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Training Course Details

Advanced Machine Learning with Tidymodels

Advanced Machine Learning with Tidymodels

Course Level: Advanced

A course that builds on the material covered in our Machine Learning with Tidymodels course. We take a look at how we can fit linear discriminant analysis (LDA) models using {discrim}, assessing model reliability using V-fold cross validation, pre-processing, tree-based models & much more. If you wish to explore the abundance of model fitting techniques {tidymodels} has to offer, then this course is certainly for you!

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Course Details

  • Course Outline
  • Learning Outcomes
  • Materials
  • Prior Knowledge

Course Outline

  • Qualitative modelling: An introduction to Linear Discriminant Analaysis (LDA).
  • Fitting LDA models & model prediction: Using {discrim} to add aditional bindings to {parnsip}, to fit LDA models
  • Advanced model assessment: V-fold cross validation using {workflows} and {tune}
  • Penalised regression techniques: Ridge regrssion, lasso and elastic net
  • Tree-Based Models: Bagging, random forrests and boosting

Learning Outcomes

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

Materials

  • Example course material for 'Advanced Machine Learning with Tidymodels
  • Example course material for 'Advanced Machine Learning with Tidymodels
  • Example course material for 'Advanced Machine Learning with Tidymodels
  • Example course material for 'Advanced Machine Learning with Tidymodels
  • Example course material for 'Advanced Machine Learning with Tidymodels

Prior Knowledge

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.

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