Dartmouth College researchers have published a free Python software package called HyperTools that allows users to turn complex data into 3D shapes or animations. The tool allows users to visualize patterns in their data and compare the characteristics of different datasets, which in turn could inform researchers on how to train their machine learning algorithms by illuminating differences between groups of data. Additionally, the Dartmouth researchers have published tutorials for HyperTools and a gallery of examples, such as how to plot the text of State of the Union addresses, to help users create visualizations.
Visualizing Patterns in Complex Data
Michael McLaughlin is a research assistant at the Center for Data Innovation. He previously worked at Oracle and held internships at USA TODAY and in local government. Prior to joining the Center for Data Innovation, Michael graduated from Wake Forest University, where he majored in Communication with Minors in Politics and International Affairs and Journalism. He is currently pursuing his Master’s in Communication at Stanford University, specializing in Data Journalism.
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