By the end of the course participants will be able to…

• use {parsnip} to build LDA models and visualise boundaries
• assess model validity using V-fold cross validation
• apply penalised regression techniques that penalises models with a high number of predictor variables
• use tree-based models in regression & classification problems, to split the predictor space into numerous simple regions

It will be assumed that participants are familiar with R. For example inputting data, basic visualisation, basic data structures and use of functions. In addition, attendees should be familar with the concepts covered in our Machine Learning with Tidymodels course.