Question 1

You need to select an environment that will meet the business and data requirements.

Which environment should you use?

Options :

A : Azure HDInsight with Spark MLlib

B :

Azure Cognitive Services

C : Azure Machine Learning Studio

D : Microsoft Machine Learning Server

Answer: D

Question 2

You use Azure Machine Learning studio to analyze a dataset containing a decimal column named column1. You need to verity that the column1 values are normally distributed. Which static should you use?

Options :

A : Profile

B : Type

C : Max

D : Mean

Answer: A

Question 3

You create a batch inference pipeline by using the Azure ML SDK. You configure the pipeline parameters by executing the following code:

You need to obtain the output from the pipeline execution. Where will you find the output?

Options :

A : the Activity Log in the Azure portal for the Machine Learning workspace

B : a file named parallel_run_step.txt located in the output folder

C : the digitjdentification.py script

D : the Inference Clusters tab in Machine Learning studio

E : the debug log

Answer: B

Question 4

You are planning to host practical training to acquaint learners with data visualization creation using Python. Learner devices are able to connect to the internet. Learner devices are currently NOT configured for Python development. Also, learners are unable to install software on their devices as they lack administrator permissions. Furthermore, they are unable to access Azure subscriptions. It is imperative that learners are able to execute Python-based data visualization code. Which of the following actions should you take?

Options :

A : You should consider configuring the use of Azure Container Instance.

B : You should consider configuring the use of Azure BatchAI.

C : You should consider configuring the use of Azure Notebooks.

D : You should consider configuring the use of Azure Kubernetes Service.

Answer: C

Question 5

You create and register a model in an Azure Machine Learning workspace.

You must use the Azure Machine Learning SDK to implement a batch inference pipeline that uses a

ParallelRunStep to score input data using the model. You must specify a value for the ParallelRunConfig

compute_target setting of the pipeline step.

You need to create the compute target.

Which class should you use?

Options :

A : BatchCompute

B : AdlaCompute

C : AmlCompute

D : Aks Compute

Answer: C