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The Google Professional-Data-Engineer exam consists of multiple-choice and scenario-based questions that test the candidates' understanding of GCP data engineering services and best practices for data engineering. Candidates have two hours and thirty minutes to complete the exam. Professional-Data-Engineer exam is available in English, Japanese, Spanish, and Portuguese.
Google Professional-Data-Engineer certification exam is designed to validate the skills and knowledge of individuals working in the field of data engineering. Google Certified Professional Data Engineer Exam certification is intended for those professionals who have expertise in designing, building, and maintaining data processing systems using Google Cloud Platform services. Professional-Data-Engineer exam evaluates the candidates' ability to design, implement, and manage data processing systems, as well as their understanding of data analysis and machine learning concepts.
NEW QUESTION # 258
An organization maintains a Google BigQuery dataset that contains tables with user-level data. They want
to expose aggregates of this data to other Google Cloud projects, while still controlling access to the user-
level data. Additionally, they need to minimize their overall storage cost and ensure the analysis cost for
other projects is assigned to those projects. What should they do?
Answer: B
Explanation:
Explanation/Reference:
Reference: https://cloud.google.com/bigquery/docs/access-control
NEW QUESTION # 259
Which role must be assigned to a service account used by the virtual machines in a Dataproc cluster so they can execute jobs?
Answer: B
Explanation:
Service accounts used with Cloud Dataproc must have Dataproc/Dataproc Worker role (or have all the permissions granted by Dataproc Worker role).
NEW QUESTION # 260
Which of the following are examples of hyperparameters? (Select 2 answers.)
Answer: C,D
Explanation:
If model parameters are variables that get adjusted by training with existing data, your hyperparameters are the variables about the training process itself. For example, part of setting up a deep neural network is deciding how many "hidden" layers of nodes to use between the input layer and the output layer, as well as how many nodes each layer should use. These variables are not directly related to the training data at all.
They are configuration variables. Another difference is that parameters change during a training job, while the hyperparameters are usually constant during a job.
Weights and biases are variables that get adjusted during the training process, so they are not hyperparameters.
Reference: https://cloud.google.com/ml-engine/docs/hyperparameter-tuning-overview
NEW QUESTION # 261
If you want to create a machine learning model that predicts the price of a particular stock based on its recent price history, what type of estimator should you use?
Answer: A
Explanation:
Regression is the supervised learning task for modeling and predicting continuous, numeric variables.
Examples include predicting real-estate prices, stock price movements, or student test scores.
Classification is the supervised learning task for modeling and predicting categorical variables. Examples include predicting employee churn, email spam, financial fraud, or student letter grades. Clustering is an unsupervised learning task for finding natural groupings of observations (i.e. clusters) based on the inherent structure within your dataset. Examples include customer segmentation, grouping similar items in e-commerce, and social network analysis.
Reference: https://elitedatascience.com/machine-learning-algorithms
NEW QUESTION # 262
Your company has recently grown rapidly and now ingesting data at a significantly higher rate than it was
previously. You manage the daily batch MapReduce analytics jobs in Apache Hadoop. However, the
recent increase in data has meant the batch jobs are falling behind. You were asked to recommend ways
the development team could increase the responsiveness of the analytics without increasing costs. What
should you recommend they do?
Answer: C
NEW QUESTION # 263
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