This project implements a Decision Tree classifier to predict poker hands from a dataset of playing cards.
The main goals are:
- Preprocess categorical features (cards & suits) using One-Hot Encoding
- Train a Decision Tree model with scikit-learn
- Evaluate performance with different metrics
- Visualize the decision tree for better interpretability