Latest Jul-2023 AI-900 Dumps PDF And Certification Training [Q57-Q71]

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Latest Jul-2023 AI-900 Dumps PDF And Certification Training

Check your preparation for Microsoft AI-900 On-Demand Exam

Microsoft AI-900: Microsoft Azure AI Fundamentals exam is a certification that is designed to validate the candidate’s knowledge and understanding of Artificial Intelligence (AI) and its applications on the Azure cloud platform. AI-900 exam is intended for individuals who are interested in understanding the basic concepts of AI and how it can be applied in various scenarios.

Passing the AI-900 exam is beneficial for individuals who are looking to start a career in AI and machine learning, or those who want to demonstrate their knowledge and expertise in these areas. Microsoft Azure AI Fundamentals certification can be useful for IT professionals, developers, data scientists, business analysts, and other professionals who want to explore the potential of AI and machine learning in their respective fields.

NO.57 You are building an AI system.
Which task should you include to ensure that the service meets the Microsoft transparency principle for responsible AI?

Ensure that all visuals have an associated text that can be read by a screen reader.

Enable autoscaling to ensure that a service scales based on demand.

Provide documentation to help developers debug code.

Ensure that a training dataset is representative of the population.

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

NO.58 You send an image to a Computer Vision API and receive back the annotated image shown in the exhibit.

Which type of computer vision was used?

object detection

semantic segmentation

optical character recognition (OCR)

image classification

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

NO.59 Match the types of AI workloads to the appropriate scenarios.
To answer, drag the appropriate workload type from the column on the left to its scenario on the right. Each workload type may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.

Reference:
https://docs.microsoft.com/en-us/learn/paths/get-started-with-artificial-intelligence-on-azure/

NO.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.

Explanation

Box 1: 11

TP = True Positive.
The class labels in the training set can take on only two possible values, which we usually refer to as positive or negative. The positive and negative instances that a classifier predicts correctly are called true positives (TP) and true negatives (TN), respectively. Similarly, the incorrectly classified instances are called false positives (FP) and false negatives (FN).
Box 2: 1,033
FN = False Negative
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio/evaluate-model-performance Finding TP is easy. It basically means the value where Predicted and True value is 1 and that is 11 in this case.
False Negative means where true value was 1 but predicted value was 0 and that is 1033 in this case The confusion matrix shows cases where both the predicted and actual values were 1 (known as true positives) at the top left, and cases where both the predicted and the actual values were 0 (true negatives) at the bottom right. The other cells show cases where the predicted and actual values differ (false positives and false negatives).
https://docs.microsoft.com/en-us/learn/modules/create-classification-model-azure-machine-learning-designer/eva

NO.61 Select the answer that correctly completes the sentence.

Explanation

NO.62 You need to develop a mobile app for employees to scan and store their expenses while travelling.
Which type of computer vision should you use?

semantic segmentation

image classification

object detection

optical character recognition (OCR)

Azure’s Computer Vision API includes Optical Character Recognition (OCR) capabilities that extract printed or handwritten text from images. You can extract text from images, such as photos of license plates or containers with serial numbers, as well as from documents – invoices, bills, financial reports, articles, and more.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-recognizing-text

NO.63 To complete the sentence, select the appropriate option in the answer area.

Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/home custom vision – This is a type of computer vision service which helps in building/training models using user provided data Creating an object detection solution with Custom Vision consists of three main tasks. First you must use upload and tag images, then you can train the model, and finally you must publish the model so that client applications can use it to generate predictions.
https://docs.microsoft.com/en-us/learn/modules/detect-objects-images-custom-vision/2-object-detection-azure

NO.64 To complete the sentence, select the appropriate option in the answer area.

Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-science-process/create-features

NO.65 For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

NO.66 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.

Generate the questions and answers from an existing webpage.

Use automated machine learning to train a model based on a file that contains the questions.

Manually enter the questions and answers.

Connect the bot to the Cortana channel and ask questions by using Cortana.

Import chit-chat content from a predefined data source.

Section: Describe features of conversational AI workloads on Azure
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

NO.67 To complete the sentence, select the appropriate option in the answer area.

Explanation

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/team-data-science-process/create-features

NO.68 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.

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/named-entity-recognition
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-sentiment-analysis

NO.69 Select the answer that correctly completes the sentence

NO.70 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.

Reference:
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai
https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles

NO.71 You have the following dataset.

You plan to use the dataset to train a model that will predict the house price categories of houses.
What are Household Income and House Price Category? To answer, select the appropriate option in the answer area.
NOTE: Each correct selection is worth one point.