MLA-C01 ML Model Development Practice Question
Which SageMaker built-in algorithm should be used for forecasting time series data with seasonal patterns?
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 time series forecasting that handles seasonality and trends.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
IP Insights
Why it's wrong here
IP Insights detects anomalous IP addresses.
- ✗
BlazingText
Why it's wrong here
BlazingText is for text classification and word embeddings.
- ✓
DeepAR
Why this is correct
DeepAR is specifically designed for time series forecasting.
- ✗
Factorization Machines
Why it's wrong here
Factorization Machines are for recommendation and click prediction.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.