Become Microsoft Certified with updated DP-100 exam questions and correct answers
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?
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 create an Azure Machine Learning workspace. The workspace contains a dataset named
sample.dataset, a compute instance, and a compute cluster. You must create a two-stage pipeline
that will prepare data in the dataset and then train and register a model based on the prepared data.
The first stage of the pipeline contains the following code:
You need to identify the location containing the output of the first stage of the script that you can use
as input for the second stage. Which storage location should you use?
You create an Azure Machine Learning workspace. You must configure an event handler to send an email notification when data drift is detected in the workspace datasets. You must minimize development efforts. You need to configure an Azure service to send the notification. Which Azure service should you use?
You create an Azure Machine Learning workspace. The workspace contains a dataset named
sample.dataset, a compute instance, and a compute cluster. You must create a two-stage pipeline
that will prepare data in the dataset and then train and register a model based on the prepared data.
The first stage of the pipeline contains the following code:
You need to identify the location containing the output of the first stage of the script that you can use
as input for the second stage. Which storage location should you use?
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