MLA-C01 ML Model Development Practice Question
Which SageMaker built-in algorithm is specifically designed for time series forecasting?
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
✓
DeepAR
DeepAR is a supervised learning algorithm for forecasting scalar time series using recurrent neural networks. The other algorithms are for different tasks: XGBoost for classification/regression, BlazingText for NLP, and Image Classification for computer vision.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Image Classification
Why it's wrong here
Image Classification is for computer vision.
- ✗
BlazingText
Why it's wrong here
BlazingText is for word2vec and text classification.
- ✓
DeepAR
Why this is correct
DeepAR is designed for time series forecasting.
- ✗
XGBoost
Why it's wrong here
XGBoost is for classification and regression, not specialized for time series.
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Written by Johnson Ajibi, MSc IT Security
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This MLA-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MLA-C01 exam.