You have a reference to a Workspace named ws. Which code retrieves the default datastore for the workspace?

• default_ds = Datastore.get(ws, 'default')

• default_ds = ws.Datastores[0]

• default_ds = ws.get_default_datastore()

A datastore contains a CSV file of structured data that you want to use as a Pandas dataframe. Which kind of dataset should you create to make it easy to do this?

• A file dataset

• A tabular dataset

You want a script to stream data directly from a file dataset. Which mode should you use?

• as_mount()

• as_download()

• as_upload()

You have uploaded some data files to a folder in a blob container, and registered the blob container as a datastore in your Azure Machine Learning workspace. You want to run a script as an experiment that loads the data files and trains a model. What should you do?

• Save the experiment script in the same blob folder as the data files.

• Create a data reference for the datastore location and pass it to the script as a parameter.

• Create global variables for the Azure Storage account name and key in the experiment script.

You are solving a classification task. You must evaluate your model on a limited data sample by using k-fold cross-validation. You start by configuring a k parameter as the number of splits. You need to configure the k parameter for the cross-validation. Which value should you use?

• K=1

• K=10

• K=0.5

• K=0.9

You are analyzing a dataset by using Azure Machine Learning Studio. You need to generate a statistical summary that contains the p-value and the unique count for each feature column. Which two modules can you use?

• Computer Linear Correlation

• Export Count Table

• Execute Python Script

• Convert to Indicator Values

• Summarize Data

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. Which is best solution

• Multiple Imputation by Chained Equation

• Remove Entire Row

• Replace with mean

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?

• Assign Data to Clusters

• Load Trained Model

• Partition and Sample

• Tune Model-Hyperparameters

You are building a binary classification model by using a supplied training set. The training set is imbalanced between two classes. You need to resolve the data imbalance. What are three possible ways to achieve this goal?

• Penalize the classification

• Resample the dataset using undersampling or oversampling

• Normalize the training feature set

• Generate synthetic samples in the minority class

• Use accuracy as the evaluation metric of the model

You are moving a large dataset from Azure Machine Learning Studio to a Weka environment. You need to format the data for the Weka environment. Which module should you use?

• Convert to CSV

• Convert to Dataset

• Convert to ARFF

• Convert to SVMLight