MLS-C01 Practice Question: Machine Learning Implementation and Operations
A data scientist uses SageMaker to train a model. The training job takes 10 hours, but the team needs to reduce costs. Which approach is MOST cost-effective?
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
✓
Enable Managed Spot Training
Managed Spot Training leverages Amazon EC2 Spot Instances, which offer spare compute capacity at up to 90% discount compared to On-Demand instances. This makes it the most cost-effective approach for reducing training costs. Option A is correct. Option B (using Automatic Model Tuning) is designed for hyperparameter optimization, not cost reduction, and may increase cost due to additional training jobs. Option C (using a larger instance type) finishes faster but at a higher per-hour cost, potentially increasing total cost. Option D (using Distributed Training with more instances) increases resource usage and cost, though it may reduce training time.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Enable Managed Spot Training
Why this is correct
Spot instances offer significant discounts, reducing cost.
- ✗
Use SageMaker Automatic Model Tuning
Why it's wrong here
Tuning adds additional training jobs, increasing cost.
- ✗
Use a larger instance type to finish faster
Why it's wrong here
Larger instances cost more per hour, potentially increasing cost.
- ✗
Use SageMaker Distributed Training with more instances
Why it's wrong here
More instances increase total cost even if training time decreases.
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