enhanced by using Scalable Machine Learning Algorithms and BigData Analytics then the analytics to reveal the massive amounts of hidden data’s and secret correlations. This typeof Analytic information useful for organizations and companies to gain deeper knowledge, development and getting advantages over the competition. When using this Analytics we can predict the accurate implementation over the data. This paper presented about the detailed review of state-of-the-art developments and overview of advantages and challenges in Machine Learning Algorithms over bigdata analytics.
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Received :21 May 2021
Accepted :14 September 2021
Published :26 September 2021
DOI: 10.30726/esij/v8.i3.2021.83018