Question 1

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 2

You create an Azure Machine Learning workspace named workspaces. You create a Python SDK v2 notebook to perform custom model training in wortcspacel. You need to run the notebook from Azure Machine Learning Studio in workspace1. What should you provision first?

Options :

A : default storage account

B : real-time endpoint

C : Azure Machine Learning compute cluster

D : Azure Machine Learning compute instance

Answer: D

Question 3

You have an Azure Machine Learning workspace.

You plan to tune a model hyperparameter when you train the model.

You need to define a search space that returns a normally distributed value.

Which parameter should you use?

Options :

A : QUniform

B : LogUniform

C : Uniform

D : LogNormal

Answer: D

Question 4

You are a data scientist working for a hotel booking website company. You use the Azure Machine Learning

service to train a model that identifies fraudulent transactions.

You must deploy the model as an Azure Machine Learning real-time web service using the Model.deploy

method in the Azure Machine Learning SDK. The deployed web service must return real-time predictions of

fraud based on transaction data input.

You need to create the script that is specified as the entry_script parameter for the InferenceConfig class used

to deploy the model.

What should the entry script do?

Options :

A : Start a node on the inference cluster where the web service is deployed.

B : Register the model with appropriate tags and properties.

C : Create a Conda environment for the web service compute and install the necessary Python packages.

D : Load the model and use it to predict labels from input data.

E : Specify the number of cores and the amount of memory required for the inference compute.

Answer: D

Question 5

You are implementing hyperparameter tuning by using Bayesian sampling for a model training from a notebook. The notebook is in an Azure Machine Learning workspace that uses a compute cluster with 20 nodes. The code implements Bandit termination policy with slack factor set to 0.2 and the HyperDriveConfig class instance with max_concurrent_runs set to 10. You must increase effectiveness of the tuning process by improving sampling convergence. You need to select which sampling convergence to use. What should you select?

Options :

A : Set the value of slack factor of early_termination_policy to 09.

B : Set the value of max_concurrent_runs of HyperDriveConfig to 4.

C : Set the value of slack factor of early_termination_policy to 0.1.

D : Set the value of max_concurrent_runs of HyperDriveConfig to 20.

Answer: B