Free Microsoft DP-100 Exam Questions

Become Microsoft Certified with updated DP-100 exam questions and correct answers

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Total 525 Questions | Updated On: Nov 14, 2024
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Question 1

You create a pipeline in designer to train a model that predicts automobile prices.
Because of non-linear relationships in the data, the pipeline calculates the natural log (Ln) of the prices in the
training data, trains a model to predict this natural log of price value, and then calculates the exponential of the
scored label to get the predicted price.
The training pipeline is shown in the exhibit. (Click the Training pipeline tab.)
Training pipeline
59
You create a real-time inference pipeline from the training pipeline, as shown in the exhibit. (Click the
Real-time pipeline tab.)
Real-time pipeline
60
You need to modify the inference pipeline to ensure that the web service returns the exponential of the scored
label as the predicted automobile price and that client applications are not required to include a price value in
the input values.
Which three modifications must you make to the inference pipeline? Each correct answer presents part of the
solution.
NOTE: Each correct selection is worth one point.


Answer: A,C,E
Question 2

You have an Azure Machine Learning workspace. You are connecting an Azure Data Lake Storage Gen2 account to the workspace as a data store.
You need to authorize access from the workspace to the Azure Data Lake Storage Gen2 account.
What should you use?


Answer: A
Question 3

You need to select a feature extraction method.
Which method should you use?


Answer: A
Question 4

Note: This question is part of a series of questions that present the same scenario. Each question in the
series contains a unique solution that might meet the stated goals. Some question sets might have 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, these
questions will not appear in the review screen.
You plan to use a Python script to run an Azure Machine Learning experiment. The script creates a reference
to the experiment run context, loads data from a file, identifies the set of unique values for the 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 be reviewed later.
You must add code to the script to record the unique label values as run metrics at the point indicated 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?


Answer: A
Question 5

You need to consider the underlined segment to establish whether it is accurate.
To transform a categorical feature into a binary indicator, you should make use of the Clean Missing Data module.
Select `No adjustment required` if the underlined segment is accurate. If the underlined segment is inaccurate, select the accurate option.


Answer: B
Page:    1 / 105      
Total 525 Questions | Updated On: Nov 14, 2024
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