nerdexam
GoogleGoogle

PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #25

PROFESSIONAL-MACHINE-LEARNING-ENGINEER Question #25: Real Exam Question with Answer & Explanation

Sign in or unlock PROFESSIONAL-MACHINE-LEARNING-ENGINEER to reveal the answer and full explanation for question #25. The question stem and answer options stay visible for context.

Submitted by parkjh· Apr 18, 2026ML model development

Question

Your team has been tasked with creating an ML solution in Google Cloud to classify support requests for one of your platforms. You analyzed the requirements and decided to use TensorFlow to build the classifier so that you have full control of the model's code, serving, and deployment. You will use Kubeflow pipelines for the ML platform. To save time, you want to build on existing resources and use managed services instead of building a completely new model. How should you build the classifier?

Options

  • AUse the Natural Language API to classify support requests.
  • BUse AutoML Natural Language to build the support requests classifier.
  • CUse an established text classification model on AI Platform to perform transfer learning.
  • DUse an established text classification model on AI Platform as-is to classify support requests.

Unlock PROFESSIONAL-MACHINE-LEARNING-ENGINEER to see the answer

You've previewed enough free PROFESSIONAL-MACHINE-LEARNING-ENGINEER questions. Unlock PROFESSIONAL-MACHINE-LEARNING-ENGINEER for full answers, explanations, the timed quiz mode, progress tracking, and the master PDF. Question stem and options stay visible so you can still see what's on the exam.

Topics

#Transfer Learning#Google Cloud AI Platform#Custom TensorFlow Models#Text Classification
Full PROFESSIONAL-MACHINE-LEARNING-ENGINEER PracticeBrowse All PROFESSIONAL-MACHINE-LEARNING-ENGINEER Questions