Become Microsoft Certified with updated DP-100 exam questions and correct answers
You train and register a model in your Azure Machine Learning workspace. You must publish a pipeline that enables client applications to use the model for batch inferencing. You must use a pipeline with a single ParallelRunStep step that runs a Python inferencing script to get predictions from the input data. You need to create the inferencing script for the ParallelRunStep pipeline step. Which two functions should you include? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
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 analyzing a numerical dataset which contains missing values in several columns. You must clean the missing values using an appropriate operation without affecting the dimensionality of the feature set. You need to analyze a full dataset to include all values. Solution: Replace each missing value using the Multiple Imputation by Chained Equations (MICE) method. Does the solution meet the goal?
You plan to use the Hyperdrive feature of Azure Machine Learning to determine the optimal hyperparameter values when training a model. You must use Hyperdrive to try combinations of the following hyperparameter values: learning_rate: any value between 0.001 and 0.1 batch_size: 16, 32, or 64 You need to configure the search space for the Hyperdrive experiment. Which two parameter expressions should you use? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
You use the following Python code in a notebook to deploy a model as a web service:
The deployment fails.
You need to use the Python SDK in the notebook to determine the events that occurred during
service deployment an initialization.
Which code segment 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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