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Free PROFESSIONAL MACHINE LEARNING ENGINEER Exam Braindumps
Professional Machine Learning Engineer Questions 161–165 (page: 34)

Updated On: 25-Oct-2026
Page 34 of 82
PDF with 402 Questions

You work at an organization that manages a popular payment app. You built a fraudulent transaction detection model by using scikit-learn and deployed it to an Agent Platform endpoint. The endpoint is currently using 1 e2-standard-2 machine with 2 vCPUs and 8 GB of memory. You discover that traffic on the gateway fluctuates to four times more than the endpoint's capacity. You need to address this issue by using the most cost-effective approach.
What should you do?

  1. Re-deploy the model with a TPU accelerator.
  2. Change the machine type to e2-highcpu-32 with 32 vCPUs and 32 GB of memory.
  3. Set up a monitoring job and an alert for CPU usage. If you receive an alert, scale the vCPUs as needed.
  4. Increase the number of maximum replicas to 6 nodes, each with 1 e2-standard-2 machine.

Answer(s): D

Explanation:

Increasing the number of replicas allows the endpoint to handle fluctuating traffic by distributing requests across multiple instances of the same machine type. This horizontal scaling is more cost-effective than upgrading to a much larger machine or using specialized accelerators when the workload is CPU-bound and fluctuating.



You are an ML engineer at a global shoe store. You manage the ML models for the company’s website. You are asked to build a model that will recommend new products to the user based on their purchase behavior and similarity with other users.
What should you do?

  1. Build a classification model
  2. Build a knowledge-based filtering model
  3. Build a collaborative-based filtering model
  4. Build a regression model using the features as predictors

Answer(s): C

Explanation:


Reference:

https://cloud.google.com/solutions/recommendations-using-machine-learning-on-compute-engine



Your team frequently creates new ML models and runs experiments. Your team pushes code to a single repository hosted on Cloud Source Repositories. You want to create a continuous integration pipeline that automatically retrains the models whenever there is any modification of the code.
What should be your first step to set up the CI pipeline?

  1. Configure a Cloud Build trigger with the event set as "Pull Request".
  2. Configure a Cloud Build trigger with the event set as "Push to a branch".
  3. Configure a Cloud Run function that builds the repository each time there is a code change.
  4. Configure a Cloud Run function that builds the repository each time a new branch is created.

Answer(s): B



You work for a multinational organization that has recently begun operations in Spain. Teams within your organization will need to work with various Spanish documents, such as business, legal, and financial documents. You want to use machine learning to help your organization get accurate translations quickly and with the least effort. Your organization does not require domain-specific terms or jargon.
What should you do?

  1. Create a Vertex AI Workbench notebook instance. In the notebook, extract sentences from the documents, and train a custom AutoML text model.
  2. Use Google Translate to translate 1,000 phrases from Spanish to English. Using these translated pairs, train a custom AutoML Translation model.
  3. Use the Document Translation feature of the Cloud Translation API to translate the documents.
  4. Create a Vertex AI Workbench notebook instance. In the notebook, convert the Spanish documents into plain text, and create a custom TensorFlow seq2seq translation model.

Answer(s): C



You have recently developed a custom model for image classification by using a neural network. You need to automatically identify the values for learning rate, number of layers, and kernel size. To do this, you plan to run multiple jobs in parallel to identify the parameters that optimize performance. You want to minimize custom code development and infrastructure management.
What should you do?

  1. Train an AutoML image classification model.
  2. Create a custom training job that uses the Vertex AI Vizier SDK for parameter optimization.
  3. Create a Vertex AI hyperparameter tuning job.
  4. Create a Vertex AI pipeline that runs different model training jobs in parallel.

Answer(s): C



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