MLS-C01 Modeling Practice Question
Which TWO of the following are appropriate use cases for using Amazon SageMaker BlazingText? (Choose 2)
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
✓
Text classification using supervised learning.
Amazon SageMaker BlazingText supports text classification using supervised learning. Option C is correct because BlazingText can learn word embeddings (e.g., Word2Vec) from large text corpora. Option B is incorrect because time series forecasting is not a capability of BlazingText; it is suited for NLP tasks. Option D is incorrect because BlazingText does not support image classification—that would require a different service or algorithm. Option E is incorrect because sequence-to-sequence translation is not supported by BlazingText; it is designed for word-level embeddings and text classification.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Text classification using supervised learning.
Why this is correct
BlazingText has supervised mode.
- ✗
Time series forecasting.
Why it's wrong here
Not supported.
- ✓
Learning word embeddings from a large text corpus.
Why this is correct
BlazingText supports Word2Vec.
- ✗
Classifying images.
Why it's wrong here
BlazingText is for text.
- ✗
Sequence-to-sequence translation.
Why it's wrong here
Not supported.
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