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#### Question 1

You must store data in Azure Blob Storage to support Azure Machine Learning.You need to transfer the data into Azure Blob Storage.What are three possible ways to achieve the goal? Each correct answer presents acomplete solution.NOTE: Each correct selection is worth one point.

A. Bulk Insert SQL Query

B. AzCopy

C. Python script

D. Azure Storage Explorer

E. Bulk Copy Program (BCP)

#### Question 2

You are building a regression model tot estimating the number of calls during an event.You need to determine whether the feature values achieve the conditions to build aPoisson regression model.Which two conditions must the feature set contain? I ach correct answer presents part ofthe solution. NOTE: Each correct selection is worth one point.

A. The label data must be a negative value.

B. The label data can be positive or negative,

C. The label data must be a positive value

D. The label data must be non discrete.

E. The data must be whole numbers.

#### Question 3

You are performing a filter based feature selection for a dataset 10 build a multi classclassifies by using Azure Machine Learning Studio.The dataset contains categorical features that are highly correlated to the output label column.You need to select the appropriate feature scoring statistical method to identify the keypredictors. Which method should you use?

A. Chi-squared

B. Spearman correlation

C. Kendall correlation

D. Person correlation

#### Question 4

Note: This question is part of a series of questions that present the same scenario. Eachquestion in the series contains a unique solution that might meet the stated goals. Somequestion 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 Scale and Reduce sampling mode.Does the solution meet the goal?

A. Yes

B. No

#### Question 5

You plan to use a Deep Learning Virtual Machine (DLVM) to train deep learning modelsusing Compute Unified Device Architecture (CUDA) computations.You need to configure the DLVM to support CUDA.What should you implement?

A. Intel Software Guard Extensions (Intel SGX) technology

B. Solid State Drives (SSD)

C. Graphic Processing Unit (GPU)

D. Computer Processing Unit (CPU) speed increase by using overcloking

E. High Random Access Memory (RAM) configuration

#### Question 6

Note: This question is part of a series of questions that present the same scenario. Eachquestion in the series contains a unique solution that might meet the stated goals. Somequestion 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 Learning learning Studio.One class has a much smaller number of observations than the other classes in the trainingYou need to select an appropriate data sampling strategy to compensate for the class imbalance.Solution: You use the Synthetic Minority Oversampling Technique (SMOTE) sampling mode.Does the solution meet the goal?

A. Yes

B. No

#### Question 7

You are a data scientist creating a linear regression model.You need to determine how closely the data fits the regression line.Which metric should you review?

A. Coefficient of determination

B. Recall

C. Precision

D. Mean absolute error

E. Root Mean Square Error

#### Question 8

You are building a recurrent neural network to perform a binary classification. You reviewthe training loss, validation loss, training accuracy, and validation accuracy for each training epoch.You need to analyze model performance.Which observation indicates that the classification model is over fitted?

A. The training loss .stays constant and the validation loss stays on a constant value andclose to the training loss value when training the model.

B. The training loss increases while the validation loss decreases when training the model.

C. The training loss decreases while the validation loss increases when training the model.

D. The training loss stays constant and the validation loss decreases when training the model.

#### Question 9

Note: This question is part of a series of questions that present the same scenario. Eachquestion in the series contains a unique solution that might meet the stated goals. Somequestion 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 model to predict the price of a student’s artwork depending on thefollowing variables: the student’s length of education, degree type, and art form.You start by creating a linear regression model.You need to evaluate the linear regression model.Solution: Use the following metrics: Mean Absolute Error, Root Mean Absolute Error,Relative Absolute Error, Relative Squared Error, and the Coefficient of Determination.Does the solution meet the goal?

A. Yes

B. No

#### Question 10

You are creating a binary classification by using a two-class logistic regression model.You need to evaluate the model results for imbalance.Which evaluation metric should you use?

A. Relative Absolute Error

B. AUC Curve

C. Mean Absolute Error

D. Relative Squared Error