Topic 1 Question 432
An ecommerce company wants to use machine learning (ML) algorithms to build and train models. The company will use the models to visualize complex scenarios and to detect trends in customer data. The architecture team wants to integrate its ML models with a reporting platform to analyze the augmented data and use the data directly in its business intelligence dashboards.
Which solution will meet these requirements with the LEAST operational overhead?
Use AWS Glue to create an ML transform to build and train models. Use Amazon OpenSearch Service to visualize the data.
Use Amazon SageMaker to build and train models. Use Amazon QuickSight to visualize the data.
Use a pre-built ML Amazon Machine Image (AMI) from the AWS Marketplace to build and train models. Use Amazon OpenSearch Service to visualize the data.
Use Amazon QuickSight to build and train models by using calculated fields. Use Amazon QuickSight to visualize the data.
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Amazon SageMaker is a fully managed service that provides a complete set of tools and capabilities for building, training, and deploying ML models. It simplifies the end-to-end ML workflow and reduces operational overhead by handling infrastructure provisioning, model training, and deployment. To visualize the data and integrate it into business intelligence dashboards, Amazon QuickSight can be used. QuickSight is a cloud-native business intelligence service that allows users to easily create interactive visualizations, reports, and dashboards from various data sources, including the augmented data generated by the ML models.
👍 2LONGMEN2023/05/18- 正解だと思う選択肢: B
B sagemaker provide deploy ml models
👍 1nosense2023/05/15 - 正解だと思う選択肢: B
ML== SageMaker
👍 1Efren2023/05/16
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