Log in

Sign up for our weekly newsletter!

When & Where
Mon, April 19, 2021 - 1:00 PM to 4:00 PM
Wed, April 21, 2021 - 1:00 PM to 4:00 PM
Remote (Zoom link sent by email and calendar invite)

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 using the tidymodels framework.

Training Keywords: 
Data Manipulation and Cleaning, Data Science, Data Visualization
Primary Tool: 
Training Learner Level: 
Intermediate to Advanced Competency
Training Host: 
Format Detail: 
Hands-on, Interactive
Participant Technology Requirement: 
Laptop with R installed, internet connection, Zoom account required
Log in to register for this training.