Free Microsoft DP-100 Exam Questions

You use Azure Machine Learning Designer to load the following datasets into an experiment: Dataset1You 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?

This question is included in a number of questions that depicts the identical set-up. However, every question has a distinctive result. Establish if the recommendation satisfies the requirements. You have been tasked with evaluating your model on a partial data sample via k-fold cross-validation. You have already configured a k parameter as the number of splits. You now have to configure the k parameter for the cross-validation with the usual value choice. Recommendation: You configure the use of the value k=1. Will the requirements be satisfied? 

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?

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 create a model to forecast weather conditions based on historical data. You need to create a pipeline that runs a processing script to load data from a datastore and pass the processed data to a machine learning model training script. Solution: Run the following code:

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?