A model reaches near-zero training error but much higher validation error. What is the most likely issue?
Select an answer to reveal the explanation.
Short Explanation and Infographic
Here's the deal — Overfitting: the model memorized training patterns that do not generalize
Full explanation below image
Full Explanation
The correct answer is: Overfitting: the model memorized training patterns that do not generalize. This matches standard ML/AI engineering practice for Domain 1: ML Fundamentals. Distractors confuse adjacent concepts or unsafe operational shortcuts. In production, validate with held-out data, monitoring, and governance appropriate to risk.