Validation

Validation is a critical step used to understand whether a model is not only doing well on training data but is also adapting properly to unseen examples. A validation split kept separate from training data helps guide decisions such as hyperparameter tuning, early stopping, and model comparison. Without proper validation, teams often mistake training success for real success. For that reason, validation is not just a checkpoint; it is part of honest modeling discipline.