DP-100 V3

DRAG DROP

You configure a Deep Learning Virtual Machine for Windows.

You need to recommend tools and frameworks to perform the following:

✑ Build deep neural network (DNN) models

✑ Perform interactive data exploration and visualization

Which tools and frameworks should you recommend? To answer, drag the appropriate tools to the correct tasks. Each tool may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content. NOTE: Each correct selection is worth one point.

View Answer

Answer:

Explanation:

Box 1: Vowpal Wabbit

Use the Train Vowpal Wabbit Version 8 module in Azure Machine Learning Studio (classic), to create a machine learning model by using Vowpal Wabbit.

Box 2: PowerBI Desktop

Power BI Desktop is a powerful visual data exploration and interactive reporting tool

BI is a name given to a modern approach to business decision making in which users are empowered to find, explore, and share insights from data across the enterprise.

Reference:

https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/train-vowpal-wabbit-version-8-model

https://docs.microsoft.com/en-us/azure/architecture/data-guide/scenarios/interactive-data-exploration

You need to select an environment that will meet the business and data requirements.

Which environment should you use?
A . Azure HDInsight with Spark MLlib
B. Azure Cognitive Services
C. Azure Machine Learning Studio
D. Microsoft Machine Learning Server

View Answer

Answer: D

You need to implement a model development strategy to determine a user’s tendency to respond to an ad.

Which technique should you use?
A . Use a Relative Expression Split module to partition the data based on centroid distance.
B. Use a Relative Expression Split module to partition the data based on distance travelled to the event.
C. Use a Split Rows module to partition the data based on distance travelled to the event.
D. Use a Split Rows module to partition the data based on centroid distance.

View Answer

Answer: A

Explanation:

Split Data partitions the rows of a dataset into two distinct sets.

The Relative Expression Split option in the Split Data module of Azure Machine Learning Studio is helpful when you need to divide a dataset into training and testing datasets using a numerical expression.

Relative Expression Split: Use this option whenever you want to apply a condition to a number column. The number could be a date/time field, a column containing age or dollar amounts, or even a percentage. For example, you might want to divide your data set depending on the cost of the items, group people by age ranges, or separate data by a calendar date.

Scenario:

Local market segmentation models will be applied before determining a user’s propensity to respond to an advertisement.

The distribution of features across training and production data are not consistent

Reference: https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/split-data

You are analyzing a dataset containing historical data from a local taxi company. You arc developing a regression a regression model.

You must predict the fare of a taxi trip.

You need to select performance metrics to correctly evaluate the- regression model.

Which two metrics can you use? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.
A . an F1 score that is high
B. an R Squared value dose to 1
C. an R-Squared value close to 0
D. a Root Mean Square Error value that is high
E. a Root Mean Square Error value that is low
F. an F 1 score that is low.

View Answer

Answer: BE

Explanation:

Reference: https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/evaluate-model

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 are a data scientist using Azure Machine Learning Studio.

You need to normalize values to produce an output column into bins to predict a target column.

Solution: Apply an Equal Width with Custom Start and Stop binning mode.

Does the solution meet the goal?
A . Yes
B. No

View Answer

Answer: B

Explanation:

Use the Entropy MDL binning mode which has a target column.

Reference: https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/group-data-into-bins

HOTSPOT

You create a binary classification model to predict whether a person has a disease.

You need to detect possible classification errors.

Which error type should you choose for each description? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

View Answer

Answer:

Explanation:

Box 1: True Positive

A true positive is an outcome where the model correctly predicts the positive class

Box 2: True Negative

A true negative is an outcome where the model correctly predicts the negative class.

Box 3: False Positive

A false positive is an outcome where the model incorrectly predicts the positive class.

Box 4: False Negative

A false negative is an outcome where the model incorrectly predicts the negative class.

Note: Let’s make the following definitions:

"Wolf" is a positive class.

"No wolf" is a negative class.

We can summarize our "wolf-prediction" model using a 2×2 confusion matrix that depicts all four possible outcomes:

Reference: https://developers.google.com/machine-learning/crash-course/classification/true-false-positive-negative

You plan to deliver a hands-on workshop to several students. The workshop will focus on creating data

visualizations using Python. Each student will use a device that has internet access.

Student devices are not configured for Python development. Students do not have administrator access to install software on their devices. Azure subscriptions are not available for students. You need to ensure that students can run Python-based data visualization code.

Which Azure tool should you use?
A . Anaconda Data Science Platform
B. Azure BatchAl
C. Azure Notebooks
D. Azure Machine Learning Service

View Answer

Answer: C

Explanation:

Reference: https://notebooks.azure.com/

HOTSPOT

You are developing a machine learning, experiment by using Azure.

The following images show the input and output of a machine learning experiment:

Use the drop-down menus to select the answer choice that answers each question based on the information presented in the graphic. NOTE: Each correct selection is worth one point.

View Answer

Answer:

HOTSPOT

You need to set up the Permutation Feature Importance module according to the model training requirements.

Which properties should you select? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

View Answer

Answer:

Explanation:

Box 1: Accuracy

Scenario: You want to configure hyperparameters in the model learning process to speed the learning phase by using hyperparameters. In addition, this configuration should cancel the lowest performing runs at each evaluation interval, thereby directing effort and resources towards models that are more likely to be successful.

Box 2: R-Squared

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 are a data scientist using Azure Machine Learning Studio.

You need to normalize values to produce an output column into bins to predict a target column.

Solution: Apply a Quantiles binning mode with a PQuantile normalization.

Does the solution meet the goal?
A . Yes
B. No

View Answer

Answer: B

Explanation:

Use the Entropy MDL binning mode which has a target column.

Reference: https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/group-data-into-bins