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Evan earned his PhD in Biological Anthropology from Southern Illinois University Carbondale where he focused on spatial patterns of skeletal and dental variation in two large necropoles of Iron Age Central Italy (1st millennium BCE).
Machine learning often evokes images of Skynet, self-driving cars, and computerized homes. However, these ideas are less science fiction as they are tangible phenomena that are predicated on description, classification, prediction, and pattern recognition in data. To social scientists, such methods might be critical for investigating evolutionary relationships, global health patterns, voter turnout in local elections, or individual psychological diagnoses.
We will discuss basic features of supervised machine learning algorithms including k-nearest neighbor, linear regression, decision tree, random forest, boosting, and ensembling.
Prior knowledge requirements: R FUN!damentals: Parts 1 through 4 or previous intermediate working knowledge of R.
