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Fall 2016
Dec 15, 2019
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CSCI 2951V - Systems for Interactive Data Exploration
Enabling visual data exploration at ``human speed'' is key to democratizing data science and maximizing human productivity. Unfortunately, traditional data management systems or more recent analytical frameworks, like Hadoop and Spark, are ill-suited for that purpose. Similar current machine learning algorithms and other analytical techniques are not designed for returning fast progressive answer. The goal of this research seminar is to study recently proposed techniques to make data exploration over large data sets more interactive, participate in the development of the next generation of interactive data exploration systems and through it make a active research contribution.
1.000 Credit hours
1.000 Lecture hours

Levels: Graduate, Undergraduate
Schedule Types: Primary Meeting

Computer Science Department

Restrictions:
Must be enrolled in one of the following Levels:     
      Graduate

Prerequisites:
(Graduate level CSCI 0320 Minimum Grade of S or Graduate level CSCI 0330 Minimum Grade of S) and (Graduate level CSCI 1270 Minimum Grade of S or Graduate level CSCI 1951A Minimum Grade of S or Graduate level CSCI 1670 Minimum Grade of S)

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