A machine learning (ML) specialist collected daily product usage data for a group of customers. The ML specialist appended customer metadata such as age and gender from an external data source. The ML specialist wants to understand product usage patterns for each day of the week for customers in specific age groups. The ML specialist creates two categorical features named dayofweek and binned_age, respectively. Which approach should the ML specialist use discover the relationship between the two new categorical features?

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B. Create crosstabs for day_of_week and binned_age. Crosstabs, or cross-tabulations, are used to display the joint distribution of two or more categorical variables. They show the frequency or proportion of observations for each combination of categories, making them ideal for understanding how product usage patterns vary across different days of the week and age groups.

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A. Create a scatterplot for day_of_week and binned_age. A scatterplot is used to visualize the relationship between two numerical variables and is not suitable for analyzing the relationship between two categorical features.

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C. Create word clouds for day_of_week and binned_age. Word clouds are used for visualizing the frequency of words in text data and are irrelevant for understanding the relationship between numerical or categorical features.

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D. Create a boxplot for day_of_week and binned_age. A boxplot is typically used to display the distribution of a numerical variable across different categories of a categorical variable or to compare distributions, not to directly show the relationship between two categorical features.

A machine learning (ML) specialist collected daily product usage data for a group of customers. The ML specialist appended customer metadata such as age and gender from an external data source. The…

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