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An AI practitioner who has minimal ML knowledge wants to predict employee attrition without writing code. Which Amazon SageMaker feature meets this requirement?
The correct answer is A because Amazon SageMaker Canvas is designed specifically for users with little or no machine learning or programming experience. It provides a visual interface to build ML models by simply uploading data, performing analysis, and generating predictions using a no-code environment.
From the AWS documentation:
'Amazon SageMaker Canvas enables business analysts and other users to generate accurate ML predictions using a visual, point-and-click interface without writing code or having prior ML experience.'
This feature allows the user to:
Import datasets (e.g., HR data)
Automatically explore the data
Select the prediction column (e.g., attrition)
Train the model
Generate and export predictions
Explanation of other options:
B . SageMaker Clarify is used to detect bias and explain ML predictions but not to build models or make predictions without code.
C . SageMaker Model Monitor monitors model quality in production but doesn't build or train models.
D . SageMaker Data Wrangler is used for data preprocessing and transformation but still requires some technical configuration.
Referenced AWS AI/ML Documents and Study Guides:
Amazon SageMaker Canvas Developer Guide
AWS Certified Machine Learning Specialty Study Guide -- AutoML and No-Code Tools Section
AWS Machine Learning Blog: ''Predict Employee Attrition with SageMaker Canvas''