Free Google Professional-Machine-Learning-Engineer Exam Questions

Become Google Certified with updated Professional-Machine-Learning-Engineer exam questions and correct answers

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Total 289 Questions | Updated On: Jan 29, 2026

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Question 1

You are an ML engineer on an agricultural research team working on a crop disease detection tool to detect leaf rust spots in images of crops to determine the presence of a disease. These spots, which can vary in shape and size, are correlated to the severity of the disease. You want to develop a solution that predicts the presence and severity of the disease with high accuracy. What should you do?

A : eate an object detection model that can localize the rust spots.

B : velop an image segmentation ML model to locate the boundaries of the rust spots.

C : velop a template matching algorithm using traditional computer vision libraries.

D : velop an image classification ML model to predict the presence of the disease.

Answer: B

Question 2

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?

A : the Natural Language API to classify support requests.

B : AutoML Natural Language to build the support requests classifier.

C : an established text classification model on AI Platform to perform transfer learning

D : an established text classification model on AI Platform as-is to classify support requests

Answer: D

Question 3

You are training an ML model on a large dataset. You are using a TPU to accelerate the training process You notice that the training process is taking longer than expected. You discover that the TPU is not reaching its full capacity. What should you do?

A : Increase the learning rate

B : Increase the number of epochs

C : Decrease the learning rate

D : Increase the batch size

Answer: D

Question 4

Your organization manages an online message board. A few months ago, you discovered an increase in toxic language and bullying on the message board. You deployed an automated text classifier that flags certain comments as toxic or harmful. Now some users are reporting that benign comments referencing their religion are being misclassified as abusive. Upon further inspection, you find that your classifier's false positive rate is higher for comments that reference certain underrepresented religious groups. Your team has a limited budget and is already overextended. What should you do?

A : Add synthetic training data where those phrases are used in non-toxic ways.

B : move the model and replace it with human moderation.

C : place your model with a different text classifier.

D : ise the threshold for comments to be considered toxic or harmful.

Answer: A

Question 5

You work for a retail company. You have a managed tabular dataset in Vertex Al that contains sales data from three different stores. The dataset includes several features such as store name and sale timestamp. You want to use the data to train a model that makes sales predictions for a new store that will open soon You need to split the data between the training, validation, and test sets What approach should you use to split the data?

A : Use Vertex Al manual split, using the store name feature to assign one store for each set.

B : Use Vertex Al default data split.

C : Use Vertex Al chronological split and specify the sales timestamp feature as the time vanable.

D : Use Vertex Al random split assigning 70% of the rows to the training set, 10% to the validation set, and 20% to the test set.

Answer: A

Page: 1 / 58

Total 289 Questions | Updated On: Jan 29, 2026

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