1. Machine learning algorithms to solve problems of heterogenous big data
Authors : Madhavi Tota
Pages : 96-101
DOI : http://dx.doi.org/10.21172/1.132.18
Keywords : Big Data Machine Learning Unsupervised learning SVM MapReduce Abstract :Abstract: With the revolution in Big Data it transforms the data by enabling optimization, enhancing insight quality and improving decision making. The extraction of this heterogonous data from such massive data through data analytics; machine learning is at its important because of its ability to learn from data with different learning algorithms and provide data driven insights, decisions, and predictions. In this research we discuss different challenges, the cause effects according to Big Data or different dimensions of data. Now a days Health Care is important issue and need improvement in health science. There are multiple processes going on within health sector. As vast amount of healthcare data is increasing every day, it is believed that extracting knowledge by data analysis process is essential. A education system generates massive knowledge by means of the services provided. This result in a researchers to put forward solutions for big data usage, depending on learning analytics techniques as well as the big data techniques relating to the educational field. This paper summarizes the role of big data analysis and prediction in healthcare, educational system provides a perspective on the domain, identifies research gaps and opportunities, and few machine learning techniques.
Citing this Journal Article :Madhavi Tota, "Machine learning algorithms to solve problems of heterogenous big data", Volume 13 Issue 2 - April 2019, 96-101
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