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AI-102 Practice Question: Which TWO actions can reduce the cost of using…
Which TWO actions can reduce the cost of using Azure Custom Vision for image classification? (Choose two.)
⚠ Common exam trap
Candidates often confuse 'faster training' with 'reduced cost' but may overlook that compact domains specifically lower resource consumption, while options like reducing images or iterations seem intuitive but are not explicitly cost-reduction features in the exam context.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use the compact domain for faster training.
Using the compact domain in Azure Custom Vision reduces model complexity and training time, which directly lowers compute costs. Compact domains are optimized for edge deployment and require fewer resources, making them more cost-effective for image classification tasks.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Include negative samples in the dataset.
Why it's wrong here
Negative samples improve accuracy but increase cost.
- ✓
Use the compact domain for faster training.
Why this is correct
Compact domain reduces training time and cost.
- ✓
Reduce the number of training images.
Why this is correct
Fewer images reduce transaction costs.
- ✗
Use a larger image size for higher accuracy.
Why it's wrong here
Larger images require more compute.
- ✗
Increase the number of training iterations.
Why it's wrong here
More iterations cost more.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI-102 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-102 exam.