You are designing an AI application that uses computer vision to detect cracks in car windshields, and warns drivers when a windshield should be repaired or replaced. When tested in good lighting conditions, the application successfully detects 99% of dangerously damaged glass. Which of the following statements should you include in the application’s user interface?

• When used in good lighting conditions, this application can be used to identify potentially dangerous cracks and defects in windshields. If you suspect your windshield is damaged, even if the application does not detect any defects, you should have it inspected by a professional.

• This application detects damage in your windshield. If the application detects a defect, have the windshield replaced or repaired. If no defect is detected, you're good to go!

• This application detects damage in any glass surface, but you must accept responsibility for using it only in appropriate lighting conditions.

Azure ML studio uses which type of datastores? Select one or more:

• File

• Blob

• Table

• Queue

You have published your Language Understanding application. What information does a client application developer need to get predictions from it?

• The endpoint and key for the application's authoring resource

• The endpoint and key for the application's prediction resource

• The Azure credentials of the user who published the Language Understanding application

You need to provision an Azure resource that will be used to author a new Language Understanding application. What kind of resource should you create?

• Language Understanding

• Cognitive Services

• Text Analytics

You use Azure Machine Learning designer to create a training pipeline and an inference pipeline for a regression model. Now you plan to deploy the inference pipeline as a real-time service. What kind of compute target should you create to host the service?

• Compute Instance

• Compute Cluster

• Inference Cluster

An automobile dealership wants to use historic car sales data to train a machine learning model. The model should predict the price of a pre-owned car based on its make, model, engine size, and mileage. What kind of machine learning model should the dealership use automated machine learning to create?

• Regression

• Classification

• Time Series

A bank wants to use historic loan repayment records to categorize loan applications as low-risk or high-risk based on characteristics like the loan amount, the income of the borrower, and the loan period. What kind of machine learning model should the dealership use automated machine learning to create?

• Regression

• Time Series

• Classification

You want to use automated machine learning to train a regression model with the best possible R2 score. How should you configure the automated machine learning experiment?

• Set the Primary metric to R2 score

• Block all algorithms other than GradientBoosting

• Enable Featurization

You plan to use the Computer Vision service to read text in a large PDF document. Which API should you use?

• The OCR API

• The Recognize Text API

• The Read API

You use Azure Machine Learning designer to create a training pipeline for a clustering model. Now you want to use the model in an inference pipeline. Which module should you use to infer cluster predictions from the model?

• Score Model

• Train Clustering Model

• Assign Data to Clusters