What should you do? A. Apply an analysis of variance (ANOVA). B. Apply a Pearson correlation coefficient. C. Apply a Spearman correlation coefficient. D. Apply a linear discriminant analysis. Explanation: The linear discriminant analysis method works only on continuous variables, not categorical or ordinal variables. Linear discriminant analysis is similar to analysis of variance (ANOVA) […]

You are creating a machine learning model. You have a dataset that contains null rows. You need to use the Clean Missing Data module in Azure Machine Learning Studio to identify and resolve the null and missing data in the dataset. Which parameter should you use? A. Replace with mean B. Remove entire column C. […]

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? A. Assign Data to Clusters B. Load Trained Model C. Partition and Sample D. Tune Model-Hyperparameters Explanation: Partition and Sample with the Stratified split option outputs multiple datasets, partitioned […]

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? A. k=0.5 B. k=0 C. k=5 D. […]

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 a Quantiles binning mode with a PQuantile normalization. Does the solution meet the goal? A. Yes B. No Explanation: Use the Entropy MDL binning mode which […]

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? A. Yes B. No Explanation: Use the Entropy MDL binning […]

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: Calculate the column median value and use the median value as the […]

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: Remove the entire column that contains the missing data point. Does the […]

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) […]

You plan to deliver a hands-on workshop to several students. The workshop will focus on creating data visualizations using Python. Each student will use a device that has internet access. Student devices are not configured for Python development. Students do not have administrator access to install software on their devices. Azure subscriptions are not available […]