2022 Latest AI-900 dumps – Instant Download PDF [Q27-Q42]

July 5, 2022July 5, 2022 examdumps2022 Latest AI-900 dumps – Instant Download PDF [Q27-Q42] 0 Comment

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2022 Latest AI-900 dumps – Instant Download PDF

Updated Verified AI-900 Downloadable Printable Exam Dumps

The Microsoft AI-900 exam, usually known as the Microsoft Azure AI Fundamentals, is well suited to baseline-level IT specialists with knowledge of artificial intelligence (AI) & Machine Learning (ML), and the relevant Microsoft Azure concepts. This is the only test that you should pass to qualify for the Microsoft Certified: Azure AI Fundamentals certification.

Q27. You have an Azure Machine Learning pipeline that contains a Split Data module. The Split Data module outputs to a Train Model module and a Score Model module. What is the function of the Split Data module?

selecting columns that must be included in the model

creating training and validation datasets

diverting records that have missing data

scaling numeric variables so that they are within a consistent numeric range

Q28. Which AI service can you use to interpret the meaning of a user input such as “Call me back later?”

Translator Text

Text Analytics

Speech

Language Understanding (LUIS)

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

Q29. To complete the sentence, select the appropriate option in the answer area.

Explanation:
In the most basic sense, regression refers to prediction of a numeric target.
Linear regression attempts to establish a linear relationship between one or more independent variables and a numeric outcome, or dependent variable.
You use this module to define a linear regression method, and then train a model using a labeled dataset. The trained model can then be used to make predictions.
Incorrect Answers:
Classification is a machine learning method that uses data to determine the category, type, or class of an item or row of data.
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/algorithm-module-reference/linear-regression
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/machine-learning-initialize- model-clustering

Q30. To complete the sentence, select the appropriate option in the answer area.

Explanation

In machine learning, if you have labeled data, that means your data is marked up, or annotated, to show the target, which is the answer you want your machine learning model to predict.
In general, data labeling can refer to tasks that include data tagging, annotation, classification, moderation, transcription, or processing.
Reference:
https://www.cloudfactory.com/data-labeling-guide

Q31. You use natural language processing to process text from a Microsoft news story.
You receive the output shown in the following exhibit.

Which type of natural languages processing was performed?

entity recognition

key phrase extraction

sentiment analysis

translation

https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/overview

Q32. To complete the sentence, select the appropriate option in the answer area.

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

Q33. To complete the sentence, select the appropriate option in the answer area.
Using Recency, Frequency, and Monetary (RFM) values to identify segments of a customer base is an example of___________

See the below in explanation:
Classification

Q34. To complete the sentence, select the appropriate option in the answer area.

Explanation
Graphical user interface, table Description automatically generated

Reference:
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai

Q35. To complete the sentence, select the appropriate option in the answer area.

Q36. 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.

Explanation
Graphical user interface, text, application, chat or text message Description automatically generated

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

Q37. Which service should you use to extract text, key/value pairs, and table data automatically from scanned documents?

Form Recognizer

Text Analytics

Ink Recognizer

Custom Vision

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/

Q38. Select the answer that correctly completes the sentence.

Explanation

Q39. To complete the sentence, select the appropriate option in the answer area.
Computer vision capabilities can be Deployed to………………..

Integrate a facial recognition feature into an app.

Q40. 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?

Custom Vision

QnA Maker

Translator Text

Face

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 semistructured 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.
Reference:
https://azure.microsoft.com/en-us/services/cognitive-services/qna-maker/

Q41. 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.

Predict stock prices.

Detect brands in an image.

Detect the color scheme in an image

Translate text between languages.

Extract key phrases.

Section: Describe features of computer vision workloads on Azure
Explanation:
B: Identify commercial brands in images or videos from a database of thousands of global logos. You can use this feature, for example, to discover which brands are most popular on social media or most prevalent in media product placement.
C: Analyze color usage within an image. Computer Vision can determine whether an image is black & white or color and, for color images, identify the dominant and accent colors.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/overview

Q42. To complete the sentence, select the appropriate option in the answer area.

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/

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