You are building a multilingual chatbot.
You need to send a different answer for positive and negative messages.
Which two Text Analytics APIs should you use? Each correct answer presents part of the solution. (Choose two.) NOTE: Each correct selection is worth one point.

• A.Linked entities from a well-known knowledge base
• B.Sentiment Analysis
• C.Key Phrases
• D.Detect Language
• E.Named Entity Recognition

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You plan to build a chatbot to support task tracking.
You create a Language Understanding service named lu1.
You need to build a Language Understanding model to integrate into the chatbot. The solution must minimize development time to build the model.
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order. (Choose four.)

Correct Answer:

Step 1: Add a new application
Create a new app
* Sign in to the LUIS portal with the URL of https://www.luis.ai.
* Select Create new app.
* Etc.
Step 2: Add example utterances.
In order to classify an utterance, the intent needs examples of user utterances that should be classified with this intent.
Step 3: Train the application
Step 4: Publish the application
In order to receive a LUIS prediction in a chat bot or other client application, you need to publish the app to the prediction endpoint.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/tutorial-intents-only

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You are developing a photo application that will find photos of a person based on a sample image by using the Face API.
You need to create a POST request to find the photos.
How should you complete the request? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Correct Answer:

Reference:
https://docs.microsoft.com/en-us/rest/api/faceapi/face/detectwithurl
https://docs.microsoft.com/en-us/rest/api/faceapi/face/findsimilar

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You plan to use containerized versions of the Anomaly Detector API on local devices for testing and in on-premises datacenters.
You need to ensure that the containerized deployments meet the following requirements:
* Prevent billing and API information from being stored in the command-line histories of the devices that run the container.
* Control access to the container images by using Azure role-based access control (Azure RBAC).
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order. (Choose four.) NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.

Correct Answer:

Explanation

Step 1: Pull the Anomaly Detector container image.
Step 2: Create a custom Dockerfile
Step 3: Push the image to an Azure container registry.
To push an image to an Azure Container registry, you must first have an image.
Step 4: Distribute the docker run script
Use the docker run command to run the containers.
Reference:
https://docs.microsoft.com/en-us/azure/container-registry/container-registry-intro

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You are creating an enrichment pipeline that will use Azure Cognitive Search. The knowledge store contains unstructured JSON data and scanned PDF documents that contain text.
Which projection type should you use for each data type? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Correct Answer:

Explanation

Box 1: Object projection
Object projections are JSON representations of the enrichment tree that can be sourced from any node.
Box 2: File projection
File projections are similar to object projections and only act on the normalized_images collection.
Reference:
https://docs.microsoft.com/en-us/azure/search/knowledge-store-projection-overview

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