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: Apr 03, 2026

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Question 1

You are developing a model to identify traffic signs in images extracted from videos taken from the dashboard of a vehicle. You have a dataset of 100 000 images that were cropped to show one out of ten different traffic signs. The images have been labeled accordingly for model training and are stored in a Cloud Storage bucket You need to be able to tune the model during each training run. How should you train the model?

A : Train a model for object detection by using Vertex Al AutoML.

B : Train a model for image classification by using Vertex Al AutoML.

C : Develop the model training code for object detection and tram a model by using Vertex Al custom training.

D : Develop the model training code for image classification and train a model by using Vertex Al custom training

Answer: C

Question 2

You trained a text classification model. You have the following SignatureDefs:

You started a TensorFlow-serving component server and tried to send an HTTP request to get a prediction using: headers = {"content-type": "application/json"} json_response = requests.post('http: //localhost:8501/v1/models/text_model:predict', data=data, headers=headers)

What is the correct way to write the predict request?

A : ta = json.dumps({ג€signature_nameג€: ג€seving_defaultג€, ג€instancesג€ [['ab', 'bc', 'cd']]})

B : ta = json.dumps({ג€signature_nameג€: ג€serving_defaultג€, ג€instancesג€ [['a', 'b', 'c', 'd', 'e', 'f']]})

C : ta = json.dumps({ג€signature_nameג€: ג€serving_defaultג€, ג€instancesג€ [['a', 'b', 'c'], ['d', 'e', 'f']]})

D : ta = json.dumps({ג€signature_nameג€: ג€serving_defaultג€, ג€instancesג€ [['a', 'b'], ['c', 'd'], ['e', 'f']]})

Answer: C

Question 3

You work for a hotel and have a dataset that contains customers' written comments scanned from paper-based customer feedback forms which are stored as PDF files Every form has the same layout. You need to quickly predict an overall satisfaction score from the customer comments on each form. How should you accomplish this task'?

A : Use the Vision API to parse the text from each PDF file Use the Natural Language API analyzesentiment feature to infer overall satisfaction scores.

B : Use the Vision API to parse the text from each PDF file Use the Natural Language API analyzeEntitysentiment feature to infer overall satisfaction scores.

C : Uptrain a Document Al custom extractor to parse the text in the comments section of each PDF file. Use the Natural Language API analyze sentiment feature to infer overall satisfaction scores.

D : Uptrain a Document Al custom extractor to parse the text in the comments section of each PDF file. Use the Natural Language API analyzeEntitySentiment feature to infer overall satisfaction scores.

Answer: D

Question 4

You have deployed multiple versions of an image classification model on AI Platform. You want to monitor the performance of the model versions over time. How should you perform this comparison?

A : mpare the loss performance for each model on a held-out dataset.

B : mpare the loss performance for each model on the validation data.

C : mpare the receiver operating characteristic (ROC) curve for each model using the What-If Tool.

D : mpare the mean average precision across the models using the Continuous Evaluation feature.

Answer: B

Question 5

You are an ML engineer at an ecommerce company and have been tasked with building a model that predicts how much inventory the logistics team should order each month. Which approach should you take?

A : a clustering algorithm to group popular items together. Give the list to the logistics team so they can increase inventory of the popular items.

B : a regression model to predict how much additional inventory should be purchased each month. Give the results to the logistics team at the beginning of the month so they can increase inventory by the amount predicted by the model.

C : a time series forecasting model to predict each item's monthly sales. Give the results to the logistics team so they can base inventory on the amount predicted by the model.

D : a classification model to classify inventory levels as UNDER_STOCKED, OVER_STOCKED, and CORRECTLY_STOCKEGive the report to the logistics team each month so they can fine-tune inventory levels.

Answer: B

Page: 1 / 58

Total 289 Questions | Updated On: Apr 03, 2026

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