Which type of visualization should the ML engineer use to meet these requirements?

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A car company has dealership locations in multiple cities.The company uses a machine learning (ML) recommendation system to market cars to its customers.An ML engineer trained the ML recommendation model on a dataset that includes multiple attributes about each car.The dataset includes attributes such as car brand, car type, fuel efficiency, and price.The ML engineer uses Amazon SageMaker Data Wrangler to analyze and visualize data.The ML engineer needs to identify the distribution of car prices for a specific type of car.

Which type of visualization should the ML engineer use to meet these requirements?

Use the SageMaker Data Wrangler scatter plot visualization to inspect the relationship between the car price and type of car.

Use the SageMaker Data Wrangler quick model visualization to quickly evaluate the data and produce importance scores for the car price and type of car.

Use the SageMaker Data Wrangler anomaly detection visualization to Identify outliers for the specific features.

Use the SageMaker Data Wrangler histogram visualization to inspect the range of values for the specific feature.

Explanations:

Scatter plots are used to analyze relationships between two variables, not for viewing the distribution of a single variable such as car prices.

Quick model visualization is used to evaluate feature importance rather than visualizing the distribution of a specific feature.

Anomaly detection visualization is used to detect outliers, not for viewing the distribution of a feature like car prices.

A histogram is suitable for showing the distribution of values for a specific feature, making it ideal for analyzing the range and frequency of car prices.

2026-04-01

2 Comments

  1. Donald
    Author

    I systematize that the answer is:
    Use the SageMaker Data Wrangler histogram visualization to inspect the range of values for the specific feature.

  2. Gerald
    Author

    I guess:
    Use the SageMaker Data Wrangler histogram visualization to inspect the range of values for the specific feature.

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