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Answer: Train an object detection model in AutoML by using the annotated image data.
The correct answer is B: Train an object detection model in AutoML by using the annotated image data. AutoML is well-suited for creating high-quality models quickly with minimal setup, making it ideal for proof-of-concept projects. It automates many aspects of model training, such as hyperparameter tuning, feature engineering, and architecture selection, which significantly reduces manual effort and speeds up development. Given that the data is already annotated, AutoML can efficiently handle the object detection tasks required for identifying damaged parts in the images.
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You are part of a data science team at an auto insurance company tasked with developing a proof-of-concept machine learning application. The application aims to use images of damaged vehicles to identify damaged parts. Your team has assembled a set of annotated images from the company's damage claim documents database. Each image is annotated with bounding boxes indicating the damaged parts and their respective names. You have sufficient budget and access to Google Cloud services to train your models. Given the need for quick initial model development, what should you do?
A
Download a pre-trained object detection model from TensorFlow Hub. Fine-tune the model in Vertex AI Workbench by using the annotated image data.
B
Train an object detection model in AutoML by using the annotated image data.
C
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.
D
Train an object detection model in Vertex AI custom training by using the annotated image data.
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