Stay ahead with 100% Free Microsoft Designing and Implementing a Data Science Solution on Azure DP-100 Dumps Practice Questions
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?
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?
You manage an Azure Machine Learning workspace. You plan to irain a natural language processing (NLP) tew classification model in multiple languages by using Azure Machine learning Python SDK v2. You need to configure the language of the text classification job by using automated machine learning. Which method of the TextClassifkationlob class should you use?
You use Azure Machine Learning Studio to build a machine learning experiment. You need to divide data into two distinct datasets. Which module should you use?
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