Month End Sale Limited Time 65% Discount Offer - Ends in 0d 00h 00m 00s - Coupon code: get65

Page: 1 / 21

Machine Learning Engineer Google Professional Machine Learning Engineer

Google Professional Machine Learning Engineer

Last Update Apr 25, 2025
Total Questions : 285

To help you prepare for the Professional-Machine-Learning-Engineer Google exam, we are offering free Professional-Machine-Learning-Engineer Google exam questions. All you need to do is sign up, provide your details, and prepare with the free Professional-Machine-Learning-Engineer practice questions. Once you have done that, you will have access to the entire pool of Google Professional Machine Learning Engineer Professional-Machine-Learning-Engineer test questions which will help you better prepare for the exam. Additionally, you can also find a range of Google Professional Machine Learning Engineer resources online to help you better understand the topics covered on the exam, such as Google Professional Machine Learning Engineer Professional-Machine-Learning-Engineer video tutorials, blogs, study guides, and more. Additionally, you can also practice with realistic Google Professional-Machine-Learning-Engineer exam simulations and get feedback on your progress. Finally, you can also share your progress with friends and family and get encouragement and support from them.

Questions 2

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

Options:

A.  

Compare the loss performance for each model on a held-out dataset.

B.  

Compare the loss performance for each model on the validation data

C.  

Compare the receiver operating characteristic (ROC) curve for each model using the What-lf Tool

D.  

Compare the mean average precision across the models using the Continuous Evaluation feature

Discussion 0
Ayesha
They are study materials that are designed to help students prepare for exams and certification tests. They are basically a collection of questions and answers that are likely to appear on the test.
Ayden Oct 16, 2024
That sounds interesting. Why are they useful? Planning this week, hopefully help me. Can you give me PDF if you have ?
Esmae
I highly recommend Cramkey Dumps to anyone preparing for the certification exam.
Mollie Aug 15, 2024
Absolutely. They really make it easier to study and retain all the important information. I'm so glad I found Cramkey Dumps.
Conor
I recently used these dumps for my exam and I must say, I was impressed with their authentic material.
Yunus Sep 13, 2024
Exactly…….The information in the dumps is so authentic and up-to-date. Plus, the questions are very similar to what you'll see on the actual exam. I felt confident going into the exam because I had studied using Cramkey Dumps.
Alaia
These Dumps are amazing! I used them to study for my recent exam and I passed with flying colors. The information in the dumps is so valid and up-to-date. Thanks a lot!!!
Zofia Sep 9, 2024
That's great to hear! I've been struggling to find good study material for my exam. I will ty it for sure.
Nell
Are these dumps reliable?
Ernie Oct 10, 2024
Yes, very much so. Cramkey Dumps are created by experienced and certified professionals who have gone through the exams themselves. They understand the importance of providing accurate and relevant information to help you succeed.
Questions 3

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?

Options:

A.  

Create an object detection model that can localize the rust spots.

B.  

Develop an image segmentation ML model to locate the boundaries of the rust spots.

C.  

Develop a template matching algorithm using traditional computer vision libraries.

D.  

Develop an image classification ML model to predict the presence of the disease.

Discussion 0
Questions 4

You need to design an architecture that serves asynchronous predictions to determine whether a particular mission-critical machine part will fail. Your system collects data from multiple sensors from the machine. You want to build a model that will predict a failure in the next N minutes, given the average of each sensor’s data from the past 12 hours. How should you design the architecture?

Options:

A.  

1. HTTP requests are sent by the sensors to your ML model, which is deployed as a microservice and exposes a REST API for prediction

2. Your application queries a Vertex AI endpoint where you deployed your model.

3. Responses are received by the caller application as soon as the model produces the prediction.

B.  

1. Events are sent by the sensors to Pub/Sub, consumed in real time, and processed by a Dataflow stream processing pipeline.

2. The pipeline invokes the model for prediction and sends the predictions to another Pub/Sub topic.

3. Pub/Sub messages containing predictions are then consumed by a downstream system for monitoring.

C.  

1. Export your data to Cloud Storage using Dataflow.

2. Submit a Vertex AI batch prediction job that uses your trained model in Cloud Storage to perform scoring on the preprocessed data.

3. Export the batch prediction job outputs from Cloud Storage and import them into Cloud SQL.

D.  

1. Export the data to Cloud Storage using the BigQuery command-line tool

2. Submit a Vertex AI batch prediction job that uses your trained model in Cloud Storage to perform scoring on the preprocessed data.

3. Export the batch prediction job outputs from Cloud Storage and import them into BigQuery.

Discussion 0
Questions 5

You have a demand forecasting pipeline in production that uses Dataflow to preprocess raw data prior to model training and prediction. During preprocessing, you employ Z-score normalization on data stored in BigQuery and write it back to BigQuery. New training data is added every week. You want to make the process more efficient by minimizing computation time and manual intervention. What should you do?

Options:

A.  

Normalize the data using Google Kubernetes Engine

B.  

Translate the normalization algorithm into SQL for use with BigQuery

C.  

Use the normalizer_fn argument in TensorFlow's Feature Column API

D.  

Normalize the data with Apache Spark using the Dataproc connector for BigQuery

Discussion 0
Title
Questions
Posted

Professional-Machine-Learning-Engineer
PDF

$36.75  $104.99

Professional-Machine-Learning-Engineer Testing Engine

$43.75  $124.99

Professional-Machine-Learning-Engineer PDF + Testing Engine

$57.75  $164.99