Which module should you use?
You are building an Azure Machine Learning experiment.
You need to transform a string column into a label column for a Multiclass Decision Jungle module.
Which module should you use?
What capability does the module provide?
You plan to use Azure Machine Learning to develop a predictive model. You plan to include an Execute Python
Script module.
What capability does the module provide?
Which three actions can you perform by using both R cod…
You have an Azure Machine Learning environment.
You are evaluating whether to use R code or Python.
Which three actions can you perform by using both R code and Python in the Machine Learning environment?
Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
Which module should you add to the experiment?
You are building an Azure Machine Learning experiment.
You need to transform 47 numeric columns into a set of 10 linearly uncorrelated features.
Which module should you add to the experiment?
Which module should you use?
You are building an Azure Machine Learning experiment.
You need to transform a string column that has 47 distinct values into a binary indicator column. The solution
must use the One-vs-All Multiclass model.
Which module should you use?
You need to improve the accuracy of the dataset, while …
You have a dataset that is missing values in a column named Column3. Column3 is correlated to two columns
named Column4 and Column5.
You need to improve the accuracy of the dataset, while minimizing data loss.
What should you do?
You need to integrate code and formatted text into an A…
You need to integrate code and formatted text into an Azure Machine Learning experiment that enables
interactive execution.
What should you use?
Which model should you use?
You are building an Azure Machine Learning solution for an online retailer.When a customer selects a product, you need to recommend products that the customer might like to purchase
at the same time. The recommendation should be based on what other customers purchased when they
purchased the same product.
Which model should you use?
What is the cause of the errors?
You have an Azure Machine Learning experiment.
You discover that a model causes many errors in a production dataset. The model causes only few errors in the
training data.
What is the cause of the errors?
Which two actions should you perform to convert the Mac…
DRAG DROP
Note: This question is part of a series of questions that use the same scenario. For your convenience, the
scenario is repeated in each question. Each question presents a different goal and answer choices, but the text
of the scenario is exactly the same in each question in this series.
You plan to create a predictive analytics solution for credit risk assessment and fraud prediction in Azure
Machine Learning. The Machine Learning workspace for the solution will be shared with other users in your
organization. You will add assets to projects and conduct experiments in the workspace.
The experiments will be used for training models that will be published to provide scoring from web services.
The experiment for fraud prediction will use Machine Learning modules and APIs to train the models and will
predict probabilities in an Apache Hadoop ecosystem.
You finish training the model and are ready to publish a predictive web service that will provide the users with
the ability to specify the data source and the save location of the results. The model includes a Split Data
module.
Which two actions should you perform to convert the Machine Learning experiment to a predictive web service?
To answer, drag the appropriate actions to the correct targets. Each action may be used once, more than once,
or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.Select and Place: