DC Field | Value | Language |
---|---|---|
dc.contributor.author | Sadaria, Priti | - |
dc.contributor.author | Dr. Achyut C., Patel | - |
dc.date.accessioned | 2024-11-21T06:38:10Z | - |
dc.date.available | 2024-11-21T06:38:10Z | - |
dc.date.issued | 2020 | - |
dc.identifier.issn | 1548-7741 | - |
dc.identifier.uri | http://10.9.150.37:8080/dspace//handle/atmiyauni/1839 | - |
dc.description.abstract | Now a day no field remains untouched with Information Technology. Health care industries are using Information Technology for different aspects. Mining of valuable information by analyzing this quickly rising data for building a useful model which can be relevant in real life is really a difficult task. Knowledge discovery and decision making from such huge data is a novel trend that is Big Data Computing. Machine learning techniques can be used to make predictive analytics. Cloud computing provides computing services over the internet which includes servers, storage, databases, software and analytics for big data processing. Extracting useful information from this massive amount of data is highly difficult, expensive, and time consuming and therefore the problem can be solved by processing huge amount of data by applying machine learning techniques on Hadoop platform in Cloud environment. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Journal of Information and Computational Science | en_US |
dc.relation.ispartofseries | 10;11 | - |
dc.subject | Hadoop | en_US |
dc.subject | MapReduce | en_US |
dc.subject | Machine Learning | en_US |
dc.subject | Big Data | en_US |
dc.subject | Cloud | en_US |
dc.title | Hadoop MapReduce with Machine Learning Techniques for Big Data Computing On Cloud Environment | en_US |
dc.type | Article | en_US |
Appears in Collections: | 01. Journal Articles |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Hadoop MapReduce with Machine Learning Techniques for Big Data Computing On Cloud Environment.pdf | 315.98 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.