Understanding Complexity by Clustering Data with Machine Learning and R
Thursday, August 28, 2014
Presented by: Brett Lantz
Duration: Approximately 60 minutes.
Although machine learning is most commonly used for prediction, it can also help make sense of the complexity in the world around us. In this webcast, we'll explore how R's open-source clustering packages can discover patterns in large data and inform our understanding of complex sociological phenomena such as teenage identities.
About Brett Lantz
Brett Lantz has spent the past 10 years using innovative data methods to understand human behavior. A sociologist by training, he was first enchanted by machine learning while studying a large database of teenagers' social networking website profiles. Since then, he has worked on interdisciplinary studies of cellular telephone calls, medical billing data, and philanthropic activity, among others.
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