[Oct-2023] Free AI-102 Exam Dumps to Improve Exam Score
2023 Realistic AI-102 Dumps Exam Tips Test Pdf Exam Material
Prerequisites
Before enrolling in the process of taking the AI-102 exams, candidates should be skilled in implementing Python and C#, using APIs and SDKs based on REST to create natural language processing solutions, computer vision solutions, and knowledge mining and communicative AI solutions based on Azure. In addition, such specialists should be knowledgeable of the elements that create the Azure AI portfolio as well as the data storage options. To add more, they should be able to implement AI principles appropriately.
To be eligible for this certification, you should have a good understanding of Azure fundamentals, including Azure Virtual Machines, Azure Storage, and Azure Virtual Networks. You should also have experience with machine learning models, including deep learning and natural language processing. Additionally, you should have knowledge of programming languages such as Python, R, and Scala.
NEW QUESTION # 126
You have a Computer Vision resource named contoso1 that is hosted in the West US Azure region.
You need to use contoso1 to make a different size of a product photo by using the smart cropping feature.
How should you complete the API URL? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://westus.dev.cognitive.microsoft.com/docs/services/computer-vision-v3-2/operations/56f91f2e778daf14a499f21b
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-generating-thumbnails#examples
NEW QUESTION # 127
You have a chatbot that uses a QnA Maker application.
You enable active learning for the knowledge base used by the QnA Maker application.
You need to integrate user input into 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.
Answer:
Explanation:
Explanation
Graphical user interface, application Description automatically generated
Step 1: For the knowledge base, select Show active learning suggestions.
In order to see the suggested questions, on the Edit knowledge base page, select View Options, then select Show active learning suggestions.
Step 2: Approve and reject suggestions.
Each QnA pair suggests the new question alternatives with a check mark, , to accept the question or an x to reject the suggestions. Select the check mark to add the question.
Step 3: Save and train the knowledge base.
Select Save and Train to save the changes to the knowledge base.
Step 4: Publish the knowledge base.
Select Publish to allow the changes to be available from the GenerateAnswer API.
When 5 or more similar queries are clustered, every 30 minutes, QnA Maker suggests the alternate questions for you to accept or reject.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/how-to/improve-knowledge-base
NEW QUESTION # 128
Your company uses an Azure Cognitive Services solution to detect faces in uploaded images. The method to detect the faces uses the following code.
You discover that the solution frequently fails to detect faces in blurred images and in images that contain sideways faces.
- A. Use the Computer Vision service instead of the Face service.
- B. Use the Identify method instead of the Detect method.
- C. Change the detection model.You need to increase the likelihood that the solution can detect faces in blurred images and images that contain sideways faces.What should you do?
- D. Use a different version of the Face API.
Answer: C
Explanation:
Explanation
Evaluate different models.
The best way to compare the performances of the detection models is to use them on a sample dataset. We recommend calling the Face - Detect API on a variety of images, especially images of many faces or of faces that are difficult to see, using each detection model. Pay attention to the number of faces that each model returns.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/specify-detection-model
NEW QUESTION # 129
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation
NEW QUESTION # 130
You develop an app in O named App1 that performs speech-to-speech translation.
You need to configure App1 to translate English to German.
How should you complete the speechTransiationConf ig object? 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.
Answer:
Explanation:
Explanation
NEW QUESTION # 131
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.
Answer:
Explanation:
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
NEW QUESTION # 132
You have 100 chatbots that each has its own Language Understanding model.
Frequently, you must add the same phrases to each model.
You need to programmatically update the Language Understanding models to include the new phrases.
How should you complete the code? 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.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/client-libraries-rest-api
NEW QUESTION # 133
You are building a chatbot.
You need to configure the chatbot to query a knowledge base.
Which dialog class should you use?
- A. AdaptiveDialog
- B. SkillDialog
- C. QnAMakerDialog
- D. ComponentDialog
Answer: C
NEW QUESTION # 134
You are building a model that will be used in an iOS app.
You have images of cats and dogs. Each image contains either a cat or a dog.
You need to use the Custom Vision service to detect whether the images is of a cat or a dog.
How should you configure the project in the Custom Vision portal? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://cran.r-project.org/web/packages/AzureVision/vignettes/customvision.html
NEW QUESTION # 135
You are developing a streaming Speech to Text solution that will use the Speech SDK and MP3 encoding.
You need to develop a method to convert speech to text for streaming MP3 data.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/speech-service/how-to-use-codec-compressed-audio-input-streams?tabs=debian&pivots=programming-language-csharp
NEW QUESTION # 136
You are developing a call to the Face API. The call must find similar faces from an existing list named employeefaces. The employeefaces list contains 60,000 images.
How should you complete the body of the HTTP 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.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/rest/api/faceapi/face/findsimilar
NEW QUESTION # 137
You are building an app that will share user images.
You need to configure the app to perform the following actions when a user uploads an image:
* Categorize the image as either a photograph or a drawing.
* Generate a caption for the image.
The solution must minimize development effort.
Which two services should you include in the solution? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
- A. object detection in Computer Vision
- B. content tags in Computer Vision
- C. image type detection in Computer Vison
- D. image classification in Custom Vision
- E. image descriptions in Computer Vision
Answer: C,E
Explanation:
According to the Microsoft documentation, Computer Vision is a cloud-based service that provides developers with access to advanced algorithms for processing images and returning information. By uploading an image or specifying an image URL, Computer Vision algorithms can analyze visual content in different ways based on inputs and user choices.
According to the Microsoft documentation, image type detection is one of the features of Computer Vision that can categorize an image as either a photograph or a drawing. You can use the image type detection feature by calling the Analyze Image API with the visualFeatures parameter set to ImageType.
The API will return a JSON response with an imageType field that indicates whether the image is a photo or a clipart.
According to the Microsoft documentation, image descriptions is another feature of Computer Vision that can generate a caption for an image. You can use the image descriptions feature by calling the Analyze Image API with the visualFeatures parameter set to Description. The API will return a JSON response with a description field that contains a list of captions for the image, each with a confidence score.
Therefore, by using these two features of Computer Vision, you can achieve your app requirements with minimal development effort. You don't need to use any other services, such as object detection, content tags, or Custom Vision, which are designed for different purposes.
NEW QUESTION # 138
You use the Custom Vision service to build a classifier.
After training is complete, you need to evaluate the classifier.
Which two metrics are available for review? Each correct answer presents a complete solution. (Choose two.) NOTE: Each correct selection is worth one point.
- A. area under the curve (AUC)
- B. recall
- C. precision
- D. F-score
- E. weighted accuracy
Answer: B,C
Explanation:
Explanation
Custom Vision provides three metrics regarding the performance of your model: precision, recall, and AP.
Reference:
https://www.tallan.com/blog/2020/05/19/azure-custom-vision/
NEW QUESTION # 139
You have an existing Azure Cognitive Search service.
You have an Azure Blob storage account that contains millions of scanned documents stored as images and PDFs.
You need to make the scanned documents available to search as quickly as possible. What should you do?
- A. Create a Cognitive Search service for each type of document.
- B. Split the data into multiple blob containers. Create an indexer for each container. Increase the search units. Within each indexer definition, schedule a sequential execution pattern.
- C. Split the data into multiple blob containers. Create a Cognitive Search service for each container. Within each indexer definition, schedule the same runtime execution pattern.
- D. Split the data into multiple virtual folders. Create an indexer for each folder. Increase the search units.Within each indexer definition, schedule the same runtime execution pattern.
Answer: D
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/search/search-howto-indexing-azure-blob-storage
NEW QUESTION # 140
You build a conversational bot named bot1.
You need to configure the bot to use a QnA Maker application.
From the Azure Portal, where can you find the information required by bot1 to connect to the QnA Maker application?
- A. Keys and Endpoint
- B. Properties
- C. Access control (IAM)
- D. Identity
Answer: A
Explanation:
Topic 1, Wide World Importers
Existing Environment
A company named Wide World Importers is developing an e-commerce platform.
You are working with a solutions architect to design and implement the features of the e-commerce platform. The platform will use microservices and a serverless environment built on Azure.
Wide World Importers has a customer base that includes English, Spanish, and Portuguese speakers.
Applications
Wide World Importers has an App Service plan that contains the web apps shown in the following table.
Azure Resources
You have the following resources:
An Azure Active Directory (Azure AD) tenant
The tenant supports internal authentication.
All employees belong to a group named AllUsers.
Senior managers belong to a group named LeadershipTeam.
An Azure Functions resource
A function app posts to Azure Event Grid when stock levels of a product change between OK, Low Stock, and Out of Stock. The function app uses the Azure Cosmos DB change feed.
An Azure Cosmos DB account
The account uses the Core (SQL) API.
The account stores data for the Product Management app and the Inventory Tracking app.
An Azure Storage account
The account contains blob containers for assets related to products.
The assets include images, videos, and PDFs.
An Azure Cognitive Services resource named wwics
A Video Indexer resource named wwivi
Requirements
Business Goals
Wide World Importers wants to leverage AI technologies to differentiate itself from its competitors.
Planned Changes
Wide World Importers plans to start the following projects:
A product creation project: Help employees create accessible and multilingual product entries, while expediting product entry creation.
A smart e-commerce project: Implement an Azure Cognitive Search solution to display products for customers to browse.
A shopping on-the-go project: Build a chatbot that can be integrated into smart speakers to support customers.
Business Requirements
Wide World Importers identifies the following business requirements for all the projects:
Provide a multilingual customer experience that supports English, Spanish, and Portuguese.
Whenever possible, scale based on transaction volumes to ensure consistent performance.
Minimize costs.
Governance and Security Requirements
Wide World Importers identifies the following governance and security requirements:
Data storage and processing must occur in datacenters located in the United States.
Azure Cognitive Services must be inaccessible directly from the internet.
Accessibility Requirements
Wide World Importers identifies the following accessibility requirements:
All images must have relevant alt text.
All videos must have transcripts that are associated to the video and included in product descriptions.
Product descriptions, transcripts, and all text must be available in English, Spanish, and Portuguese.
Product Creation Requirements
Wide World Importers identifies the following requirements for improving the Product Management app:
Minimize how long it takes for employees to create products and add assets.
Remove the need for manual translations.
Smart E-Commerce Requirements
Wide World Importers identifies the following requirements for the smart e-commerce project:
Ensure that the Cognitive Search solution meets a Service Level Agreement (SLA) of 99.9% availability for searches and index writes.
Provide users with the ability to search insight gained from the images, manuals, and videos associated with the products.
Support autocompletion and autosuggestion based on all product name variants.
Store all raw insight data that was generated, so the data can be processed later.
Update the stock level field in the product index immediately upon changes.
Update the product index hourly.
Shopping On-the-Go Requirements
Wide World Importers identifies the following requirements for the shopping on-the-go chatbot:
Answer common questions.
Support interactions in English, Spanish, and Portuguese.
Replace an existing FAQ process so that all Q&A is managed from a central location.
Provide all employees with the ability to edit Q&As. Only senior managers must be able to publish updates.
Support purchases by providing information about relevant products to customers. Product displays must include images and warnings when stock levels are low or out of stock.
Product JSON Sample
You have the following JSON sample for a product.
NEW QUESTION # 141
You build a QnA Maker resource to meet the chatbot requirements.
Which RBAC role should you assign to each group? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/concepts/role-based-access-control
NEW QUESTION # 142
You are developing the chatbot.
You create the following components:
* A QnA Maker resource
* A chatbot by using the Azure Bot Framework SDK
You need to add an additional component to meet the technical requirements and the chatbot requirements.
What should you add?
- A. Dispatch
- B. chatdown
- C. Microsoft Translator
- D. Language Understanding
Answer: A
Explanation:
Explanation
Scenario: All planned projects must support English, French, and Portuguese.
If a bot uses multiple LUIS models and QnA Maker knowledge bases (knowledge bases), you can use the Dispatch tool to determine which LUIS model or QnA Maker knowledge base best matches the user input.
The dispatch tool does this by creating a single LUIS app to route user input to the correct model.
Reference:
https://docs.microsoft.com/en-us/azure/bot-service/bot-builder-tutorial-dispatch
NEW QUESTION # 143
You are building a natural language model.
You need to enable active learning.
What should you do?
- A. Enable sentiment analysis.
- B. Enable speech priming.
- C. Add show-all-intents=true to the prediction endpoint query.
- D. Add log=true to the prediction endpoint query.
Answer: D
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-how-to-review-endpoint-utterances#log-user-
NEW QUESTION # 144
You are developing the smart e-commerce project.
You need to implement autocompletion as part of the Cognitive Search solution.
Which three actions should you perform? Each correct answer presents part of the solution. (Choose three.) NOTE: Each correct selection is worth one point.
- A. Add a suggester that has the three product name fields as source fields.
- B. Make API queries to the autocomplete endpoint and include suggesterName in the body.
- C. Set the searchAnalyzer property for the three product name variants.
- D. Make API queries to the search endpoint and include the product name fields in the searchFields query parameter.
- E. Add a suggester for each of the three product name fields.
- F. Set the analyzer property for the three product name variants.
Answer: A,B,F
Explanation:
Explanation
Scenario: Support autocompletion and autosuggestion based on all product name variants.
A: Call a suggester-enabled query, in the form of a Suggestion request or Autocomplete request, using an API.
API usage is illustrated in the following call to the Autocomplete REST API.
POST /indexes/myxboxgames/docs/autocomplete?search&api-version=2020-06-30
{
"search": "minecraf",
"suggesterName": "sg"
}
B: In Azure Cognitive Search, typeahead or "search-as-you-type" is enabled through a suggester. A suggester provides a list of fields that undergo additional tokenization, generating prefix sequences to support matches on partial terms. For example, a suggester that includes a City field with a value for "Seattle" will have prefix combinations of "sea", "seat", "seatt", and "seattl" to support typeahead.
F: Use the default standard Lucene analyzer ("analyzer": null) or a language analyzer (for example, "analyzer":
"en.Microsoft") on the field.
Reference:
https://docs.microsoft.com/en-us/azure/search/index-add-suggesters
NEW QUESTION # 145
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