Machine Learning with R: Random Forest Classification Approach

The Random Forest is a powerful algorithm used for classification in the industry. The classification algorithm consists of many decision trees to get more accurate predictions. This workshop will go over the theoretical part of Random Forest, then provide attendees with hands-on training on conducting Random Forest classification, training the data, testing accuracy, and working with tuning parameters. 

A beginner-level understanding of R-programming, introductory statistical knowledge, and familiarity with decision trees are required for this workshop. 

*Presented by Shaila Jamal (DASH Support Assistant). This virtual workshop will be recorded and shared on the Sherman Centre's website.