You are building an app that will share user images.
You need to configure the app to meet the following requirement’s
• uploaded images must be scanned and any text must be extracted from the images.
• Extracted text must be analyzed for the presence of profane language.
• The solution must minimize development effort.
what should you use for each requirement? To answer, select the apocopate opinions in the answer area.
NOTE: Each correct selection is worth one point.

You have a Language Understanding solution that runs in a Docker container.
You download the Language Understanding container image from the Microsoft Container Registry (MCR).
You need to deploy the container image to a host computer.
Which three 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.

You are building a transcription service for technical podcasts.

Testing reveals that the service fails to transcribe technical terms accurately.
You need to improve the accuracy of the service.
Which five 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.
NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.

You have an Azure Cognitive Search solution and an enrichment pipeline that performs Sentiment Analysis on social media posts.
You need to define a knowledge store that will include the social media posts and the Sentiment Analysis results.
Which two fields should you include in the definition? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A.

storageContainer

B.

tables

C.

storaeeConnectionString

D.

files

E.

objects

You are building a chatbot.
You need to use the Content Moderator API to identify aggressive and sexually explicit language.

You have a chatbot that was built by using Microsoft Bot Framework and deployed to Azure.
You need to configure the bot to support voice interactions. The solution must support multiple client apps.
Which type of channel should you use?

A.

Cortana

B.

Microsoft Teams

C.

Direct Line Speech

You are building a chatbot.
You need to ensure that the bot will recognize the names of your company's products and codenames. The solution must minimize development effort. Which Azure Cognitive Service for Language service should you include in the solution?

 

A.

custom text classification

B.

entity linking

C.

custom Named Entity Recognition (NER)

D.

key phrase extraction

A1 You have an Azure OpenA1 resource named AH that hosts three deployments of the GPT 3.5 model. Each deployment is optimized for a unique workload.
You plan to deploy three apps. Each app will access AM by using the REST API and will use the deployment that was optimized for the apps intended workload.
You need to provide each app with access to AH and the appropriate deployment. The solution must ensure that only the apps can access AM.
What should you use to provide access to AM. and what should each app use to connect to its appropriate deployment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

You have a mobile app that manages printed forms.
You need the app to send images of the forms directly to Forms Recognizer to extract relevant information. For compliance reasons, the image files must not be stored in the cloud.
In which format should you send the images to the Form Recognizer API endpoint?

A.

raw image binary

B.

form URL encoded

C.

JSON

You build a chatbot that uses the Azure OpenAI GPT 3.5 model.
You need to improve the quality of the responses from the chatbot. The solution must minimize development effort.
What are two ways to achieve the goal? Each correct answer presents a complete solution.
NOTE: Each correct answer is worth one point.

A.

Fine-tune the model.

B.

Provide grounding content.

C.

Add sample request/response pairs.

D.

Retrain the language model by using your own data.

E.

Train a custom large language model (LLM).