NO.99 You are creating an experiment by using Azure Machine Learning Studio.
You must divide the data into four subsets for evaluation. There is a high degree of missing values in the dat a. You must prepare the data for analysis.
You need to select appropriate methods for producing the experiment.
Which three modules should you run 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.

NO.100 You are using Azure Machine Learning to train machine learning models. You need a compute target on which to remotely run the training script. You run the following Python code:

NO.101 You have a dataset that contains 2,000 rows. You are building a machine learning classification model by using Azure Learning Studio. You add a Partition and Sample module to the experiment.
You need to configure the module. You must meet the following requirements:
Divide the data into subsets
Assign the rows into folds using a round-robin method
Allow rows in the dataset to be reused
How should you configure the module? To answer, select the appropriate options in the dialog box in the answer area.
NOTE: Each correct selection is worth one point.

NO.102 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.

NO.103 You plan to use Hyperdrive to optimize the hyperparameters selected when training a model. You create the following code to define options for the hyperparameter experiment


For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.

NO.104 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.

NO.105 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 an Azure Machine Learning service datastore in a workspace. The datastore contains the following files:
* /data/2018/Q1.csv
* /data/2018/Q2.csv
* /data/2018/Q3.csv
* /data/2018/Q4.csv
* /data/2019/Q1.csv
All files store data in the following format:
id,f1,f2,I
1,1,2,0
2,1,1,1
3,2,1,0
4,2,2,1
You run the following code:

You need to create a dataset named training_data and load the data from all files into a single data frame by using the following code:

Solution: Run the following code:

Does the solution meet the goal?

NO.106 You previously deployed a model that was trained using a tabular dataset named training-dataset, which is based on a folder of CSV files.
Over time, you have collected the features and predicted labels generated by the model in a folder containing a CSV file for each month. You have created two tabular datasets based on the folder containing the inference data: one named predictions-dataset with a schema that matches the training data exactly, including the predicted label; and another named features-dataset with a schema containing all of the feature columns and a timestamp column based on the filename, which includes the day, month, and year.
You need to create a data drift monitor to identify any changing trends in the feature data since the model was trained. To accomplish this, you must define the required datasets for the data drift monitor.
Which datasets should you use to configure the data drift monitor? To answer, drag the appropriate datasets to the correct data drift monitor options. Each source 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.

NO.107 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 Learning learning Studio.
One class has a much smaller number of observations than the other classes in the training You need to select an appropriate data sampling strategy to compensate for the class imbalance.
Solution: You use the Synthetic Minority Oversampling Technique (SMOTE) sampling mode.
Does the solution meet the goal?

NO.108 An organization uses Azure Machine Learning service and wants to expand their use of machine learning.
You have the following compute environments. The organization does not want to create another compute environment.

You need to determine which compute environment to use for the following scenarios.
Which compute types should you use? To answer, drag the appropriate compute environments to the correct scenarios. Each compute environment 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.

NO.109 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 analyzing a numerical dataset which contain missing values in several columns.
You must clean the missing values using an appropriate operation without affecting the dimensionality of the feature set.
You need to analyze a full dataset to include all values.
Solution: Use the last Observation Carried Forward (IOCF) method to impute the missing data points.
Does the solution meet the goal?

NO.110 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.

NO.111 You manage an Azure Machine Learning workspace by using the Python SDK v2.
You must create a compute cluster in the workspace. The compute cluster must run workloads and properly handle interruptions. You start by calculating the maximum amount of compute resources required by the workloads and size the cluster to match the calculations.
The cluster definition includes the following properties and values:
* name=”mlcluster1”
* size=”STANDARD.DS3.v2″
* min_instances=1
* maxjnstances=4
* tier=”dedicated”
The cost of the compute resources must be minimized when a workload is active Of idle. Cluster property changes must not affect the maximum amount of compute resources available to the workloads run on the cluster.
You need to modify the cluster properties to minimize the cost of compute resources.
Which properties should you modify? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

NO.112 You are performing sentiment analysis using a CSV file that includes 12,000 customer reviews written in a short sentence format. You add the CSV file to Azure Machine Learning Studio and configure it as the starting point dataset of an experiment. You add the Extract N-Gram Features from Text module to the experiment to extract key phrases from the customer review column in the dataset.
You must create a new n-gram dictionary from the customer review text and set the maximum n-gram size to trigrams.
What should you select? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

NO.113 Your Azure Machine Learning workspace has a dataset named real_estate_dat a. A sample of the data in the dataset follows.

You want to use automated machine learning to find the best regression model for predicting the price column.
You need to configure an automated machine learning experiment using the Azure Machine Learning SDK.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

NO.114 You create an Azure Databricks workspace and a linked Azure Machine Learning workspace.
You have the following Python code segment in the Azure Machine Learning workspace:
import mlflow
import mlflow.azureml
import azureml.mlflow
import azureml.core
from azureml.core import Workspace
subscription_id = ‘subscription_id’
resourse_group = ‘resource_group_name’
workspace_name = ‘workspace_name’
ws = Workspace.get(name=workspace_name,
subscription_id=subscription_id,
resource_group=resource_group)
experimentName = “/Users/{user_name}/{experiment_folder}/{experiment_name}” mlflow.set_experiment(experimentName) uri = ws.get_mlflow_tracking_uri() mlflow.set_tracking_uri(uri) Instructions: For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.