Microsoft DP-100 Exam Practice Test Instant Access

Question 1

You are using Azure Machine Learning to monitor a trained and deployed model. You implement Event Grid to respond to Azure Machine Learning events.

Model performance has degraded due to model input data changes.

You need to trigger a remediation ML pipeline based on an Azure Machine Learning event.

Which event should you use?

ARunStatusChanged

BDatasetDriftDetected

CModelDeployed

DRunCompleted

Answer : B

Question 2

You create a multi-class image classification deep learning model that uses the PyTorch deep learning

framework.

You must configure Azure Machine Learning Hyperdrive to optimize the hyperparameters for the classification model.

You need to define a primary metric to determine the hyperparameter values that result in the model with the best accuracy score.

Which three actions must you perform? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

ASet the primary_metric_goal of the estimator used to run the bird_classifier_train.py script to maximize.

BAdd code to the bird_classifier_train.py script to calculate the validation loss of the model and log it as a float value with the key loss.

CSet the primary_metric_goal of the estimator used to run the bird_classifier_train.py script to minimize.

DSet the primary_metric_name of the estimator used to run the bird_classifier_train.py script to accuracy.

ESet the primary_metric_name of the estimator used to run the bird_classifier_train.py script to loss.

FAdd code to the bird_classifier_train.py script to calculate the validation accuracy of the model and log it as a float value with the key accuracy.

Answer : A, D, F

AD:

primary_metric_name='accuracy',

primary_metric_goal=PrimaryMetricGoal.MAXIMIZE

Optimize the runs to maximize 'accuracy'. Make sure to log this value in your training script.

Note:

primary_metric_name: The name of the primary metric to optimize. The name of the primary metric needs to exactly match the name of the metric logged by the training script.

primary_metric_goal: It can be either PrimaryMetricGoal.MAXIMIZE or PrimaryMetricGoal.MINIMIZE and determines whether the primary metric will be maximized or minimized when evaluating the runs.

F: The training script calculates the val_accuracy and logs it as 'accuracy', which is used as the primary metric.

Question 3

You are authoring a notebook in Azure Machine Learning studio.

You must install packages from the notebook into the currently running kernel. The installation must be limited to the currently running kernel only.

You need to install the packages.

Which magic function should you use?

A!pjp

B%load

C!conda

D%pip

Answer : D

Question 4

You manage an Azure Machine Learning workspace.

You build an image recognition training pipeline, which includes hyperparameter tuning. For each epoch run, you plan to log the following metrics:

* the transformed images used for training in an existing folder

* a description to explain the hyperparameter changes

You need to configure logging for the experiment.

Which two functions should you use? Each correct answer presents part of the solution. Choose two. NOTE: Each correct selection is worth one point.

Amlflow.log_artifact()

Bmlflow.log_artifacts()

Cmlflow.logjnetric()

Dmlflow.log_param()

Answer : B, D

Question 5

You are with a time series dataset in Azure Machine Learning Studio.

You need to split your dataset into training and testing subsets by using the Split Data module.

Which splitting mode should you use?

ARegular Expression Split

BSplit Rows with the Randomized split parameter set to true

CRelative Expression Split

DRecommender Split

Answer : B

Split Rows: Use this option if you just want to divide the data into two parts. You can specify the percentage of data to put in each split, but by default, the data is divided 50-50.

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

Question 6

You are creating a machine learning model. You have a dataset that contains null rows.

You need to use the Clean Missing Data module in Azure Machine Learning Studio to identify and resolve the null and missing data in the dataset.

Which parameter should you use?

AReplace with mean

BRemove entire column

CRemove entire row

DHot Deck

Answer : B

Remove entire row: Completely removes any row in the dataset that has one or more missing values. This is useful if the missing value can be considered randomly missing.

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

Question 7

You train and register an Azure Machine Learning model

You plan to deploy the model to an online endpoint

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 managed online endpoint with the default authentication settings. Deploy the model to the online endpoint.

Does the solution meet the goal?

AYes

BNo

Answer : B

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