Free Microsoft DP-100 Exam Questions

You train and register an Azure Machine Learning model You plan to deploy the model to an online endpoint You need to ensure that applications will be able to use the authentication method with a nonexpiring artifact to access the model. Solution: Create a managed online endpoint and set the value of its auth.mode parameter to aml.token. Deploy the model to the online endpoint. 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 have a deployment of an Azure OpenAI Service base model. You plan to fine-tune the model. You need to prepare a file that contains training data. Which file format should you use?

You manage an Azure Machine Learning workspace. The development environment tor managing the workspace is configured to use Python SDK v2 in Azure Machine Learning Notebooks A Synapse Spark Compute is currently attached and uses system-assigned identity You need to use Python code to update the Synapse Spark Compute 10 use a user-assigned identity. Solution: Configure the IdentityConfiguration class with the appropriate identity type. Does the solution meet the goal?

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?