Microsoft Updated DP-100 Exam Questions and Answers by ned

You are running a training experiment on remote compute in Azure Machine Learning.

The experiment is configured to use a conda environment that includes the mlflow and azureml-contrib-run packages.

You must use MLflow as the logging package for tracking metrics generated in the experiment.

You need to complete the script for the experiment.

How should you complete the code? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

You create a binary classification model. The model is registered in an Azure Machine Learning workspace. You use the Azure Machine Learning Fairness SDK to assess the model fairness.

You develop a training script for the model on a local machine.

You need to load the model fairness metrics into Azure Machine Learning studio.

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 are a data scientist using Azure Machine Learning Studio.

You need to normalize values to produce an output column into bins to predict a target column.

Solution: Apply an Equal Width with Custom Start and Stop binning mode.

Does the solution meet the goal?

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:

Does the solution meet the goal?