Chapter 1 Prerequisites

The reader should have some basic knowledge of the following topics:

Statistical learning
- Train/ test split
- Cross-validation
- Overfitting
- Gradient descent
- Bias variance trade-off
- Hyperparameters
Regression trees and random forest models
Basic R knowledge (only for the applied part)