Match each SageMaker built-in algorithm to its primary use case.
Drag a concept onto its matching description — or click a concept then click the description.
Gradient boosted trees for regression and classification
Word2Vec and text classification
Learning embeddings for pairs of objects
Anomaly detection in IP traffic
Time series forecasting
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Linear Learner: Used for regression and binary/multiclass classification.
Correct matches: Linear Learner → regression/classification, Object Detection → image object detection. Common confusions: swapping XGBoost (gradient boosting) with BlazingText (text vectors).
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Linear Learner: Used for regression and binary/multiclass classification.
Why this is correct
Linear Learner is designed for supervised learning tasks including regression and classification.
XGBoost: Used for word2vec and text classification.
Why it's wrong here
Incorrect — XGBoost is a gradient boosting algorithm, not for word2vec; that is BlazingText.
BlazingText: Gradient boosting algorithm for classification and regression.
Why it's wrong here
Incorrect — BlazingText is for text embedding and classification, not gradient boosting; that is XGBoost.
Object Detection: Detects objects in images.
Why this is correct
Object Detection algorithm is used for identifying and localizing objects in images.
Go deeper
About these practice questions
Courseiva writes every MLS-C01 question from scratch — 1,672 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLS-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 MLS-C01 exam.