Valid AI-102 Dumps shared by PassLeader for Helping Passing AI-102 Exam! PassLeader now offer the newest AI-102 VCE dumps and AI-102 PDF dumps, the PassLeader AI-102 exam questions have been updated and ANSWERS have been corrected, get the newest PassLeader AI-102 dumps with VCE and PDF here: https://www.passleader.com/ai-102.html (106 Q&As Dumps –> 124 Q&As Dumps –> 284 Q&As Dumps –> 351 Q&As Dumps)
BTW, DOWNLOAD part of PassLeader AI-102 dumps from Cloud Storage: https://drive.google.com/drive/folders/1DtLmjMoVidk2fNQdkrtdSFHqFqxHU7re
NEW QUESTION 91
You have an Azure Cognitive Search service. During the past 12 months, query volume steadily increased. You discover that some search query requests to the Cognitive Search service are being throttled. You need to reduce the likelihood that search query requests are throttled.
Solution: You add indexes.
Does this meet the goal?
A. Yes
B. No
Answer: B
Explanation:
Instead, you could migrate to a Cognitive Search service that uses a higher tier. Note: A simple fix to most throttling issues is to throw more resources at the search service (typically replicas for query-based throttling, or partitions for indexing-based throttling). However, increasing replicas or partitions adds cost, which is why it is important to know the reason why throttling is occurring at all.
https://docs.microsoft.com/en-us/azure/search/search-performance-analysis
NEW QUESTION 92
You have an Azure Cognitive Search service. During the past 12 months, query volume steadily increased. You discover that some search query requests to the Cognitive Search service are being throttled. You need to reduce the likelihood that search query requests are throttled.
Solution: You migrate to a Cognitive Search service that uses a higher tier.
Does this meet the goal?
A. Yes
B. No
Answer: A
Explanation:
A simple fix to most throttling issues is to throw more resources at the search service (typically replicas for query-based throttling, or partitions for indexing-based throttling). However, increasing replicas or partitions adds cost, which is why it is important to know the reason why throttling is occurring at all.
https://docs.microsoft.com/en-us/azure/search/search-performance-analysis
NEW QUESTION 93
You have receipts that are accessible from a URL. You need to extract data from the receipts by using Form Recognizer and the SDK. The solution must use a prebuilt model. Which client and method should you use?
A. the FormRecognizerClient client and the StartRecognizeContentFromUri method
B. the FormTrainingClient client and the StartRecognizeContentFromUri method
C. the FormRecognizerClient client and the StartRecognizeReceiptsFromUri method
D. the FormTrainingClient client and the StartRecognizeReceiptsFromUri method
Answer: D
Explanation:
To analyze receipts from a URL, use the StartRecognizeReceiptsFromUri method.
https://docs.microsoft.com/en-us/azure/applied-ai-services/form-recognizer/quickstarts/client-library
NEW QUESTION 94
You have a collection of 50,000 scanned documents that contain text. You plan to make the text available through Azure Cognitive Search. You need to configure an enrichment pipeline to perform optical character recognition (OCR) and text analytics. The solution must minimize costs. What should you attach to the skillset?
A. a new Computer Vision resource
B. a free (Limited enrichments) Cognitive Services resource
C. an Azure Machine Learning pipeline
D. a new Cognitive Services resource that uses the S0 pricing tier
Answer: A
Explanation:
The Computer Vision API uses text recognition APIs to extract and recognize text information from images. Read uses the latest recognition models, and is optimized for large, text-heavy documents and noisy images.
https://docs.microsoft.com/en-us/azure/architecture/solution-ideas/articles/cognitive-search-with-skillsets
NEW QUESTION 95
You are training a Language Understanding model for a user support system. You create the first intent named GetContactDetails and add 200 examples. You need to decrease the likelihood of a false positive. What should you do?
A. Enable active learning.
B. Add a machine learned entity.
C. Add additional examples to the GetContactDetails intent.
D. Add examples to the None intent.
Answer: A
Explanation:
Active learning is a technique of machine learning in which the machine learned model is used to identify informative new examples to label. In LUIS, active learning refers to adding utterances from the endpoint traffic whose current predictions are unclear to improve your model.
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-glossary
NEW QUESTION 96
You are developing an application that will use Azure Cognitive Search for internal documents. You need to implement document-level filtering for Azure Cognitive Search. Which three actions should you include in the solution? (Each correct answer presents part of the solution. Choose three.)
A. Send Azure AD access tokens with the search request.
B. Retrieve all the groups.
C. Retrieve the group memberships of the user.
D. Add allowed groups to each index entry.
E. Create one index per group.
F. Supply the groups as a filter for the search requests.
Answer: CDF
Explanation:
Your documents must include a field specifying which groups have access. This information becomes the filter criteria against which documents are selected or rejected from the result set returned to the issuer.
D: A query request targets the documents collection of a single index on a search service.
CF: In order to trim documents based on group_ids access, you should issue a search query with a group_ids/any(g:search.in(g, ‘group_id1, group_id2,…’)) filter, where ‘group_id1, group_id2,…’ are the groups to which the search request issuer belongs.
https://docs.microsoft.com/en-us/azure/search/search-security-trimming-for-azure-search
NEW QUESTION 97
You are building a chatbot by using the Microsoft Bot Framework Composer as shown in the exhibit:
The chatbot contains a dialog named GetUserDetails. GetUserDetails contains a TextInput control that prompts users for their name. The user input will be stored in a property named name. You need to ensure that you can dispose of the property when the last active dialog ends. Which scope should you assign to name?
A. dialog
B. user
C. turn
D. conversation
Answer: A
Explanation:
The dialog scope associates properties with the active dialog. Properties in the dialog scope are retained until the dialog ends.
Incorrect:
Not B: The user scope associates properties with the current user. Properties in the user scope do not expire. These properties are in scope while the bot is processing an activity associated with the user.
Not C: The turn scope associates properties with the current turn. Properties in the turn scope expire at the end of the turn.
Not D: The conversation scope associates properties with the current conversation. Properties in the conversation scope have a lifetime of the conversation itself. These properties are in scope while the bot is processing an activity associated with the conversation (for example, multiple users together in a Microsoft Teams channel).
https://docs.microsoft.com/en-us/composer/concept-memory?tabs=v2x
NEW QUESTION 98
You need to enable speech capabilities for a chatbot. Which three actions should you perform? (Each correct answer presents part of the solution. Choose three.)
A. Enable WebSockets for the chatbot app.
B. Create a Speech service.
C. Register a Direct Line Speech channel.
D. Register a Cortana channel.
E. Enable CORS for the chatbot app.
F. Create a Language Understanding service.
Answer: ABC
Explanation:
You can use the Speech service to voice-enable a chat bot. The Direct Line Speech channel uses the text-to-speech service, which has neural and standard voices. You’ll need to make a small configuration change so that your bot can communicate with the Direct Line Speech channel using web sockets.
https://docs.microsoft.com/en-us/azure/cognitive-services/speech-service/tutorial-voice-enable-your-bot-speech-sdk
NEW QUESTION 99
HotSpot
You run the following command:
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
Answer:
Explanation:
Box 1: Yes. http://localhost:5000/status. Also requested with GET, this verifies if the api-key used to start the container is valid without causing an endpoint query.
Box 2: Yes. The command saves container and LUIS logs to output mount at C:\output, located on container host.
Box 3: Yes. http://localhost:5000/swagger. The container provides a full set of documentation for the endpoints and a Try it out feature. With this feature, you can enter your settings into a web-based HTML form and make the query without having to write any code. After the query returns, an example CURL command is provided to demonstrate the HTTP headers and body format that’s required.
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-container-howto
NEW QUESTION 100
HotSpot
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.)
Answer:
Explanation:
Box 1: Classification. An object detection project is for detecting which objects, if any, from a set of candidates are present in an image.
Box 2: Multiclass. A multiclass classification project is for classifying images into a set of tags, or target labels. An image can be assigned to one tag only. A multilabel classification project is similar, but each image can have multiple tags assigned to it.
Box 3: General. Optimized for a broad range of image classification tasks. If none of the other specific domains are appropriate, or if you’re unsure of which domain to choose, select one of the General domains.
https://cran.r-project.org/web/packages/AzureVision/vignettes/customvision.html
NEW QUESTION 101
Drag and Drop
You are building a Language Understanding model for purchasing tickets. You have the following utterance for an intent named PurchaseAndSendTickets. Purchase [2 audit business] tickets to [Paris] [next Monday] and send tickets to [[email protected]]. You need to select the entity types. The solution must use built-in entity types to minimize training data whenever possible. Which entity type should you use for each label? (To answer, drag the appropriate entity types to the correct labels. Each entity type 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.)
Answer:
Explanation:
Box 1: GeographyV2. The prebuilt geographyV2 entity detects places. Because this entity is already trained, you do not need to add example utterances containing GeographyV2 to the application intents.
Box 2: Email. Email prebuilt entity for a LUIS app: Email extraction includes the entire email address from an utterance. Because this entity is already trained, you do not need to add example utterances containing email to the application intents.
Box 3: Machine learned. The machine-learning entity is the preferred entity for building LUIS applications.
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-reference-prebuilt-geographyv2
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-reference-prebuilt-email
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/reference-entity-machine-learned-entity
NEW QUESTION 102
Drag and Drop
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:
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.
https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/how-to/improve-knowledge-base
NEW QUESTION 103
……
Get the newest PassLeader AI-102 VCE dumps here: https://www.passleader.com/ai-102.html (106 Q&As Dumps –> 124 Q&As Dumps –> 284 Q&As Dumps –> 351 Q&As Dumps)
And, DOWNLOAD the newest PassLeader AI-102 PDF dumps from Cloud Storage for free: https://drive.google.com/drive/folders/1DtLmjMoVidk2fNQdkrtdSFHqFqxHU7re