Google Professional-Machine-Learning-Engineer Dumps - Google Professional Machine Learning Engineer PDF Sample Questions

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Exam Code:
Professional-Machine-Learning-Engineer
Exam Name:
Google Professional Machine Learning Engineer
270 Questions
Last Update Date : 21 May, 2024
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Realexamdumps Providing most updated Machine Learning Engineer Question Answers. Here are a few exams:


Sample Questions

Realexamdumps Providing most updated Machine Learning Engineer Question Answers. Here are a few sample questions:

Google Professional-Machine-Learning-Engineer Sample Question 1

You have trained a model on a dataset that required computationally expensive preprocessing operations. You need to execute the same preprocessing at prediction time. You deployed the model on Al Platform for high-throughput online prediction. Which architecture should you use?


Options:

A. • Validate the accuracy of the model that you trained on preprocessed data• Create a new model that uses the raw data and is available in real time• Deploy the new model onto Al Platform for online prediction
B. • Send incoming prediction requests to a Pub/Sub topic• Transform the incoming data using a Dataflow job• Submit a prediction request to Al Platform using the transformed data• Write the predictions to an outbound Pub/Sub queue
C. • Stream incoming prediction request data into Cloud Spanner• Create a view to abstract your preprocessing logic.• Query the view every second for new records• Submit a prediction request to Al Platform using the transformed data• Write the predictions to an outbound Pub/Sub queue.
D. • Send incoming prediction requests to a Pub/Sub topic• Set up a Cloud Function that is triggered when messages are published to the Pub/Sub topic.• Implement your preprocessing logic in the Cloud Function• Submit a prediction request to Al Platform using the transformed data• Write the predictions to an outbound Pub/Sub queue

Answer: E

Google Professional-Machine-Learning-Engineer Sample Question 2

You work for a toy manufacturer that has been experiencing a large increase in demand. You need to build an ML model to reduce the amount of time spent by quality control inspectors checking for product defects. Faster defect detection is a priority. The factory does not have reliable Wi-Fi. Your company wants to implement the new ML model as soon as possible. Which model should you use?


Options:

A. AutoML Vision model
B. AutoML Vision Edge mobile-versatile-1 model
C. AutoML Vision Edge mobile-low-latency-1 model
D. AutoML Vision Edge mobile-high-accuracy-1 model

Answer: B

Google Professional-Machine-Learning-Engineer Sample Question 3

You have trained a deep neural network model on Google Cloud. The model has low loss on the training data, but is performing worse on the validation data. You want the model to be resilient to overfitting. Which strategy should you use when retraining the model?


Options:

A. Apply a dropout parameter of 0 2, and decrease the learning rate by a factor of 10
B. Apply a 12 regularization parameter of 0.4, and decrease the learning rate by a factor of 10.
C. Run a hyperparameter tuning job on Al Platform to optimize for the L2 regularization and dropout parameters
D. Run a hyperparameter tuning job on Al Platform to optimize for the learning rate, and increase the number of neurons by a factor of 2.

Answer: B

Google Professional-Machine-Learning-Engineer Sample Question 4

You were asked to investigate failures of a production line component based on sensor readings. After receiving the dataset, you discover that less than 1% of the readings are positive examples representing failure incidents. You have tried to train several classification models, but none of them converge. How should you resolve the class imbalance problem?


Options:

A. Use the class distribution to generate 10% positive examples
B. Use a convolutional neural network with max pooling and softmax activation
C. Downsample the data with upweighting to create a sample with 10% positive examples
D. Remove negative examples until the numbers of positive and negative examples are equal

Answer: E


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