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Professional-Machine-Learning-Engineer Dumps With Exact Questions and Answers

Exact2pass Provides 100% Valid Google Professional Machine Learning Engineer Professional-Machine-Learning-Engineer Exam dumps Questions and answers which can helps you to Pass Your Certification Exam in First Attempt.

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Professional-Machine-Learning-Engineer Questions and Answers

Question # 1

You are an ML engineer at a manufacturing company You are creating a classification model for a predictive maintenance use case You need to predict whether a crucial machine will fail in the next three days so that the repair crew has enough time to fix the machine before it breaks. Regular maintenance of the machine is relatively inexpensive, but a failure would be very costly You have trained several binary classifiers to predict whether the machine will fail. where a prediction of 1 means that the ML model predicts a failure.

You are now evaluating each model on an evaluation dataset. You want to choose a model that prioritizes detection while ensuring that more than 50% of the maintenance jobs triggered by your model address an imminent machine failure. Which model should you choose?

A.

The model with the highest area under the receiver operating characteristic curve (AUC ROC) and precision greater than 0 5

B.

The model with the lowest root mean squared error (RMSE) and recall greater than 0.5.

C.

The model with the highest recall where precision is greater than 0.5.

D.

The model with the highest precision where recall is greater than 0.5.

Question # 2

Your organization wants to make its internal shuttle service route more efficient. The shuttles currently stop at all pick-up points across the city every 30 minutes between 7 am and 10 am. The development team has already built an application on Google Kubernetes Engine that requires users to confirm their presence and shuttle station one day in advance. What approach should you take?

A.

1. Build a tree-based regression model that predicts how many passengers will be picked up at each shuttle station.

2. Dispatch an appropriately sized shuttle and provide the map with the required stops based on the prediction.

B.

1. Build a tree-based classification model that predicts whether the shuttle should pick up passengers at each shuttle station.

2. Dispatch an available shuttle and provide the map with the required stops based on the prediction

C.

1. Define the optimal route as the shortest route that passes by all shuttle stations with confirmed attendance at the given time under capacity constraints.

2 Dispatch an appropriately sized shuttle and indicate the required stops on the map

D.

1. Build a reinforcement learning model with tree-based classification models that predict the presence of passengers at shuttle stops as agents and a reward function around a distance-based metric

2. Dispatch an appropriately sized shuttle and provide the map with the required stops based on the simulated outcome.

Question # 3

You work for a semiconductor manufacturing company. You need to create a real-time application that automates the quality control process High-definition images of each semiconductor are taken at the end of the assembly line in real time. The photos are uploaded to a Cloud Storage bucket along with tabular data that includes each semiconductor's batch number serial number dimensions, and weight You need to configure model training and serving while maximizing model accuracy. What should you do?

A.

Use Vertex Al Data Labeling Service to label the images and train an AutoML image classification model.

Deploy the model and configure Pub/Sub to publish a message when an image is categorized into the failing class.

B.

Use Vertex Al Data Labeling Service to label the images and train an AutoML image classification model. Schedule a daily batch prediction job that publishes a Pub/Sub message when the job completes.

C.

Convert the images into an embedding representation Import this data into BigQuery, and train a BigQuery. ML K-means clustenng model with two clusters Deploy the model and configure Pub/Sub to publish a message when a semiconductor's data is categorized into the failing cluster.

D.

Import the tabular data into BigQuery use Vertex Al Data Labeling Service to label the data and train an AutoML tabular classification model Deploy the model and configure Pub/Sub to publish a message when a semiconductor's data is categorized into the failing class.

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