Exam Professional Machine Learning Engineer topic 1 question 67 discussion

Actual exam question from Google's Professional Machine Learning Engineer

Question #: 67
Topic #: 1

[All Professional Machine Learning Engineer Questions]

You have a large corpus of written support cases that can be classified into 3 separate categories: Technical Support, Billing Support, or Other Issues. You need to quickly build, test, and deploy a service that will automatically classify future written requests into one of the categories. How should you configure the pipeline?

A. Use the Cloud Natural Language API to obtain metadata to classify the incoming cases.
B. Use AutoML Natural Language to build and test a classifier. Deploy the model as a REST API.
C. Use BigQuery ML to build and test a logistic regression model to classify incoming requests. Use BigQuery ML to perform inference.
D. Create a TensorFlow model using Google’s BERT pre-trained model. Build and test a classifier, and deploy the model using Vertex AI.

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Suggested Answer: B 🗳️

by Vedjha at Dec. 8, 2022, 12:07 p.m.

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wish0035

Highly Voted 2 years ago

Selected Answer: B

ans: B A => no, you need customization. C, B => more work and complexity B => AutoML is easier and faster and "you need to quickly build, test, and deploy". Also the REST API part fits our use case.

upvoted 9 times

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