MLS-C01 Modeling Practice Question
Network Topology
Refer to the exhibit. A training job failed with the error shown. What is the most likely cause?
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
✓
The training data contains missing values or outliers that cause numerical instability
The error message explicitly states that the input contains NaN or infinity, which indicates missing values or outliers in the training data. This causes numerical instability during training. Option A is incorrect because the error is about input data, not model architecture. Option C is incorrect because the error is from the training script, not insufficient memory. Option D is incorrect because the error is about input values, not runtime limits.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The model architecture is incorrect
Why it's wrong here
Architecture issues would not produce this error.
- ✓
The training data contains missing values or outliers that cause numerical instability
Why this is correct
Error indicates NaN or infinity in input.
- ✗
The instance type does not have enough memory
Why it's wrong here
Not a memory error.
- ✗
The training job exceeded the maximum runtime
Why it's wrong here
Different failure reason.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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