Question 1easymultiple choice
Full question →easymultiple choiceObjective-mapped
A data scientist trains a classification model to distinguish between images of cats and dogs. The model achieves 99% accuracy on the training set but only 75% accuracy on a validation set. Which concept best describes this situation?
Answer choices
Why each option matters
Good practice is not just finding the correct option. The wrong answers often show the exact trap the exam wants you to fall into.
A
Distractor review
Underfitting
Underfitting occurs when the model performs poorly on both training and validation sets, not just validation.
B
Best answer
Overfitting
This is correct. The model performs well on training but poorly on validation, indicating it has learned noise and is not generalizing.
C
Distractor review
Model bias
Model bias refers to systematic errors due to incorrect assumptions, but the performance pattern here is more about variance from overfitting.
D
Distractor review
Data leakage
Data leakage would make the validation performance artificially high, not low, because the model would have used information from outside the training set.
Common exam trap
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Technical deep dive
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
- Static NAT maps one inside address to one outside address.
- PAT allows many inside hosts to share one public address using ports.
- Inside local and inside global describe the private and translated addresses.
- NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
- Identify inside and outside interfaces first.
- Check whether the scenario needs static NAT, dynamic NAT or PAT.
- Do not confuse NAT matching ACLs with normal packet-filtering intent.
Related practice questions
Related AI-900 practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
More questions from this exam
Keep practising from the same exam bank, or move into a focused topic page if this question exposed a weak area.
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FAQ
Questions learners often ask
What does this AI-900 question test?
Static NAT maps one inside address to one outside address.
What is the correct answer to this question?
The correct answer is: Overfitting — The significant gap between high training accuracy and lower validation accuracy is a classic sign of overfitting. The model has memorized the training data too well, including noise and irrelevant patterns, and fails to generalize to new unseen data. Underfitting would show poor performance on both sets. Model bias refers to assumptions that cause systematic errors, but here the issue is variance due to overfitting. Data leakage would allow the model to use information not available during inference, typically leading to overly optimistic validation scores, not a large gap.
What should I do if I get this AI-900 question wrong?
Then try more questions from the same exam bank and focus on understanding why the wrong options are tempting.
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