Page Reader AI | Exam Professional Machine Learning Engineer topic 1 question 204 discussion

Exam Professional Machine Learning Engineer topic 1 question 204 discussion - ExamTopics

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Problem Description

An auto insurance company is developing a proof-of-concept ML application to identify damaged vehicle parts from images. Annotated images with bounding boxes and part names are available. The goal is to quickly create an initial model using Google Cloud.

Solution Options

Four options are presented:

A. Fine-tune a pre-trained object detection model from TensorFlow Hub in Vertex AI Workbench.
B. Train an object detection model using AutoML.
C. Create a Vertex AI Pipelines with AutoMLTrainingJobRunOp for custom object detection model training.
D. Train an object detection model using Vertex AI custom training.

Suggested Answer

The suggested answer is B, using AutoML for training.

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?

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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