Question 56

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?
  • Question 57

    You need to modify the inputs for the global penalty event model to address the bias and variance issue.
    Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

    Question 58

    You publish a batch inferencing pipeline that will be used by a business application.
    The application developers need to know which information should be submitted to and returned by the REST interface for the published pipeline.
    You need to identify the information required in the REST request and returned as a response from the published pipeline.
    Which values should you use in the REST request and to expect in the response? To answer, select the appropriate options in the answer area.
    NOTE: Each correct selection is worth one point.

    Question 59

    You are evaluating a completed binary classification machine learning model.
    You need to use the precision as the valuation metric.
    Which visualization should you use?
  • Question 60

    You are a data scientist working for a hotel booking website company. You use the Azure Machine Learning service to train a model that identifies fraudulent transactions.
    You must deploy the model as an Azure Machine Learning real-time web service using the Model.deploy method in the Azure Machine Learning SDK. The deployed web service must return real-time predictions of fraud based on transaction data input.
    You need to create the script that is specified as the entry_script parameter for the InferenceConfig class used to deploy the model.
    What should the entry script do?