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Microsoft DP-100 Designing and Implementing a Data Science Solution on Azure Exam Practice Test

Demo: 73 questions
Total 460 questions

Designing and Implementing a Data Science Solution on Azure Questions and Answers

Question 1

You use the Two-Class Neural Network module in Azure Machine Learning Studio to build a binary

classification model. You use the Tune Model Hyperparameters module to tune accuracy for the model.

You need to select the hyperparameters that should be tuned using the Tune Model Hyperparameters module.

Which two hyperparameters should you use? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

Options:

A.

Number of hidden nodes

B.

Learning Rate

C.

The type of the normalizer

D.

Number of learning iterations

E.

Hidden layer specification

Question 2

You are performing feature scaling by using the scikit-learn Python library for x.1 x2, and x3 features.

Original and scaled data is shown in the following image.

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.

Options:

Question 3

You create machine learning models by using Azure Machine Learning.

You plan to train and score models by using a variety of compute contexts. You also plan to create a new compute resource in Azure Machine Learning studio.

You need to select the appropriate compute types.

Which compute types should you select? To answer, drag the appropriate compute types to the correct requirements. Each compute type 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.

Options:

Question 4

: 218 HOTSPOT

You collect data from a nearby weather station. You have a pandas dataframe named weather_df that includes the following data:

The data is collected every 12 hours: noon and midnight.

You plan to use automated machine learning to create a time-series model that predicts temperature over the next seven days. For the initial round of training, you want to train a maximum of 50 different models.

You must use the Azure Machine Learning SDK to run an automated machine learning experiment to train these models.

You need to configure the automated machine learning run.

How should you complete the AutoMLConfig definition? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 5

You use the Azure Machine Learning Python SDK to create a batch inference pipeline.

You must publish the batch inference pipeline so that business groups in your organization can use the pipeline. Each business group must be able to specify a different location for the data that the pipeline submits to the model for scoring.

You need to publish the pipeline.

What should you do?

Options:

A.

Create multiple endpoints for the published pipeline service and have each business group submit jobs to its own endpoint.

B.

Define a PipelineParameter object for the pipeline and use it to specify the business group-specific input dataset for each pipeline run.

C.

Define a OutputFileDatasetConfig object for the pipeline and use the object to specify the business group-specific input dataset for each pipeline run.

D.

Have each business group run the pipeline on local compute and use a local file for the input data.

Question 6

You create an Azure Machine Learning workspace.

You plan to write an Azure Machine Learning SDK for Python v2 script that logs an image for an experiment. The logged image must be available from the images tab in Azure Machine Learning Studio.

You need to complete the script.

Which code segments should you use? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 7

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 use Azure Machine Learning designer to load the following datasets into an experiment:

You need to create a dataset that has the same columns and header row as the input datasets and contains all rows from both input datasets.

Solution: Use the Execute Python Script module.

Does the solution meet the goal?

Options:

A.

Yes

B.

No

Question 8

ESTION NO: 60

You are building recurrent neural network to perform a binary classification.

The training loss, validation loss, training accuracy, and validation accuracy of each training epoch has been provided. You need to identify whether the classification model is over fitted.

Which of the following is correct?

Options:

A.

The training loss increases while the validation loss decreases when training the model.

B.

The training loss decreases while the validation loss increases when training the model.

C.

The training loss stays constant and the validation loss decreases when training the model.

D.

The training loss .stays constant and the validation loss stays on a constant value and close to the training loss value when training the model.

Question 9

You are building a recurrent neural network to perform a binary classification. You review the training loss, validation loss, training accuracy, and validation accuracy for each training epoch.

You need to analyze model performance.

Which observation indicates that the classification model is over fitted?

Options:

A.

The training loss .stays constant and the validation loss stays on a constant value and close to the training loss value when training the model.

B.

The training loss increases while the validation loss decreases when training the model.

C.

The training loss decreases while the validation loss increases when training the model.

D.

The training loss stays constant and the validation loss decreases when training the model.

Question 10

You create a datastore named training_data that references a blob container in an Azure Storage account. The blob container contains a folder named csv_files in which multiple comma-separated values (CSV) files are stored.

You have a script named train.py in a local folder named ./script that you plan to run as an experiment using an estimator. The script includes the following code to read data from the csv_files folder:

You have the following script.

You need to configure the estimator for the experiment so that the script can read the data from a data reference named data_ref that references the csv_files folder in the training_data datastore.

Which code should you use to configure the estimator?

Options:

A.

Option A

B.

Option B

C.

Option C

D.

Option D

E.

Option E

Question 11

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?

Options:

A.

pipeline_run.get.metrics()

B.

pipeline_run.wait_for_completion(show_output=True)

C.

pipeline_param = PipelineParameter(name="stdout",default_value="console")

D.

pipeline_run.get_status()

Question 12

You use the following code to run a script as an experiment in Azure Machine Learning:

You must identify the output files that are generated by the experiment run.

You need to add code to retrieve the output file names.

Which code segment should you add to the script?

Options:

A.

files = run.get_properties()

B.

files= run.get_file_names()

C.

files = run.get_details_with_logs()

D.

files = run.get_metrics()

E.

files = run.get_details()

Question 13

You are using C-Support Vector classification to do a multi-class classification with an unbalanced training dataset. The C-Support Vector classification using Python code shown below:

You need to evaluate the C-Support Vector classification code.

Which evaluation statement should you use? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 14

You have an existing GitHub repository containing Azure Machine Learning project files.

You need to clone the repository to your Azure Machine Learning shared workspace file system.

Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.

Options:

Question 15

You are producing a multiple linear regression model in Azure Machine Learning Studio.

Several independent variables are highly correlated.

You need to select appropriate methods for conducting effective feature engineering on all the data.

Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Options:

Question 16

You have several machine learning models registered in an Azure Machine Learning workspace.

You must use the Fairlearn dashboard to assess fairness in a selected model.

Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Options:

Question 17

You have a dataset that includes confidential data. You use the dataset to train a model.

You must use a differential privacy parameter to keep the data of individuals safe and private.

You need to reduce the effect of user data on aggregated results.

What should you do?

Options:

A.

Decrease the value of the epsilon parameter to reduce the amount of noise added to the data

B.

Increase the value of the epsilon parameter to decrease privacy and increase accuracy

C.

Decrease the value of the epsilon parameter to increase privacy and reduce accuracy

D.

Set the value of the epsilon parameter to 1 to ensure maximum privacy

Question 18

You monitor an Azure Machine Learning classification training experiment named train-classification on Azure Notebooks.

You must store a table named table as an artifact in Azure Machine Learning Studio during model training.

You need to collect and list the metrics by using MLfow.

how should you complete the code segment? To answer, select the appropriate option in the answer area.

NOTE: Each correct selection is worth on* point.

Options:

Question 19

You use an Azure Machine Learning workspace.

You create the following Python code:

For each of the following statements, select Yes if the statement is true. Otherwise, select No.

NOTE: Each correct selection is worth one point.

Options:

Question 20

You design a project for interactive data mangling with Apache Spark in an Azure Machine Learning workspace. The data pipeline must provide the following solution:

• Ingest and process a vast amount of data from various sources and linked services, such as databases and APIs

• Visualize the results in Microsoft Power Bl.

• Include a possibility to quickly identify and address issues by observing only a small amount of data using the fewest resources.

You need to select a computation option for project activities.

Options:

Question 21

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 create a model to forecast weather conditions based on historical data.

You need to create a pipeline that runs a processing script to load data from a datastore and pass the processed data to a machine learning model training script.

Solution: Run the following code:

Does the solution meet the goal?

Options:

A.

Yes

B.

No

Question 22

You use Azure Machine Learning studio to analyze an mltable data asset containing a decimal column named column1. You need to verify that the column1 values are normally distributed.

Which statistic should you use?

Options:

A.

Max

B.

Type

C.

Profile

D.

Mean

Question 23

You are creating a new experiment in Azure Machine Learning Studio. You have a small dataset that has missing values in many columns. The data does not require the application of predictors for each column. You plan to use the Clean Missing Data module to handle the missing data.

You need to select a data cleaning method.

Which method should you use?

Options:

A.

Synthetic Minority Oversampling Technique (SMOTE)

B.

Replace using MICE

C.

Replace using; Probabilistic PCA

D.

Normalization

Question 24

You train a machine learning model.

You must deploy the model as a real-time inference service for testing. The service requires low CPU utilization and less than 48 MB of RAM. The compute target for the deployed service must initialize automatically while minimizing cost and administrative overhead.

Which compute target should you use?

Options:

A.

Azure Kubernetes Service (AKS) inference cluster

B.

Azure Machine Learning compute cluster

C.

Azure Container Instance (ACI)

D.

attached Azure Databricks cluster

Question 25

You are creating a machine learning model in Python. The provided dataset contains several numerical columns and one text column. The text column represents a product's category. The product category will always be one of the following:

Bikes

Cars

Vans

Boats

You are building a regression model using the scikit-learn Python package.

You need to transform the text data to be compatible with the scikit-learn Python package.

How should you complete the code segment? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 26

You are creating a new Azure Machine Learning pipeline using the designer.

The pipeline must train a model using data in a comma-separated values (CSV) file that is published on a

website. You have not created a dataset for this file.

You need to ingest the data from the CSV file into the designer pipeline using the minimal administrative effort.

Which module should you add to the pipeline in Designer?

Options:

A.

Convert to CSV

B.

Enter Data ManuallyD

C.

Import Data

D.

Dataset

Question 27

You must store data in Azure Blob Storage to support Azure Machine Learning.

You need to transfer the data into Azure Blob Storage.

What are three possible ways to achieve the goal? Each correct answer presents a complete solution.

NOTE: Each correct selection is worth one point.

Options:

A.

Bulk Insert SQL Query

B.

AzCopy

C.

Python script

D.

Azure Storage Explorer

E.

Bulk Copy Program (BCP)

Question 28

You manage an Azure Machine Learning workspace. The development environment tor managing the workspace is configured to use Python SDK v2 in Azure Machine Learning Notebooks A Synapse Spark Compute is currently attached and uses system-assigned identity You need to use Python code to update the Synapse Spark Compute 10 use a user-assigned identity.

Solution: Configure the IdentityConfiguration class with the appropriate identity type.

Does the solution meet the goal?

Options:

A.

Yes

B.

No

Question 29

You use Azure Machine Learning Designer lo load the following datasets into an experiment:

Dataset1:

Dataset2:

You need to create a dataset that has the same columns and header row as the input datasets and contains all rows from both input datasets.

Solution: Use the Add Rows component.

Does the solution meet the goal?

Options:

A.

Yes

B.

No

Question 30

You have a dataset created for multiclass classification tasks that contains a normalized numerical feature set with 10,000 data points and 150 features.

You use 75 percent of the data points for training and 25 percent for testing. You are using the scikit-learn machine learning library in Python. You use X to denote the feature set and Y to denote class labels.

You create the following Python data frames:

You need to apply the Principal Component Analysis (PCA) method to reduce the dimensionality of the feature set to 10 features in both training and testing sets.

How should you complete the code segment? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 31

You have an Azure Machine Learning workspace.

You plan to use the terminal to configure a compute instance to run a notebook.

You need to add a new R kernel to the compute instance.

In which order should you perform the actions? To answer, move all actions from the list of actions to the answer area and arrange them in the correct order.

Options:

Question 32

ESTION NO: 159

You create a machine learning model by using the Azure Machine Learning designer. You publish the model as a real-time service on an Azure Kubernetes Service (AKS) inference compute cluster. You make no changes to the deployed endpoint configuration.

You need to provide application developers with the information they need to consume the endpoint.

Which two values should you provide to application developers? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

Options:

A.

The name of the AKS cluster where the endpoint is hosted.

B.

The name of the inference pipeline for the endpoint.

C.

The URL of the endpoint.

D.

The run ID of the inference pipeline experiment for the endpoint.

E.

The key for the endpoint.

Question 33

You manage an Azure Machine Learning workspace named workspace 1 with a compute instance named computet.

You must remove a kernel named kernel 1 from computet1. You connect to compute 1 by using noa terminal window from workspace 1.

You need to enter a command in the terminal window to remove kernel 1.

Which command should you use? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection it worth one point.

Options:

Question 34

You use an Azure Machine Learning workspace.

You must monitor cost at the endpoint and deployment level.

You have a trained model that must be deployed as an online endpoint. Users must authenticate by using Microsoft Entra ID.

What should you do?

Options:

A.

Deploy the model lo Azure Kubernetes Service (AKS). During deployment, set the token_auth_mode parameter of the target configuration object to true.

B.

Deploy the model to a managed online endpoint. During deployment, set the token_auth_mode parameter of the target configuration object to true.

C.

Deploy the model to Azure Kubernetes Service (AKS). During deployment, set the auth.mode parameter to configure the authentication type.

D.

Deploy the model to a managed online endpoint. During deployment, set the auth_mode parameter to configure the authentication type.

Question 35

You train a machine learning model by using Aunt Machine Learning.

You use the following training script m Python to log an accuracy value.

You must use a Python script to define a sweep job.

You need to provide the primary metric and goal you want hyper parameter tuning to optimize.

How should you complete the Python script? To answer select the appropriate options in the answer area

NOTE: Each correct selection is worth one point.

Options:

Question 36

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 train and register an Azure Machine Learning model.

You plan to deploy the model to an online end point.

You need to ensure that applications will be able to use the authentication method with a non-expiring artifact to access the model.

Solution:

Create a Kubernetes online endpoint and set the value of its auth-mode parameter to amyl Token. Deploy the model to the online endpoint.

Does the solution meet the goal?

Options:

A.

Yes

B.

No

Question 37

You have an Azure Machine Learning workspace that contains a training cluster and an inference cluster.

You plan to create a classification model by using the Azure Machine Learning designer.

You need to ensure that client applications can submit data as HTTP requests and receive predictions as responses.

Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Options:

Question 38

You are running a training experiment on remote compute in Azure Machine Learning.

The experiment is configured to use a conda environment that includes the mlflow and azureml-contrib-run packages.

You must use MLflow as the logging package for tracking metrics generated in the experiment.

You need to complete the script for the experiment.

How should you complete the code? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 39

You create an Azure Data Lake Storage Gen2 stowage account named storage1 containing a file system named fsi and a folder named folder1.

The contents of folder1 must be accessible from jobs on compute targets in the Azure Machine Learning workspace.

You need to construct a URl to reference folder1.

How should you construct the URI? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 40

You manage an Azure Machine Learning workspace.

You experiment with an MLflow model that trains interactively by using a notebook in the workspace. You need to log dictionary type artifacts of the experiments in Azure Machine Learning by using MLflow. Which syntax should you use?

Options:

A.

mlflow.log_artifact(my_dict)

B.

mlflow.log_metric("my_metric", my_dict)

C.

mlflow.log_artifacts(my_dict>

D.

mlflow.log metrics(my diet)

Question 41

You have an Azure Machine Learning workspace that contains a CPU-based compute cluster and an Azure Kubernetes Services (AKS) inference cluster. You create a tabular dataset containing data that you plan to use to create a classification model.

You need to use the Azure Machine Learning designer to create a web service through which client applications can consume the classification model by submitting new data and getting an immediate prediction as a response.

Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Options:

Question 42

You manage an Azure Machine Learning workspace.

You need to define an environment from a Docker image by using the Azure Machine Learning Python SDK v2.

Which parameter should you use?

Options:

A.

conda_file

B.

image

C.

build

D.

properties

Question 43

You are building a binary classification model by using a supplied training set.

The training set is imbalanced between two classes.

You need to resolve the data imbalance.

What are three possible ways to achieve this goal? Each correct answer presents a complete solution NOTE: Each correct selection is worth one point.

Options:

A.

Penalize the classification

B.

Resample the data set using under sampling or oversampling

C.

Generate synthetic samples in the minority class.

D.

Use accuracy as the evaluation metric of the model.

E.

Normalize the training feature set.

Question 44

You have an Azure Machine Learning workspace named Workspace 1 Workspace! has a registered Mlflow model named model 1 with PyFunc flavor

You plan to deploy model1 to an online endpoint named endpointl without egress connectivity by using Azure Machine learning Python SDK vl

You have the following code:

You need to add a parameter to the ManagedOnllneDeployment object to ensure the model deploys successfully

Solution: Add the with_package parameter.

Does the solution meet the goal?

Options:

A.

Yes

B.

No

Question 45

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 creating a new experiment in Azure Machine Learning Studio.

One class has a much smaller number of observations than the other classes in the training set.

You need to select an appropriate data sampling strategy to compensate for the class imbalance.

Solution: You use the Scale and Reduce sampling mode.

Does the solution meet the goal?

Options:

A.

Yes

B.

No

Question 46

You plan to preprocess text from CSV files. You load the Azure Machine Learning Studio default stop words list.

You need to configure the Preprocess Text module to meet the following requirements:

Ensure that multiple related words from a single canonical form.

Remove pipe characters from text.

Remove words to optimize information retrieval.

Which three options should you select? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 47

You need to produce a visualization for the diagnostic test evaluation according to the data visualization requirements.

Which three modules should you recommend be used in sequence? To answer, move the appropriate modules from the list of modules to the answer area and arrange them in the correct order.

Options:

Question 48

You need to configure the Edit Metadata module so that the structure of the datasets match.

Which configuration options should you select? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 49

N NO: 17 HOTSPOT

You need to configure the Permutation Feature Importance module for the model training requirements.

What should you do? To answer, select the appropriate options in the dialog box in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 50

ION NO: 19 DRAG DROP

You need to correct the model fit issue.

Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Options:

Question 51

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.

Options:

Question 52

You need to implement early stopping criteria as suited in the model training requirements.

Which three code segments should you use to develop the solution? To answer, move the appropriate code segments from the list of code segments to the answer area and arrange them in the correct order.

NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.

Options:

Question 53

You need to select a feature extraction method.

Which method should you use?

Options:

A.

Spearman correlation

B.

Mutual information

C.

Mann-Whitney test

D.

Pearson’s correlation

Question 54

You need to replace the missing data in the AccessibilityToHighway columns.

How should you configure the Clean Missing Data module? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 55

You need to select a feature extraction method.

Which method should you use?

Options:

A.

Mutual information

B.

Mood’s median test

C.

Kendall correlation

D.

Permutation Feature Importance

Question 56

You need to visually identify whether outliers exist in the Age column and quantify the outliers before the outliers are removed.

Which three Azure Machine Learning Studio modules should you use in sequence? To answer, move the appropriate modules from the list of modules to the answer area and arrange them in the correct order.

Options:

Question 57

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.

Options:

Question 58

You need to configure the Feature Based Feature Selection module based on the experiment requirements and datasets.

How should you configure the module properties? To answer, select the appropriate options in the dialog box in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 59

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 options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 60

You need to define an evaluation strategy for the crowd sentiment models.

Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Options:

Question 61

You need to define a process for penalty event detection.

Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Options:

Question 62

You need to implement a scaling strategy for the local penalty detection data.

Which normalization type should you use?

Options:

A.

Streaming

B.

Weight

C.

Batch

D.

Cosine

Question 63

You need to implement a feature engineering strategy for the crowd sentiment local models.

What should you do?

Options:

A.

Apply an analysis of variance (ANOVA).

B.

Apply a Pearson correlation coefficient.

C.

Apply a Spearman correlation coefficient.

D.

Apply a linear discriminant analysis.

Question 64

You need to define a modeling strategy for ad response.

Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Options:

Question 65

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

Which environment should you use?

Options:

A.

Azure HDInsight with Spark MLlib

B.

Azure Cognitive Services

C.

Azure Machine Learning Studio

D.

Microsoft Machine Learning Server

Question 66

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

Which technique should you use?

Options:

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.

Question 67

You need to define a process for penalty event detection.

Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Options:

Question 68

You need to build a feature extraction strategy for the local models.

How should you complete the code segment? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 69

You need to define an evaluation strategy for the crowd sentiment models.

Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Options:

Question 70

You need to implement a new cost factor scenario for the ad response models as illustrated in the

performance curve exhibit.

Which technique should you use?

Options:

A.

Set the threshold to 0.5 and retrain if weighted Kappa deviates +/- 5% from 0.45.

B.

Set the threshold to 0.05 and retrain if weighted Kappa deviates +/- 5% from 0.5.

C.

Set the threshold to 0.2 and retrain if weighted Kappa deviates +/- 5% from 0.6.

D.

Set the threshold to 0.75 and retrain if weighted Kappa deviates +/- 5% from 0.15.

Question 71

You need to use the Python language to build a sampling strategy for the global penalty detection models.

How should you complete the code segment? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 72

You need to resolve the local machine learning pipeline performance issue. What should you do?

Options:

A.

Increase Graphic Processing Units (GPUs).

B.

Increase the learning rate.

C.

Increase the training iterations,

D.

Increase Central Processing Units (CPUs).

Question 73

You need to modify the inputs for the global penalty event model to address the bias and variance issue.

Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Options:

Demo: 73 questions
Total 460 questions