MLS-C01 Modeling Practice Question
A data scientist is building a recommendation system for an e-commerce platform. The dataset contains user interactions (clicks, purchases) and item metadata. The scientist wants to use matrix factorization. Which algorithm should be used?
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
✓
SageMaker Factorization Machines
SageMaker Factorization Machines is specifically designed for recommendation systems and matrix factorization tasks. Option A (SageMaker Image Classification) is used for image classification, not matrix factorization. Option B (SageMaker BlazingText) is used for text classification or word embeddings, not for recommendation. Option C (SageMaker XGBoost) is a gradient boosting algorithm for regression and classification, not matrix factorization.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
SageMaker Image Classification
Why it's wrong here
Image Classification is for images.
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SageMaker BlazingText
Why it's wrong here
BlazingText is for word embeddings.
- ✗
SageMaker XGBoost
Why it's wrong here
XGBoost is not for matrix factorization.
- ✓
SageMaker Factorization Machines
Why this is correct
Factorization Machines are designed for recommendation and matrix factorization.
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