Microsoft AI-102 Designing and Implementing a Microsoft Azure AI Solution 09 31Oct2024 - Practice Quiz

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Question 1 of 30

A data scientist is preparing a dataset for a machine learning model that predicts customer churn for a telecommunications company. The dataset includes features such as customer demographics, account information, and usage patterns. The data scientist notices that the dataset has missing values, outliers, and categorical variables that need to be encoded. Which of the following steps should the data scientist prioritize to ensure the dataset is ready for modeling?

Impute missing values using the median for numerical features and mode for categorical features, then apply one-hot encoding to categorical variables.

Remove all rows with missing values and convert all categorical variables to numerical values using label encoding.

Normalize all numerical features to a range of 0 to 1 and ignore the categorical variables entirely.

Replace outliers with the mean of the feature and apply binary encoding to categorical variables.

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