AWS Certified AI Practitioner AIF-C01 Practice Question
A team exports a spreadsheet where each row lists a customer and each column contains attributes such as age, subscription type, and churn status. When preparing this dataset for a machine learning model, which data type does it represent?
Data arranged in rows and columns like a spreadsheet is considered tabular data. Each row is an independent record and each column is a feature, which is the typical structure used by algorithms such as linear regression or decision trees. Unstructured text, time-series, and image data have different formats: text is free-form strings, time-series emphasizes sequence and timestamp order, and image data consists of pixel arrays. Therefore, only the tabular option correctly describes the customer spreadsheet.
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What is tabular data in machine learning?
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How does tabular data differ from time-series data?
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Why is tabular data preferred for decision tree algorithms?
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What is tabular data in machine learning?
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How do machine learning models handle missing data in tabular datasets?
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Why can’t unstructured, time-series, or image data be used as tabular data?
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AWS Certified AI Practitioner AIF-C01
Fundamentals of AI and ML
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