University of Cape Town
Department of Statistical Sciences
STA4026S - Honours Analytics
Section A: Theory and Application of Supervised Learning

A 6-lecture (double-period) section on supervised learning.

The outline is as follows:

L1: Introduction to supervised learning

• Bias-Variance trade-off
  
• Model validation

L2: Model Selection & Regularisation

• Linear regression models
  
• L_1 & L_2 regularisation
  
• ElasticNet
  

L3: Classification Models

• Logistic regression
  
• Model evaluation
  
• ROC curves
  
• Regularisation

L4: Beyond Linearity

• Polynomial regression
  
• KNN

L5 & L6: Tree-based Methods

• CART
  
• Random forests
  
• Boosting
  

This repo was initially generated from a bookdown template available here: https://github.com/jtr13/bookdown-template.