Big Data on Machine Learning – A Review

B. K, Dharmarajan K
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Abstract

In rapid development of Big Data technology over the recent years, this paper discussing about the Machine Learning (ML) playing role that is based on methods and algorithms to Big Data Processing and Big Data Analytics. In evolutionary fields and computing fields of developments that both are complementing each other. Big Data: The rapid growth of such data solutions needed to be studied and provided to handle then to gain the knowledge from datasets and extracting values due to the data sets are very high in velocity and variety. The Big data analytics are involving and indicating the appropriate data storage and computational outline that enhanced by using Scalable Machine Learning Algorithms and Big Data Analytics then the analytics to reveal the massive amounts of hidden data’s and secret correlations. This type of 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 big data analytics.
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机器学习中的大数据——综述
在近年来大数据技术飞速发展的背景下,本文探讨了基于机器学习的方法和算法在大数据处理和大数据分析中所发挥的作用。在进化领域和计算领域,两者的发展是相互补充的。大数据:由于数据集的速度和种类非常快,需要研究和提供快速增长的数据解决方案来处理数据集,从数据集中获取知识并提取值。大数据分析涉及并指示适当的数据存储和计算大纲,通过使用可扩展机器学习算法和大数据分析来增强,然后分析揭示大量隐藏数据和秘密关联。这种类型的分析信息有助于组织和公司获得更深入的知识,发展和获得竞争优势。当使用此分析时,我们可以预测数据的准确实现。本文详细回顾了机器学习算法在大数据分析方面的最新发展,概述了机器学习算法的优势和挑战。
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