7.3 Training vs Testing Data

When building an ML model, we split our data into at least two parts. The training set is what the model learns from. The testing set is kept hidden during training and used only at the end to measure how well the model performs on data it has never seen.

Think of a student preparing for an exam. The practice questions are like training data. The actual exam, with new questions, is like the testing data — it shows whether the student truly learned the concepts or just memorised the practice sheet.