Braindump2go Free Exam Dumps with PDF and VCE Collection
https://www.mcitpdump.com/july-2023free-offer-braindump2go-ai-900-vce-for-instant-downloadingq119-q150.html
Export date: Thu Nov 21 8:53:29 2024 / +0000 GMT

[July-2023]Free Offer Braindump2go AI-900 VCE for Instant Downloading[Q119-Q150]


July/2023 Latest Braindump2go AI-900 Exam Dumps with PDF and VCE Free Updated Today! Following are some new Braindump2go AI-900 Real Exam Questions!

QUESTION 119
In which two scenarios can you use a speech synthesis solution? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

A. an automated voice that reads back a credit card number entered into a telephone by using a numeric keypad
B. generating live captions for a news broadcast
C. extracting key phrases from the audio recording of a meeting
D. an AI character in a computer game that speaks audibly to a player

Answer: AD
Explanation:
Azure Text to Speech is a Speech service feature that converts text to lifelike speech.
Incorrect Answers:
C: Extracting key phrases is not speech synthesis.
Reference:
https://azure.microsoft.com/en-in/services/cognitive-services/text-to-speech/ 1

QUESTION 120
Drag and Drop Question
You need to scan the news for articles about your customers and alert employees when there is a negative article. Positive articles must be added to a press book.
Which natural language processing tasks should you use to complete the process? To answer, drag the appropriate tasks to the correct locations. Each task 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:
Box 1: Entity recognition
the Named Entity Recognition module in Machine Learning Studio (classic), to identify the names of things, such as people, companies, or locations in a column of text.
Named entity recognition is an important area of research in machine learning and natural language processing (NLP), because it can be used to answer many real-world questions, such as:
Which companies were mentioned in a news article?
Does a tweet contain the name of a person? Does the tweet also provide his current location?
Were specified products mentioned in complaints or reviews?
Box 2: Sentiment Analysis
The Text Analytics API's Sentiment Analysis feature provides two ways for detecting positive and negative sentiment. If you send a Sentiment Analysis request, the API will return sentiment labels (such as "negative", "neutral" and "positive") and confidence scores at the sentence and document-level.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/named-entity-recognition 2
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-sentiment-analysis 3

QUESTION 121
You need to provide content for a business chatbot that will help answer simple user queries.
What are three ways to create question and answer text by using QnA Maker? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

A. Generate the questions and answers from an existing webpage.
B. Use automated machine learning to train a model based on a file that contains the questions.
C. Manually enter the questions and answers.
D. Connect the bot to the Cortana channel and ask questions by using Cortana.
E. Import chit-chat content from a predefined data source.

Answer: ACE
Explanation:
Automatic extraction
Extract question-answer pairs from semi-structured content, including FAQ pages, support websites, excel files, SharePoint documents, product manuals and policies.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/concepts/content-types 4

QUESTION 122
You have a frequently asked questions (FAQ) PDF file.
You need to create a conversational support system based on the FAQ.
Which service should you use?

A. QnA Maker
B. Text Analytics
C. Computer Vision
D. Language Understanding (LUIS)

Answer: A
Explanation:
QnA Maker is a cloud-based API service that lets you create a conversational question-and-answer layer over your existing data. Use it to build a knowledge base by extracting questions and answers from your semi-structured content, including FAQs, manuals, and documents.
Reference:
https://azure.microsoft.com/en-us/services/cognitive-services/qna-maker/ 8 5

QUESTION 123
You need to reduce the load on telephone operators by implementing a chatbot to answer simple questions with predefined answers.
Which two AI service should you use to achieve the goal? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A. Text Analytics
B. QnA Maker
C. Azure Bot Service
D. Translator Text

Answer: BC
Explanation:
Bots are a popular way to provide support through multiple communication channels. You can use the QnA Maker service and Azure Bot Service to create a bot that answers user questions.
Reference:
https://docs.microsoft.com/en-us/learn/modules/build-faq-chatbot-qna-maker-azure-bot-service/ 6

QUESTION 124
Which two scenarios are examples of a conversational AI workload? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

A. a smart device in the home that responds to questions such as “What will the weather be like today?”
B. a website that uses a knowledge base to interactively respond to users' questions
C. assembly line machinery that autonomously inserts headlamps into cars
D. monitoring the temperature of machinery to turn on a fan when the temperature reaches a specific threshold

Answer: AB
Explanation:
Natural language processing (NLP) is used for tasks such as sentiment analysis, topic detection, language detection, key phrase extraction, and document categorization.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language-processing 7

QUESTION 125
What is the main foundation for the Personal Digital Assistant?

A. Azure Speech
B. Bot Framework
C. Computer Vision Service
D. Text Analytics
E. Automated Machine Learning

Answer: B

QUESTION 126
You need to develop a web-based AI solution for a customer support system. Users must be able to interact with a web app that will guide them to the best resource or answer.
Which service should you use?

A. Custom Vision
B. QnA Maker
C. Translator Text
D. Face

Answer: B
Explanation:
QnA Maker is a cloud-based API service that lets you create a conversational question-and-answer layer over your existing data. Use it to build a knowledge base by extracting questions and answers from your semi-structured content, including FAQs, manuals, and documents. Answer users' questions with the best answers from the QnAs in your knowledge base—automatically. Your knowledge base gets smarter, too, as it continually learns from user behavior.
Incorrect Answers:
A: Azure Custom Vision is a cognitive service that lets you build, deploy, and improve your own image classifiers. An image classifier is an AI service that applies labels (which represent classes) to images, according to their visual characteristics. Unlike the Computer Vision service, Custom Vision allows you to specify the labels to apply.
D: Azure Cognitive Services Face Detection API: At a minimum, each detected face corresponds to a faceRectangle field in the response. This set of pixel coordinates for the left, top, width, and height mark the located face. Using these coordinates, you can get the location of the face and its size. In the API response, faces are listed in size order from largest to smallest.
Reference:
https://azure.microsoft.com/en-us/services/cognitive-services/qna-maker/ 8 5

QUESTION 127
Which AI service should you use to create a bot from a frequently asked questions (FAQ) document?

A. QnA Maker
B. Language Understanding (LUIS
C. Text Analytics
D. Speech

Answer: A

QUESTION 128
Which scenario is an example of a webchat bot?

A. Determine whether reviews entered on a website for a concert are positive or negative, and then add a thumbs up or thumbs down emoji to the reviews.
B. Translate into English questions entered by customers at a kiosk so that the appropriate person can call the customers back.
C. Accept questions through email, and then route the email messages to the correct person based on the content of the message.
D. From a website interface, answer common questions about scheduled events and ticket purchases for a music festival.

Answer: D

QUESTION 129
Which two scenarios are examples of a conversational AI workload? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

A. a telephone answering service that has a pre-recorder message
B. a chatbot that provides users with the ability to find answers on a website by themselves
C. telephone voice menus to reduce the load on human resources
D. a service that creates frequently asked questions (FAQ) documents by crawling public websites

Answer: BC
Explanation:
B: A bot is an automated software program designed to perform a particular task. Think of it as a robot without a body.
C: Automated customer interaction is essential to a business of any size. In fact, 61% of consumers prefer to communicate via speech, and most of them prefer self-service. Because customer satisfaction is a priority for all businesses, self-service is a critical facet of any customer-facing communications strategy.
Incorrect Answers:
D: Early bots were comparatively simple, handling repetitive and voluminous tasks with relatively straightforward algorithmic logic. An example would be web crawlers used by search engines to automatically explore and catalog web content.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/big-data/ai-overview 9
https://docs.microsoft.com/en-us/azure/architecture/solution-ideas/articles/interactive-voice-response-bot 10

QUESTION 130
Drag and Drop Question
Match the principles of responsible AI to appropriate requirements.
To answer, drag the appropriate principles from the column on the left to its requirement on the right. Each principle 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:
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai 26 18 16 14 11
https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles 12

QUESTION 131
Drag and Drop Question
You plan to deploy an Azure Machine Learning model as a service that will be used by client applications.
Which three processes should you perform in sequence before you deploy the model? To answer, move the appropriate processes from the list of processes to the answer area and arrange them in the correct order.

Answer:

Explanation:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-ml-pipelines 13

QUESTION 132
You are building an AI-based app.
You need to ensure that the app uses the principles for responsible AI.
Which two principles should you follow? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A. Implement an Agile software development methodology
B. Implement a process of AI model validation as part of the software review process
C. Establish a risk governance committee that includes members of the legal team, members of the risk management team, and a privacy officer
D. Prevent the disclosure of the use of AI-based algorithms for automated decision making

Answer: BC
Explanation:
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai 26 18 16 14 11
https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/3-implications-responsible-ai-practical 15

QUESTION 133
Hotspot Question
Select the answer that correctly completes the sentence.

Answer:

Explanation:
Fairness is a core ethical principle that all humans aim to understand and apply. This principle is even more important when AI systems are being developed. Key checks and balances need to make sure that the system's decisions don't discriminate or run a gender, race, sexual orientation, or religion bias toward a group or individual.
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai 26 18 16 14 11

QUESTION 134
Hotspot Question
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:
The probability score of the object classification (which you can interpret as the confidence of the predicted class being correct).
https://docs.microsoft.com/en-us/learn/modules/detect-objects-images-custom-vision/1a-what-is-object-detection 17

QUESTION 135
Hotspot Question
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai 26 18 16 14 11

QUESTION 136
Hotspot Question
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:
In Azure Machine Learning, data-scaling and normalization techniques are applied to make feature engineering easier. Collectively, these techniques and this feature engineering are called featurization in automated ML experiments.
Feature selection is only about selection.
Modifying features = Feature engineering
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-configure-auto-features 19

QUESTION 137
Hotspot Question
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-label-data 20

QUESTION 138
You are authoring a Language Understanding (LUIS) application to support a music festival.
You want users to be able to ask questions about scheduled shows, such as: "Which act is playing on the main stage?"
The question "Which act is playing on the main stage?" is an example of which type of element?

A. an intent
B. an utterance
C. a domain
D. an entity

Answer: B
Explanation:
Utterances are input from the user that your app needs to interpret.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/LUIS/luis-concept-utterance 21

QUESTION 139
You build a QnA Maker bot by using a frequently asked questions (FAQ) page.
You need to add professional greetings and other responses to make the bot more user friendly.
What should you do?

A. Increase the confidence threshold of responses
B. Enable active learning
C. Create multi-turn questions
D. Add chit-chat

Answer: D
Explanation:
https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/how-to/chit-chat-knowledge-base?tabs=v1 22

QUESTION 140
You need to develop a chatbot for a website. The chatbot must answer users' questions based on the information in the following documents:
- A product troubleshooting guide in a Microsoft Word document
- A frequently asked questions (FAQ) list on a webpage
Which service should you use to process the documents?

A. Azure Bot Service
B. Language Understanding
C. Text Analytics
D. QnA Maker

Answer: D
Explanation:
https://docs.microsoft.com/en-us/azure/cognitive-services/QnAMaker/Overview/overview 23

QUESTION 141
You are building a Language Understanding model for an e-commerce business.
You need to ensure that the model detects when utterances are outside the intended scope of the model.
What should you do?

A. Test the model by using new utterances
B. Add utterances to the None intent
C. Create a prebuilt task entity
D. Create a new model

Answer: B
Explanation:
The None intent is filled with utterances that are outside of your domain.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/LUIS/luis-concept-intent 24

QUESTION 142
When you are creating a Clustering Model, what common ML algorithm are you using?

A. Multiclass Logistic Regression
B. K-means
C. Linear Regression
D. Two-Class Neural Network
E. Decision Forest Regression

Answer: B

QUESTION 143
You create a regression model with low RMSE and review the best model metrics.
Where on the Residual histogram should the most frequently occurring residual values cluster for your model?

A. 1
B. 0.5
C. 0
D. -1
E. 2
F. -0.5

Answer: C

QUESTION 144
You are creating a pipeline in Azure ML Designer. You need to add a module to execute the programming code.
What languages can you use for code execution in Azure ML Designer?

A. C++
B. Java
C. Python
D. TypeScript
E. C#
F. R
G. JavaScript

Answer: CF

QUESTION 145
You are using Text Analytics Entity Recognition API to analyze the following sentence- “After Peter met Sara at Microsoft headquarters in Paris, they visited the Eiffel tower.”
How many entities with the category “Location” should you expect in the API response?

A. 0
B. 1
C. 2
D. 3
E. 4

Answer: D
Explanation:
Named Entity Recognition (NER) is a Text Analytics service that helps identify entities in the text and group them into different entity categories, like person, organization, location, event, etc.
You should expect three recognized named entities with the category “Location” in the API response- “headquarters,” “Paris,” and “Eiffel tower.”
https://docs.microsoft.com/en-us/learn/modules/analyze-text-with-text-analytics-service/2-get-started-azure 25

QUESTION 146
The customer service of your company spends a lot of time answering the same questions. They asked you to help them to automate this process. They provided you a Microsoft Excel (*.xlsx) document with frequently asked questions and typical answers.
What service will you use to create a knowledge base from this document?

A. Azure Bot Service
B. Custom vision
C. Text Analytics
D. QnA Maker
E. LUIS

Answer: D

QUESTION 147
What markup language will you use for the control of Speech Synthesis output for your phone auto attendant?

A. HTML
B. SQL
C. SSML
D. JSON
E. TeX

Answer: C

QUESTION 148
You need to create a Web Bot using the Azure portal. You have to choose a bot template.
What are two SDK languages you can select for the bot template?

A. C++
B. Node.js
C. Python
D. C#
E. Java

Answer: BD

QUESTION 149
When you design an AI system to assess whether loans should be approved, the factors used to make the decision should be explainable.
This is an example of which Microsoft guiding principle for responsible AI?

A. transparency
B. inclusiveness
C. fairness
D. privacy and security

Answer: A
Explanation:
Achieving transparency helps the team to understand the data and algorithms used to train the model, what transformation logic was applied to the data, the final model generated, and its associated assets. This information offers insights about how the model was created, which allows it to be reproduced in a transparent way.
Reference:
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai 26 18 16 14 11
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/strategy/responsible-ai 27

QUESTION 150
You are building a tool that will process images from retail stores and identify the products of competitors.
The solution will use a custom model.
Which Azure Cognitive Services service should you use?

A. Custom Vision
B. Form Recognizer
C. Face
D. Computer Vision

Answer: A
Explanation:
Azure Custom Vision is an image recognition service that lets you build, deploy, and improve your own image identifier models. An image identifier applies labels (which represent classifications or objects) to images, according to their detected visual characteristics. Unlike the Computer Vision service, Custom Vision allows you to specify your own labels and train custom models to detect them.


Resources From:

1.2023 Latest Braindump2go AI-900 Exam Dumps (PDF & VCE) Free Share:
https://www.braindump2go.com/ai-900.html

2.2023 Latest Braindump2go AI-900 PDF and AI-900 VCE Dumps Free Share:
https://drive.google.com/drive/folders/1VMADE4rTtp2SjgbY_rnCokxgjUS7cH28?usp=sharing

3.2023 Free Braindump2go AI-900 Exam Questions Download:
https://www.braindump2go.com/free-online-pdf/AI-900-PDF-Dumps(119-150).pdf

Free Resources from Braindump2go,We Devoted to Helping You 100% Pass All Exams!

Links:
  1. https://azure.microsoft.com/en-in/services/cogniti ve-services/text-to-speech/
  2. https://docs.microsoft.com/en-us/azure/machine-lea rning/studio-module-reference/named-entity-recogni tion
  3. https://docs.microsoft.com/en-us/azure/cognitive-s ervices/text-analytics/how-tos/text-analytics-how- to-sentiment-analysis
  4. https://docs.microsoft.com/en-us/azure/cognitive-s ervices/qnamaker/concepts/content-types
  5. https://azure.microsoft.com/en-us/services/cogniti ve-services/qna-maker/
  6. https://docs.microsoft.com/en-us/learn/modules/bui ld-faq-chatbot-qna-maker-azure-bot-service/
  7. https://docs.microsoft.com/en-us/azure/architectur e/data-guide/technology-choices/natural-language-p rocessing
  8. https://azure.microsoft.com/en-us/services/cogniti ve-services/qna-maker/
  9. https://docs.microsoft.com/en-us/azure/architectur e/data-guide/big-data/ai-overview
  10. https://docs.microsoft.com/en-us/azure/architectur e/solution-ideas/articles/interactive-voice-respon se-bot
  11. https://docs.microsoft.com/en-us/azure/cloud-adopt ion-framework/innovate/best-practices/trusted-ai
  12. https://docs.microsoft.com/en-us/learn/modules/res ponsible-ai-principles/4-guiding-principles
  13. https://docs.microsoft.com/en-us/azure/machine-lea rning/concept-ml-pipelines
  14. https://docs.microsoft.com/en-us/azure/cloud-adopt ion-framework/innovate/best-practices/trusted-ai
  15. https://docs.microsoft.com/en-us/learn/modules/res ponsible-ai-principles/3-implications-responsible- ai-practical
  16. https://docs.microsoft.com/en-us/azure/cloud-adopt ion-framework/innovate/best-practices/trusted-ai
  17. https://docs.microsoft.com/en-us/learn/modules/det ect-objects-images-custom-vision/1a-what-is-object -detection
  18. https://docs.microsoft.com/en-us/azure/cloud-adopt ion-framework/innovate/best-practices/trusted-ai
  19. https://docs.microsoft.com/en-us/azure/machine-lea rning/how-to-configure-auto-features
  20. https://docs.microsoft.com/en-us/azure/machine-lea rning/how-to-label-data
  21. https://docs.microsoft.com/en-us/azure/cognitive-s ervices/LUIS/luis-concept-utterance
  22. https://docs.microsoft.com/en-us/azure/cognitive-s ervices/qnamaker/how-to/chit-chat-knowledge-base?t abs=v1
  23. https://docs.microsoft.com/en-us/azure/cognitive-s ervices/QnAMaker/Overview/overview
  24. https://docs.microsoft.com/en-us/azure/cognitive-s ervices/LUIS/luis-concept-intent
  25. https://docs.microsoft.com/en-us/learn/modules/ana lyze-text-with-text-analytics-service/2-get-starte d-azure
  26. https://docs.microsoft.com/en-us/azure/cloud-adopt ion-framework/innovate/best-practices/trusted-ai
  27. https://docs.microsoft.com/en-us/azure/cloud-adopt ion-framework/strategy/responsible-ai
Post date: 2023-07-20 06:28:14
Post date GMT: 2023-07-20 06:28:14

Post modified date: 2023-07-20 06:28:14
Post modified date GMT: 2023-07-20 06:28:14

Export date: Thu Nov 21 8:53:29 2024 / +0000 GMT
This page was exported from Braindump2go Free Exam Dumps with PDF and VCE Collection [ https://www.mcitpdump.com ]
Export of Post and Page has been powered by [ Universal Post Manager ] plugin from www.ProfProjects.com