Missing Data and Feature Preparation

Scenario

You're preparing a tabular dataset for a supervised learning task and need a clean training pipeline before comparing models.

Question

How would you handle missing values, normalize data, and prepare datasets for modeling?

Problem

Scenario

You're preparing a tabular dataset for a supervised learning task and need a clean training pipeline before comparing models.

Question

How would you handle missing values, normalize data, and prepare datasets for modeling?

Example Dataset

size·120K policy application records, 38 featurestarget·Policy lapse within 12 monthsfeatures·Mixed numerical, categorical, ordinal, and binary fieldsmissingness·1% to 18% depending on field

Problem

Scenario

You're preparing a tabular dataset for a supervised learning task and need a clean training pipeline before comparing models.

Question

How would you handle missing values, normalize data, and prepare datasets for modeling?

Example Dataset

size·120K policy application records, 38 featurestarget·Policy lapse within 12 monthsfeatures·Mixed numerical, categorical, ordinal, and binary fieldsmissingness·1% to 18% depending on field

Problem

Scenario

You're preparing a tabular dataset for a supervised learning task and need a clean training pipeline before comparing models.

Question

How would you handle missing values, normalize data, and prepare datasets for modeling?

Example Dataset

size·120K policy application records, 38 featurestarget·Policy lapse within 12 monthsfeatures·Mixed numerical, categorical, ordinal, and binary fieldsmissingness·1% to 18% depending on field

Interview Guides

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Scenario

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Example Dataset

Problem

Scenario

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Example Dataset

Missing Data and Feature Preparation

Problem

Scenario

Question

Example Dataset

Problem

Scenario

Question

Example Dataset