Ultimate Hyperparameter Tuning and AutoML Tutorial: From Zero

Deep learning is a family of machine learning methods that use multi-layer neural networks.

The F1-score is a metric that balances precision and recall, providing a single value to assess model performance.

AUC-ROC (Area Under the Receiver Operating Characteristic curve) measures the ability of a binary classifier to distinguish between classes, particularly useful for imbalanced datasets.

RMSE (Root Mean Squared Error) quantifies the average difference between predicted values and actual values, reflecting the sensitivity to outliers in regression problems.