MLA-C01 Data Preparation for Machine Learning Practice Question
A company is building a real-time inference pipeline for an ML model. The raw data arrives in JSON format via Amazon Kinesis Data Streams. Before invoking the SageMaker endpoint, the data must be preprocessed to match the training data format. Which THREE steps should be included in the preprocessing function? (Select THREE)
⚠ Common exam trap
Candidates often confuse the preprocessing function's scope with broader MLOps tasks like model retraining, or assume a specific serialization format like CSV is required when JSON is natively supported by SageMaker endpoints.
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
✓
Ensure that missing values are handled consistently with the training phase
The preprocessing function must handle missing values identically to how they were handled during training to maintain data consistency. If the training phase used mean imputation for a numeric feature, the inference pipeline must apply the same mean value; otherwise, the model will receive unexpected input distributions, degrading prediction accuracy.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Ensure that missing values are handled consistently with the training phase
Why this is correct
Missing value handling must be identical to training to avoid errors.
- ✗
Convert the data to a CSV string for model input
Why it's wrong here
SageMaker endpoints accept JSON; converting to CSV adds unnecessary complexity.
- ✓
Apply the same feature engineering transformations (e.g., scaling, encoding) that were used during training
Why this is correct
Ensures inference data matches training data format.
- ✗
Re-train the model periodically using new data
Why it's wrong here
Re-training is a separate offline process, not part of inference preprocessing.
- ✓
Parse the JSON payload
Why this is correct
Necessary to extract features from raw JSON.
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