Level: Intermediate, some experience required
Keywords: R, Machine Learning, Tree-based Models, Analytics
Note: Please see Prerequisite Section Below
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Tree-based machine learning models, have provided the foundation for some of the most advanced, accessible and accurate machine learning techniques used in data science. During this session we will explore a theoretical and practical overview of decision trees as one example of tree-based methods and introduce how to interpret and evaluate these models.
Please note: Due to time constraints, this session will not cover Decision Tree Pruning, rather this will be covered in the next session Introduction to Machine Learning - Tree-based Models 2.
Basic programming skills in R required, awareness and basic knowledge of machine learning techniques, applications and types useful but not essential.
Access to R & Rstudio (R’s Graphical User Interface, or RStudio Cloud (Free Online)), Provided ZIP File .zip.