MLA-C01 ML Model Development Practice Question
Which SageMaker built-in algorithm is 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 built-in algorithm specifically for time series forecasting. BlazingText is for text, XGBoost is for tabular data, and IP Insights is for anomaly detection in IP traffic.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
BlazingText
Why it's wrong here
BlazingText is for word embeddings and text classification.
- ✓
DeepAR
Why this is correct
DeepAR is used for time series forecasting.
- ✗
IP Insights
Why it's wrong here
IP Insights is for network anomaly detection.
- ✗
XGBoost
Why it's wrong here
XGBoost is for supervised learning on tabular data, not time series.
Go deeper
Related to this question
About these practice questions
One of 835 original MLA-C01 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
JA
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.