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Microsoft AI-900 Exam Syllabus Topics:

Section	Weight	Objectives
Features of natural language processing (NLP) workloads on Azure	30-35%	- Text analytics and language understanding 1. Language modeling and translation 2. Sentiment analysis 3. Key phrase extraction
Describe AI workloads and considerations	20-25%	- Fundamentals of artificial intelligence concepts 1. Responsible AI principles 2. Common AI workloads
Features of computer vision workloads on Azure	15-20%	- Computer vision solutions 1. Object detection 2. Image classification 3. OCR and image analysis
Fundamentals of machine learning on Azure	25-30%	- Core machine learning concepts 1. Supervised vs unsupervised learning 2. Training and validation concepts

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Microsoft Azure AI Fundamentals Sample Questions (Q271-Q276):

NEW QUESTION # 271
You need to predict the animal population of an area.
Which Azure Machine Learning type should you use?

A. clustering
B. classification
C. regression

Answer: C

Explanation:
According to the AI-900 official study materials, regression is a type of supervised machine learning used to predict continuous numeric values. Predicting the animal population of an area involves estimating a numeric quantity, which makes regression the appropriate model type.
Microsoft Learn defines regression workloads as predicting real-valued outputs, such as:
* Forecasting sales or demand.
* Predicting housing prices.
* Estimating resource usage or population sizes.
In contrast:
* Classification predicts discrete categories (e.g., "cat" or "dog").
* Clustering groups data into similar clusters but doesn't produce numeric predictions.
Therefore, because the task requires predicting a numerical population size, the verified answer is C.
Regression, as per Microsoft's AI-900 official guidelines.

NEW QUESTION # 272
Select the answer that correctly completes the sentence.

Answer:

Explanation:

NEW QUESTION # 273
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/cloud-adoption-framework/innovate/best-practices/trusted-ai

NEW QUESTION # 274
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 # 275
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:
Explanation

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.
Note: The Custom Vision service uses a machine learning algorithm to apply labels to images. You, the developer, must submit groups of images that feature and lack the characteristics in question. You label the images yourself at the time of submission. Then the algorithm trains to this data and calculates its own accuracy by testing itself on those same images. Once the algorithm is trained, you can test, retrain, and eventually use it to classify new images according to the needs of your app. You can also export the model itself for offline use.
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

NEW QUESTION # 276
......

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