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Last Attempt Professional-Machine-Learning-Engineer Questions

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Question 32

You have recently developed a custom model for image classification by using a neural network. You need to automatically identify the values for learning rate, number of layers, and kernel size. To do this, you plan to run multiple jobs in parallel to identify the parameters that optimize performance. You want to minimize custom code development and infrastructure management. What should you do?

Options:

A.

Create a Vertex Al pipeline that runs different model training jobs in parallel.

B.

Train an AutoML image classification model.

C.

Create a custom training job that uses the Vertex Al Vizier SDK for parameter optimization.

D.

Create a Vertex Al hyperparameter tuning job.

Question 33

You are an ML engineer at a regulated insurance company. You are asked to develop an insurance approval model that accepts or rejects insurance applications from potential customers. What factors should you consider before building the model?

Options:

A.

Redaction, reproducibility, and explainability

B.

Traceability, reproducibility, and explainability

C.

Federated learning, reproducibility, and explainability

D.

Differential privacy federated learning, and explainability

Question 34

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?

Options:

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 35

You work for a food product company. Your company's historical sales data is stored in BigQuery You need to use Vertex Al’s custom training service to train multiple TensorFlow models that read the data from BigQuery and predict future sales You plan to implement a data preprocessing algorithm that performs min-max scaling and bucketing on a large number of features before you start experimenting with the models. You want to minimize preprocessing time, cost and development effort How should you configure this workflow?

Options:

A.

Write the transformations into Spark that uses the spark-bigquery-connector and use Dataproc to preprocess the data.

B.

Write SQL queries to transform the data in-place in BigQuery.

C.

Add the transformations as a preprocessing layer in the TensorFlow models.

D.

Create a Dataflow pipeline that uses the BigQuerylO connector to ingest the data process it and write it back to BigQuery.

Page: 8 / 21
Exam Name: Google Professional Machine Learning Engineer
Last Update: Nov 22, 2024
Questions: 285
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