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AWS Certified Machine Learning - Specialty

  • Topic 1 Question 341

    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.

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