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Information about Microsoft DP-100 Exam
Vendor: Microsoft
Exam Code: DP-100
Exam Name: Designing and Implementing a Data Science Solution onAzure
Number of Questions: 251
Certification Name: Azure Data Scientist Associate
Exam Language: English
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Question No. 1
Note: This question is part of a series of questions that present the same scenario. Each question inthe series contains a unique solution that might meet the stated goals. Some question sets mighthave more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, thesequestions will not appear in the review screen.
You train and register a machine learning model.
You plan to deploy the model as a real-time web service. Applications must use key-basedauthentication to use the model.
You need to deploy the web service.
Solution:
Create an AksWebservice instance.
Set the value of the auth_enabled property to False.
Set the value of the token_auth_enabled property to True.
Deploy the model to the service.
Does the solution meet the goal?
A. YesB. No
Answer: B
Question No. 2
Note: This question is part of a series of questions that present the same scenario. Each question inthe series contains a unique solution that might meet the stated goals. Some question sets mighthave more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, thesequestions will not appear in the review screen.
You plan to use a Python script to run an Azure Machine Learning experiment. The script creates areference to the experiment run context, loads data from a file, identifies the set of unique values forthe label column, and completes the experiment run:
from azureml.core import Run
import pandas as pd
run = Run.get_context()
data = pd.read_csv('data.csv')
label_vals = data['label'].unique()
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# Add code to record metrics here
run.complete()
The experiment must record the unique labels in the data as metrics for the run that can bereviewed later.
You must add code to the script to record the unique label values as run metrics at the pointindicated by the comment.
Solution: Replace the comment with the following code:
run.upload_file('outputs/labels.csv', './data.csv')
Does the solution meet the goal?
A. YesB. No
Answer: B
Question No. 3
Note: This question is part of a series of questions that present the same scenario. Each question inthe series contains a unique solution that might meet the stated goals. Some question sets mighthave more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, thesequestions will not appear in the review screen.
You plan to use a Python script to run an Azure Machine Learning experiment. The script creates areference to the experiment run context, loads data from a file, identifies the set of unique values forthe label column, and completes the experiment run:
from azureml.core import Run
import pandas as pd
run = Run.get_context()
data = pd.read_csv('data.csv')
label_vals = data['label'].unique()
# Add code to record metrics here
run.complete()
The experiment must record the unique labels in the data as metrics for the run that can bereviewed later.
You must add code to the script to record the unique label values as run metrics at the pointindicated by the comment.
Solution: Replace the comment with the following code:
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run.log_table('Label Values', label_vals)
Does the solution meet the goal?
A. YesB. No
Answer: B
Question No. 4
Note: This question is part of a series of questions that present the same scenario. Each question inthe series contains a unique solution that might meet the stated goals. Some question sets mighthave more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, thesequestions will not appear in the review screen.
You plan to use a Python script to run an Azure Machine Learning experiment. The script creates areference to the experiment run context, loads data from a file, identifies the set of unique values forthe label column, and completes the experiment run:
from azureml.core import Run
import pandas as pd
run = Run.get_context()
data = pd.read_csv('data.csv')
label_vals = data['label'].unique()
# Add code to record metrics here
run.complete()
The experiment must record the unique labels in the data as metrics for the run that can bereviewed later.
You must add code to the script to record the unique label values as run metrics at the pointindicated by the comment.
Solution: Replace the comment with the following code:
for label_val in label_vals:
run.log('Label Values', label_val)
Does the solution meet the goal?
A. YesB. No
Answer: A
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Question No. 5
You plan to run a Python script as an Azure Machine Learning experiment.
The script must read files from a hierarchy of folders. The files will be passed to the script as adataset argument.
You must specify an appropriate mode for the dataset argument.
Which two modes can you use? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
A. to_pandas_dataframe ()B. as_download()C. as_upload()D. as mount ()
Answer: B
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