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Although the Microsoft AI-900 Exam is associated with the foundational-level certification, all the successful candidates can pursue various lucrative career paths in the field of IT. Some of the job roles that these professionals can work in include a Data Scientist, a Software Developer, and an Azure AI Engineer, among others. They can also proceed to get some other role-based certificates to boost their potential in the world of Information Technology. With the Microsoft Certified: Azure AI Fundamentals certification, you can earn an average of $48,000 per annum as an entry-level specialist. Those with some work experience can get an average of $74,000 per year.
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NEW QUESTION # 161
You are processing photos of runners in a race.
You need to read the numbers on the runners' shirts to identity the runners in the photos.
Which type of computer vision should you use?
Answer: B
Explanation:
Optical character recognition (OCR) allows you to extract printed or handwritten text from images and documents.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/overview-ocr
NEW QUESTION # 162
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:
NEW QUESTION # 163
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
Explanation:
In the context of Microsoft Azure AI Fundamentals (AI-900) and general machine learning principles, regression refers to a type of supervised learning used to predict continuous numerical values based on historical data. The goal of regression is to model the relationship between input variables (features) and a continuous output variable (target).
In this scenario, the task is to predict how many vehicles will travel across a bridge on a given day. The number of vehicles is a numerical value that can vary continuously depending on factors such as time of day, weather, weekday/weekend, or traffic trends. Because the output is numeric and not categorical, this problem type clearly fits into regression analysis.
Microsoft's official learning content for AI-900, under "Identify features of regression and classification machine learning models," specifies that regression models are used to predict values such as sales forecasts, demand estimation, temperature prediction, or traffic volume-all of which share the same underlying objective: predicting a quantity.
To clarify other options:
* Classification is used when predicting categories or discrete classes, such as determining whether an email is spam or not spam, or if an image contains a cat or a dog.
* Clustering is an unsupervised learning technique used to group similar data points without predefined labels (for example, grouping customers by purchasing behavior).
Since predicting the number of vehicles results in a continuous numerical output, it aligns precisely with the regression workload type described in the Microsoft AI-900 study materials.
NEW QUESTION # 164
Which type of machine learning should you use to predict the number of gift cards that will be sold next month?
Answer: A
Explanation:
According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and Microsoft Learn module "Identify features of regression machine learning", regression is the machine learning technique used when the goal is to predict a continuous numeric value based on historical data. In this question, predicting the number of gift cards that will be sold next month involves forecasting a quantity-a numeric outcome- which is the hallmark of a regression problem.
Regression models learn patterns from past data (for example, previous months' gift card sales, seasonality, holidays, and marketing spend) and use that information to predict future sales. Common algorithms used for regression include linear regression, decision tree regression, and boosted regression trees. The output is a continuous value such as "2,450 gift cards expected next month." In contrast:
* A. Classification is used when the output is categorical, such as predicting whether a transaction is
"fraud" or "not fraud," or whether a customer will "renew" or "cancel." It answers questions with discrete classes rather than numeric values.
* C. Clustering is an unsupervised learning technique used to group similar data points together based on their characteristics-for example, segmenting customers into behavior-based clusters. Clustering doesn't predict future numeric outcomes.
The AI-900 curriculum explicitly explains that regression predicts numeric values, classification predicts categories, and clustering finds natural groupings in data.
Therefore, to predict the number of gift cards to be sold, the correct and verified machine learning type is Regression.
Reference:Microsoft Learn - Identify the types of machine learning models: Regression, Classification, and Clustering (AI-900 Learning Path)
NEW QUESTION # 165
Match the types of computer vision 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.
Answer:
Explanation:
Reference:
https://azure.microsoft.com/en-us/services/cognitive-services/face/
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-object-detection
NEW QUESTION # 166
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