Topic 1 Question 204
You work for an auto insurance company. You are preparing a proof-of-concept ML application that uses images of damaged vehicles to infer damaged parts. Your team has assembled a set of annotated images from damage claim documents in the company’s database. The annotations associated with each image consist of a bounding box for each identified damaged part and the part name. You have been given a sufficient budget to train models on Google Cloud. You need to quickly create an initial model. What should you do?
Download a pre-trained object detection model from TensorFlow Hub. Fine-tune the model in Vertex AI Workbench by using the annotated image data.
Train an object detection model in AutoML by using the annotated image data.
Create a pipeline in Vertex AI Pipelines and configure the AutoMLTrainingJobRunOp component to train a custom object detection model by using the annotated image data.
Train an object detection model in Vertex AI custom training by using the annotated image data.
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- 正解だと思う選択肢: B
Speed: AutoML excels in creating high-quality models with minimal code and setup, significantly accelerating model development. Ease of use: It provides a user-friendly interface and automates many aspects of model training, making it accessible even for those without extensive ML expertise. Automatic optimization: AutoML automatically handles hyperparameter tuning, feature engineering, and architecture selection, reducing manual effort and expertise required. Custom object detection: It supports custom object detection tasks, directly addressing the need to identify damaged parts in images.
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