Google Cloud Professional Machine Learning Engineer — 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?

Answer options

• 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.

Correct answer: B

Explanation

The correct answer is B because AutoML is designed for users who want to train models quickly without needing deep expertise in machine learning, making it ideal for generating a model from annotated image data. Options A and C involve additional steps like fine-tuning or setting up pipelines, which are unnecessary for an initial model. Option D suggests custom training, which is more complex and time-consuming compared to the streamlined AutoML process.