DP-100 Exam Dumps - Microsoft Azure Questions and Answers

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,f2i

1,1.2,0

2,1,1,

1 3,2.1,0

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?

Your team is building a data engineering and data science development environment.

The environment must support the following requirements:

support Python and Scala

compose data storage, movement, and processing services into automated data pipelines

the same tool should be used for the orchestration of both data engineering and data science

support workload isolation and interactive workloads

enable scaling across a cluster of machines

You need to create the environment.

What should you do?

You create a binary classification model using Azure Machine Learning Studio.

You must use a Receiver Operating Characteristic (RO C) curve and an F1 score to evaluate the model.

You need to create the required business metrics.

How should you complete the experiment? To answer, select the appropriate options in the dialog box in the answer area.

NOTE: Each correct selection is worth one point.

You manage an Azure Machine Learning workspace named workspace1.

You must register an Azure Blob storage datastore in workspace1 by using an access key. You develop Python SDK v2 code to import all modules required to register the datastore.

You need to complete the Python SDK v2 code to define the datastore.

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

NOTE: Each correct selection is worth one point.

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 endpoint1 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 scoring_script parameter.

Does the solution meet the goal?

You create a multi-class image classification deep learning model that uses a set of labeled images. You

create a script file named train.py that uses the PyTorch 1.3 framework to train the model.

You must run the script by using an estimator. The code must not require any additional Python libraries to be installed in the environment for the estimator. The time required for model training must be minimized.

You need to define the estimator that will be used to run the script.

Which estimator type should you use?

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?

You are training machine learning models in Azure Machine Learning. You use Hyperdrive to tune the hyperparameters. In previous model training and tuning runs, many models showed similar performance. You need to select an early termination policy that meets the following requirements:

• accounts for the performance of all previous runs when evaluating the current run

• avoids comparing the current run with only the best performing run to date

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

You deploy a model as an Azure Machine Learning real-time web service using the following code.

The deployment fails.

You need to troubleshoot the deployment failure by determining the actions that were performed during deployment and identifying the specific action that failed.

Which code segment should you run?

You create an Azure Machine learning workspace and load a Python training script named tram.py in the src subfolder. The dataset used to train your model is available locally. You run the following script to tram the model:

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