Topic 1 Question 265
A company wants to conduct targeted marketing to sell solar panels to homeowners. The company wants to use machine learning (ML) technologies to identify which houses already have solar panels. The company has collected 8,000 satellite images as training data and will use Amazon SageMaker Ground Truth to label the data.
The company has a small internal team that is working on the project. The internal team has no ML expertise and no ML experience.
Which solution will meet these requirements with the LEAST amount of effort from the internal team?
Set up a private workforce that consists of the internal team. Use the private workforce and the SageMaker Ground Truth active learning feature to label the data. Use Amazon Rekognition Custom Labels for model training and hosting.
Set up a private workforce that consists of the internal team. Use the private workforce to label the data. Use Amazon Rekognition Custom Labels for model training and hosting.
Set up a private workforce that consists of the internal team. Use the private workforce and the SageMaker Ground Truth active learning feature to label the data. Use the SageMaker Object Detection algorithm to train a model. Use SageMaker batch transform for inference.
Set up a public workforce. Use the public workforce to label the data. Use the SageMaker Object Detection algorithm to train a model. Use SageMaker batch transform for inference.
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B. Set up a private workforce that consists of the internal team. Use the private workforce to label the data. Use Amazon Rekognition Custom Labels for model training and hosting.
By setting up a private workforce consisting of the internal team and using Amazon Rekognition Custom Labels, the company can leverage the labeling capabilities of the internal team to label the data. Amazon Rekognition Custom Labels can then be used for model training and hosting.
This option eliminates the need for additional complex steps such as active learning or object detection algorithm training, which may require more ML expertise and effort from the internal team. Instead, it relies on the simplicity and convenience of using Amazon Rekognition Custom Labels for model training and hosting, making it the least effort-intensive option for the team with no ML expertise or experience.
👍 3RRST2023/06/14- 正解だと思う選択肢: B
B is correct
👍 3SandeepGun2023/06/17 It's A due to small team on the project and minimal effort from the team required. SageMaker Ground Truth active learning feature can speed up the labeling process for 8000 images.
👍 2ADVIT2023/07/07
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