Become Microsoft Certified with updated DP-100 exam questions and correct answers
You use Azure Machine Learning Designer to load the following datasets into an experiment:
Dataset1
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 Join Data component.
Does the solution meet the goal?
You plan to run a script as an experiment using a Script Run Configuration. The script uses modules from the scipy library as well as several Python packages that are not typically installed in a default conda environment. You plan to run the experiment on your local workstation for small datasets and scale out the experiment by running it on more powerful remote compute clusters for larger datasets. You need to ensure that the experiment runs successfully on local and remote compute with the least administrative effort. What should you do?
You must use the Azure Machine Learning SDK to interact with data and experiments in the
workspace.
You need to configure the config.json file to connect to the workspace from the Python environment.
Which two additional parameters must you add to the config.json file in order to connect to the
workspace? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
You create an Azure Machine Learning workspace. The workspace contains a dataset named
sample.dataset, a compute instance, and a compute cluster. You must create a two-stage pipeline
that will prepare data in the dataset and then train and register a model based on the prepared data.
The first stage of the pipeline contains the following code:
You need to identify the location containing the output of the first stage of the script that you can use
as input for the second stage. Which storage location should you use?
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 Apply Transformation module.
Does the solution meet the goal?
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