Overfitting
/ˌəʊvəˈfɪtɪŋ/
Definition
When an ML model learns training data too precisely — including noise — and fails to generalise to new examples.
Example in context
"99% training accuracy but 62% on the test set — classic overfitting. We added dropout and reduced model complexity."
Related terms
Practice this term
Master Overfitting in context by working through exercises in the Data Science & ML module. You'll see the term used in real engineering scenarios with multiple-choice, fill-in-the-blank, and matching drills.