Become Microsoft Certified with updated DP-100 exam questions and correct answers
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 develop and train a machine learning model to predict fraudulent transactions for a hotel booking website. Traffic to the site varies considerably. The site experiences heavy traffic on Monday and Friday and much lower traffic on other days. Holidays are also high web traffic days. You need to deploy the model as an Azure Machine Learning real-time web service endpoint on compute that can dynamically scale up and down to support demand. Which deployment compute option should you use?
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?


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