Predikt : a simpler machine learning experience

dc.contributor.advisorAziz, Adnanen
dc.contributor.committeeMemberKrasner, Herben
dc.creatorPrakash, Piyushen
dc.date.accessioned2015-11-09T16:45:56Zen
dc.date.available2015-11-09T16:45:56Zen
dc.date.issued2015-05en
dc.date.submittedMay 2015en
dc.date.updated2015-11-09T16:45:56Zen
dc.descriptiontexten
dc.description.abstractWith the exponential growth in volume of data being generated by the businesses today, the need for automated systems to facilitate decision making is growing. In many cases, the volume of data has reached the scale where it is not humanly possible to analyze the relevant data using traditional processes, which are dependent on manual intervention, to reach a good decision. The increase in diversity of data sources (internal, external, social, sensors, etc) has added significantly to the challenge of decision making. Predikt presents a simplified approach for the automation of decision making in organizations using Data Mining and Machine Learning techniques with minimal human intervention. Human Intervention, when required, will typically be to accept, reject or override a decision already made by the machine. Predikt front-end as well as back-end is able to adapt to end users unique requirements. Predikt is able to render User Interface dynamically based on User Inputs, while backend is able to do intelligent data processing such as binning (for numeric columns) and multiple model evaluation.en
dc.description.departmentElectrical and Computer Engineeringen
dc.format.mimetypeapplication/pdfen
dc.identifierdoi:10.15781/T2XG9Pen
dc.identifier.urihttp://hdl.handle.net/2152/32310en
dc.language.isoenen
dc.subjectMachine learningen
dc.subjectPredictive analyticsen
dc.titlePredikt : a simpler machine learning experienceen
dc.typeThesisen
thesis.degree.departmentElectrical and Computer Engineeringen
thesis.degree.disciplineElectrical and Computer Engineeringen
thesis.degree.grantorThe University of Texas at Austinen
thesis.degree.levelMastersen
thesis.degree.nameMaster of Science in Engineeringen

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