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The DP-100 Exam covers a wide range of topics, including data exploration, data preparation, modeling, and deployment. You will need to understand key Azure technologies such as Azure Machine Learning, Azure Databricks, and Azure Cosmos DB, as well as programming languages like Python and R. You will also need to be familiar with data storage and processing, data visualization, and machine learning techniques.
Certification DP-100 Exam & Brain DP-100 ExamThe most attractive thing about a learning platform is not the size of his question bank, nor the amount of learning resources, but more importantly, it is necessary to have a good control over the annual propositional trend. The DP-100 study materials through research and analysis of the annual questions, found that there are a lot of hidden rules are worth exploring, plus we have a powerful team of experts, so the rule can be summed up and use. The DP-100 Study Materials can be based on the analysis of the annual questions, it is concluded that a series of important conclusions related to the qualification examination, combining with the relevant knowledge of recent years, then predict the direction which can determine this year's exam. DP-100 study materials will improve the ability to accurately forecast the topic and proposition trend this year. Microsoft Designing and Implementing a Data Science Solution on Azure Sample Questions (Q262-Q267):NEW QUESTION # 262
You are using The Azure Machine Learning designer to transform a dataset containing the census data of all nations.
You must use the Split Data component to separate the dataset into two datasets. The first dataset must contain the census data of the United States. The second dataset must include the census data of the remaining nations.
You need to configure the component to create the datasets.
Which configuration values should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point. Answer:
Explanation:
Explanation:
NEW QUESTION # 263
You need to identify the methods for dividing the data according, to the testing requirements.
Which properties should you select? To answer, select the appropriate option-, m the answer area. NOTE:
Each correct selection is worth one point. Answer:
Explanation:
NEW QUESTION # 264
You have a Python script that executes a pipeline. The script includes the following code:
from azureml.core import Experiment
pipeline_run = Experiment(ws, 'pipeline_test').submit(pipeline)
You want to test the pipeline before deploying the script.
You need to display the pipeline run details written to the STDOUT output when the pipeline completes.
Which code segment should you add to the test script?
A. pipeline_param = PipelineParameter(name="stdout",
default_value="console")
B. pipeline_run.wait_for_completion(show_output=True)
C. pipeline_run.get.metrics()
D. pipeline_run.get_status()
Answer: B
Explanation:
wait_for_completion: Wait for the completion of this run. Returns the status object after the wait.
Syntax: wait_for_completion(show_output=False, wait_post_processing=False, raise_on_error=True) Parameter: show_output Indicates whether to show the run output on sys.stdout.
NEW QUESTION # 265
You create an Azure Machine Learning dataset containing automobile price dat a. The dataset includes 10.000 rows and 10 columns. You use the Azure Machine Learning designer to transform the dataset by using an Execute Python Script component and custom code.
The code must combine three columns to create a new column.
You need to configure the code function.
Which configurations should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point. Answer:
Explanation:
NEW QUESTION # 266
You create an Azure Machine Learning workspace. You train a classification model by using automated machine learning (automated ML) in Azure Machine Learning studio. The training data contains multiple classes that have significantly different numbers of samples.
You must use a metric type to avoid labeling negative samples as positive and an averaging method that will minimize the class imbalance.
You need to configure the metric type and the averaging method.
Which configurations should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point. Answer:
Explanation:
Explanation:
NEW QUESTION # 267
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