Assessing model performance and improving it.
Metrics: Accuracy, Precision-Recall, ROC Curve, Mean Squared Error (MSE).
Techniques: Cross-validation, Hyperparameter tuning (Grid Search, Random Search).
Sub Tracks:
Model Performance Metrics
Cross-Validation & Resampling Techniques
Hyperparameter Tuning & Optimization
Model Interpretability & Explainability