- Learn cross-validation and hyperparameter tuning.
- Understand overfitting, bias-variance trade-offs, and model optimization.
- Apply feature engineering to enhance predictive accuracy.
- Gain hands-on experience with boosting and bagging techniques.
- Skills are directly transferable to real-world machine learning projects.
