| Exam Name: | Designing and Implementing a Data Science Solution on Azure | ||
| Exam Code: | DP-100 Dumps | ||
| Vendor: | Microsoft | Certification: | Microsoft Azure |
| Questions: | 525 Q&A's | Shared By: | deacon |
You are creating a new Azure Machine Learning pipeline using the designer.
The pipeline must train a model using data in a comma-separated values (CSV) file that is published on a
website. You have not created a dataset for this file.
You need to ingest the data from the CSV file into the designer pipeline using the minimal administrative effort.
Which module should you add to the pipeline in Designer?
You create an Azure Machine Learning pipeline named pipeline 1 with two steps that contain Python scnpts. Data processed by the first step is passed to the second step.
You must update the content of the downstream data source of pipeline 1 and run the pipeline again.
You need to ensure the new run of pipeline 1 fully processes the updated content.
Solution: Change the value of the compute.target parameter of the PythonScriptStep object in the two steps.
Does the solution meet the goal '
You manage an Azure Machine Learning workspace That has an Azure Machine Learning datastore.
Data must be loaded from the following sources:
• a credential-less Azure Blob Storage
• an Azure Data Lake Storage (ADLS) Gen 2 which is not a credential-less datastore
You need to define the authentication mechanisms to access data in the Azure Machine Learning datastore.
Which data access mechanism should you use? To answer, move the appropriate data access mechanisms to the correct storage types. You may use each data access mechanism once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
You plan to use a Data Science Virtual Machine (DSVM) with the open source deep learning frameworks Caffe2 and Theano. You need to select a pre configured DSVM to support the framework.
What should you create?