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This two-part workshop provides an introduction to machine learning algorithms using the tidymodels package. It covers what machine learning is, which problems it is most and least equipped to address, and explores the tidymodels framework to fit supervised machine learning models in R.

Addressing machine learning problems requires a deep conceptual understanding of the material. While the workshop will cover coding in R, it will also dedicate a significant portion of the time to motivating machine learning techniques.

By the end of the workshop, learners should feel prepared to explore machine learning approaches for their own data problems. This workshop does not cover unsupervised machine learning techniques.

Prerequisites: Familiarity with R programming and data wrangling is assumed. If you are not familiar with the materials in Data Wrangling and Manipulation in R, we recommend attending that workshop first. In addition, this workshop focuses on how to implement machine-learning approaches. Learners will likely benefit from previous exposure to statistics.

Date & Time

February 27, 2024
10:00am - 12:00pm


Online via Zoom





Event Category

Event Categories:
Professional Development Events