Microsoft Azure DP-100 Exam Dumps

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?

You use the Azure Machine Learning Python SDK to define a pipeline to train a model.

The data used to train the model is read from a folder in a datastore.

You need to ensure the pipeline runs automatically whenever the data in the folder changes.

What should you do?

You plan to implement an Azure Machine Learning solution. You have the following requirements:

• Run a Jupyter notebook to interactively tram a machine learning model.

• Deploy assets and workflows for machine learning proof of concept by using scripting rather than custom programming.

You need to select a development technique for each requirement

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

NOTE: Each correct selection is worth one point.

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 have an Azure Machine Learning workspace. You connect to a terminal session from the Notebooks page in Azure Machine Learning studio.

You plan to add a new Jupyter kernel that will be accessible from the same terminal session.

You need to perform the task that must be completed before you can add the new kernel.

Solution: Delete the Python 3.6 - AzureML kernel.

Does the solution meet the goal?