Free Google Professional-Machine-Learning-Engineer Exam Questions
Absolute Free Professional-Machine-Learning-Engineer Exam Practice for Comprehensive Preparation
-
Google Professional-Machine-Learning-Engineer Exam Questions
-
Provided By: Google
- Exam: Professional Machine Learning Engineer
- Certification: Google Cloud Certified
-
Total Questions: 312
-
Updated On: Sep 23, 2026
-
Rated: 4.9 |
-
Online Users: 624
-
Question 1
-
You built a deep learning-based image classification model by using on-premises data. You want to use Vertex Al to deploy the model to production Due to security concerns you cannot move your data to the cloud. You are aware that the input data distribution might change over time You need to detect model performance changes in production. What should you do?
Answer: C
-
-
Question 2
-
You are building a linear model with over 100 input features, all with values between -1 and 1. You suspect that many features are non-informative. You want to remove the non-informative features from your model while keeping the informative ones in their original form. Which technique should you use?
Answer: B
-
-
Question 3
-
You need to develop an image classification model by using a large dataset that contains labeled images in a Cloud Storage bucket. What should you do?
Answer: C
-
You need to develop an image classification model by using a large dataset that contains labeled images in a Cloud Storage bucket. What should you do?
-
Question 4
-
While running a model training pipeline on Vertex Al, you discover that the evaluation step is failing because of an out-of-memory error. You are currently using TensorFlow Model Analysis (TFMA) with a standard Evaluator TensorFlow Extended (TFX) pipeline component for the evaluation step. You want to stabilize the pipeline without downgrading the evaluation quality while minimizing infrastructure overhead. What should you do?
Answer: C
-
-
Question 5
-
You need to build an ML model for a social media application to predict whether a user’s submitted profile photo meets the requirements. The application will inform the user if the picture meets the requirements. How should you build a model to ensure that the application does not falsely accept a non-compliant picture?
Answer: A
-
You need to build an ML model for a social media application to predict whether a user’s submitted profile photo meets the requirements. The application will inform the user if the picture meets the requirements. How should you build a model to ensure that the application does not falsely accept a non-compliant picture?