Become Microsoft Certified with updated DP-100 exam questions and correct answers
You use Azure Machine Learning Studio to build a machine learning experiment. You need to divide data into two distinct datasets. Which module should you use?
An organization creates and deploys a multi-class image classification deep learning model that uses a set of labeled photographs. The software engineering team reports there is a heavy inferencing load for the prediction web services during the summer. The production web service for the model fails to meet demand despite having a fully-utilized compute cluster where the web service is deployed. You need to improve performance of the image classification web service with minimal downtime and minimal administrative effort. What should you advise the IT Operations team to 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 creating a new experiment in Azure Machine Learning Studio. One class has a much smaller number of observations than the other classes in the training set. You need to select an appropriate data sampling strategy to compensate for the class imbalance. Solution: You use the Stratified split for the sampling mode. Does the solution meet the goal?
You plan to run a Python script as an Azure Machine Learning experiment. The script must read files from a hierarchy of folders. The files will be passed to the script as a dataset argument. You must specify an appropriate mode for the dataset argument. Which two modes can you use? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.

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