Train / Test / Validation Split

Summary

Splitting data so a model is trained on one portion, tuned on a second (validation), and finally evaluated on a completely unseen third (test) — the basic discipline that prevents you from fooling yourself about model performance.

• 1Practice a train/test split and explain why test data must never touch the training process.
• 2Learn why validation data exists separately from test data (for tuning, not final evaluation).
• 3Understand data leakage — when test information accidentally influences training.