[Dec-2021] Verified Microsoft AI-900 Bundle Real Exam Dumps PDF [Q40-Q63]

[Dec-2021] Verified Microsoft AI-900 Bundle Real Exam Dumps PDF

AI-900 Dumps PDF New [2021] Ultimate Study Guide

Explain Computer Vision Workloads Features on Azure (15-20%)

Here, the following skills will be measured:

Identify the basic types of Computer Vision Solution – The candidates need to understand and be able to identify a range of features. They include image classification solutions, semantic segmentation solutions, object detection solutions, and optical attributes recognition solutions. It also covers the attributes of facial recognition, facial analysis, and facial detection solutions.
Identify Azure services & tools for Computer Vision Projects – This section requires that the learners identify different capabilities of Computer Vision service, Face service, Customer Vision service, and Form Recognizer service.

Target Audience

The Microsoft AI-900 exam is designed for those individuals who have little to no experience in the world of IT. It is aimed at the students with both non-technical and technical backgrounds. They have basic programming experience and knowledge. However, they are not required to have software engineering or data science experience.

NEW QUESTION 40
For a machine learning progress, how should you split data for training and evaluation?

A. Randomly split the data into columns for training and columns for evaluation.
B. Use features for training and labels for evaluation.
C. Randomly split the data into rows for training and rows for evaluation.
D. Use labels for training and features for evaluation.

Answer: C

Explanation:
Explanation
https://docs.microsoft.com/en-us/azure/machine-learning/algorithm-module-reference/split-data

NEW QUESTION 41
Which AI service should you use to create a bot from a frequently asked questions (FAQ) document?

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

Answer: A

Explanation:
Section: Describe features of conversational AI workloads on Azure
Explanation/Reference:

NEW QUESTION 42
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation

Box 1: No
Box 2: Yes
Box 3: Yes
Anomaly detection encompasses many important tasks in machine learning:
Identifying transactions that are potentially fraudulent.
Learning patterns that indicate that a network intrusion has occurred.
Finding abnormal clusters of patients.
Checking values entered into a system.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/anomaly-detection

NEW QUESTION 43
Which AI service can you use to interpret the meaning of a user input such as "Call me back later?"

A. Translator Text
B. Text Analytics
C. Speech
D. Language Understanding (LUIS)

Answer: B

Explanation:
Text Analytics is an AI service that uncovers insights such as sentiment, entities, and key phrases in unstructured text.
Incorrect Answers:
D: Language Understanding (LUIS) is a cloud-based API service, not an AI service, that applies custom machine-learning intelligence to a user's conversational, natural language text to predict overall meaning, and pull out relevant, detailed information.
Reference:
https://azure.microsoft.com/en-us/services/cognitive-services/text-analytics/
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/what-is-luis

NEW QUESTION 44
You have a dataset that contains information about taxi journeys that occurred during a given period.
You need to train a model to predict the fare of a taxi journey. What should you use as a feature?

A. the trip ID of individual taxi journeys
B. the trip distance of individual taxi journeys
C. the number of taxi journeys in the dataset
D. the fare of individual taxi journeys

Answer: B

Explanation:
The label is the column you want to predict. The identified Featuresare the inputs you give the model to predict the Label.
Example:
The provided data set contains the following columns:
passenger_count: The number of passengers on the trip is a feature.
trip_time_in_secs: The amount of time the trip took. You want to predict the fare of the trip before the trip is completed. At that moment, you don't know how long the trip would take. Thus, the trip time is not a feature and you'll exclude this column from the model.
trip_distance: The distance of the trip is a feature.
payment_type: The payment method (cash or credit card) is a feature. fare_amount: The total taxi fare paid is the label.
Reference:
https://docs.microsoft.com/en-us/dotnet/machine-learning/tutorials/predict-prices

NEW QUESTION 45
You need to determine the location of cars in an image so that you can estimate the distance between the cars.
Which type of computer vision should you use?

A. image classification
B. optical character recognition (OCR)
C. face detection
D. object detection

Answer: D

Explanation:
Section: Describe features of computer vision workloads on Azure
Explanation:
Object detection is similar to tagging, but the API returns the bounding box coordinates (in pixels) for each object found. For example, if an image contains a dog, cat and person, the Detect operation will list those objects together with their coordinates in the image. You can use this functionality to process the relationships between the objects in an image. It also lets you determine whether there are multiple instances of the same tag in an image.
The Detect API applies tags based on the objects or living things identified in the image. There is currently no formal relationship between the tagging taxonomy and the object detection taxonomy. At a conceptual level, the Detect API only finds objects and living things, while the Tag API can also include contextual terms like
"indoor", which can't be localized with bounding boxes.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-object-detection

NEW QUESTION 46
Which type of machine learning should you use to predict the number of gift cards that will be sold next month?

A. classification
B. clustering
C. regression

Answer: B

Explanation:
Clustering, in machine learning, is a method of grouping data points into similar clusters. It is also called segmentation.
Over the years, many clustering algorithms have been developed. Almost all clustering algorithms use the features of individual items to find similar items. For example, you might apply clustering to find similar people by demographics. You might use clustering with text analysis to group sentences with similar topics or sentiment.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/machine-learning-initialize- model-clustering

NEW QUESTION 47
You are building an AI system.
Which task should you include to ensure that the service meets the Microsoft transparency principle for responsible AI?

A. Provide documentation to help developers debug code.
B. Enable autoscaling to ensure that a service scales based on demand.
C. Ensure that all visuals have an associated text that can be read by a screen reader.
D. Ensure that a training dataset is representative of the population.

Answer: A

Explanation:
Reference:
https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles

NEW QUESTION 48
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:

Explanation

Reference:
https://azure.microsoft.com/en-gb/services/cognitive-services/speech-to-text/#features

NEW QUESTION 49
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/get-started-build-detector

NEW QUESTION 50
What are two tasks that can be performed by using computer vision? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

A. Extract key phrases.
B. Detect brands in an image.
C. Translate text between languages.
D. Detect the color scheme in an image
E. Predict stock prices.

Answer: A,B

Explanation:
B: Azure's Computer Vision service gives you access to advanced algorithms that process images and return information based on the visual features you're interested in. For example, Computer Vision can determine whether an image contains adult content, find specific brands or objects, or find human faces.
E: Computer Vision includes Optical Character Recognition (OCR) capabilities. You can use the new Read API to extract printed and handwritten text from images and documents. It uses the latest models and works with text on a variety of surfaces and backgrounds. These include receipts, posters, business cards, letters, and whiteboards. The two OCR APIs support extracting printed text in several languages.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/overview

NEW QUESTION 51
Match the facial recognition tasks to the appropriate questions.
To answer, drag the appropriate task from the column on the left to its question on the right. Each task may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation

Box 1: verification
Face verification: Check the likelihood that two faces belong to the same person and receive a confidence score.
Box 2: similarity
Box 3: Grouping
Box 4: identification
Face detection: Detect one or more human faces along with attributes such as: age, emotion, pose, smile, and facial hair, including 27 landmarks for each face in the image.
Reference:
https://azure.microsoft.com/en-us/services/cognitive-services/face/#features

NEW QUESTION 52
Which AI service can you use to interpret the meaning of a user input such as "Call me back later?"

A. Language Understanding (LUIS)
B. Translator Text
C. Speech
D. Text Analytics

Answer: A

Explanation:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/what-is-luis

NEW QUESTION 53
You have the process shown in the following exhibit.

Which type AI solution is shown in the diagram?

A. a sentiment analysis solution
B. a chatbot
C. a computer vision application
D. a machine learning model

Answer: B

NEW QUESTION 54
Your website has a chatbot to assist customers.
You need to detect when a customer is upset based on what the customer types in the chatbot.
Which type of AI workload should you use?

A. anomaly detection
B. semantic segmentation
C. natural language processing
D. regression

Answer: C

Explanation:
Section: Describe features of Natural Language Processing (NLP) workloads on Azure Explanation:
Natural language processing (NLP) is used for tasks such as sentiment analysis, topic detection, language detection, key phrase extraction, and document categorization.
Sentiment Analysis is the process of determining whether a piece of writing is positive, negative or neutral.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language- processing

NEW QUESTION 55
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:

Explanation

Accelerate your business processes by automating information extraction. Form Recognizer applies advanced machine learning to accurately extract text, key/value pairs, and tables from documents. With just a few samples, Form Recognizer tailors its understanding to your documents, both on-premises and in the cloud.
Turn forms into usable data at a fraction of the time and cost, so you can focus more time acting on the information rather than compiling it.
Reference:
https://azure.microsoft.com/en-us/services/cognitive-services/form-recognizer/

NEW QUESTION 56
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:

Explanation:
In the most basic sense, regression refers to prediction of a numeric target.
Example: Regression Model: A Boosted Decision Tree algorithm was used to create and train the model for predicting the repayment rate.
Reference:
https://gallery.azure.ai/Experiment/Student-Loan-Repayment-Rate-Prediction

NEW QUESTION 57
What are three Microsoft guiding principles for responsible AI? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

A. decisiveness
B. opinionatedness
C. reliability and safety
D. inclusiveness
E. fairness
F. knowledgeability

Answer: C,D,E

Explanation:
Section: Describe Artificial Intelligence workloads and considerations
Explanation/Reference:
https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles

NEW QUESTION 58
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. QnA Maker
B. Face
C. Translator Text
D. Custom Vision

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. 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/

NEW QUESTION 59
You are designing an AI system that empowers everyone, including people who have hearing, visual, and other impairments.
This is an example of which Microsoft guiding principle for responsible AI?

A. fairness
B. accountability
C. reliability and safety
D. inclusiveness

Answer: D

Explanation:
Inclusiveness: At Microsoft, we firmly believe everyone should benefit from intelligent technology, meaning it must incorporate and address a broad range of human needs and experiences. For the 1 billion people with disabilities around the world, AI technologies can be a game-changer.
Reference:
https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles

NEW QUESTION 60
You are developing a model to predict events by using classification.
You have a confusion matrix for the model scored on test data as shown in the following exhibit.

Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio/evaluate-model-performance

NEW QUESTION 61
You need to provide content for a business chatbot that will help answer simple user queries.
What are three ways to create Question: 57
solution.
NOTE: Each correct selection is worth one point.

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

Answer: B,D,E

Explanation:
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

NEW QUESTION 62
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation
Graphical user interface, text, application, email Description automatically generated

Reference:
https://docs.microsoft.com/en-us/azure/bot-service/bot-service-overview-introduction?view=azure-bot-service-4.