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Microsoft AI-900 Exam Questions
Free Microsoft AI-900 Exam Actual Questions
Note: Premium Questions for AI-900 were last updated On Apr. 24, 2026 (see below)
Which type of machine learning should you use to identify groups of people who have similar purchasing habits?
According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and the Microsoft Learn module ''Describe features of common AI workloads'', clustering is a type of unsupervised machine learning used to group data points that share similar characteristics. In unsupervised learning, the data provided to the model does not have predefined labels or outcomes. Instead, the algorithm identifies inherent patterns or groupings within the dataset based on similarities in input features.
In this scenario, the task is to identify groups of people who have similar purchasing habits. There is no predefined label such as ''buyer type'' or ''purchase category.'' The goal is to discover hidden patterns---such as grouping customers by spending behavior, preferred products, or frequency of purchases. This is precisely what clustering algorithms are designed to do.
Clustering is commonly used in:
Customer segmentation for marketing analytics.
Market basket analysis to find associations in purchasing patterns.
Recommender systems to identify similar user profiles.
Anomaly detection when outliers deviate from natural clusters.
Typical algorithms for clustering include K-means, Hierarchical clustering, and DBSCAN. These models analyze multidimensional data to form clusters that maximize intra-group similarity and minimize inter-group similarity.
By contrast:
Classification (A) is a supervised learning method that predicts a categorical label (e.g., whether a customer will churn or not). It requires labeled training data.
Regression (B) is used to predict continuous numeric values (e.g., sales revenue, temperature).
Since the question focuses on discovering groups of similar customers without prior labels, the correct type of machine learning is Clustering.
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?
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/overview
You can provide the Text Analytics service with unstructured text and it will return a list of entities in the text that it recognizes. You can provide the Text Analytics service with unstructured text and it will return a list of entities in the text that it recognizes. The service can also provide links to more information about that entity on the web. An entity is essentially an item of a particular type or a category; and in some cases, subtype, such as those as shown in the following table.
https://docs.microsoft.com/en-us/learn/modules/analyze-text-with-text-analytics-service/2-get-started-azure
You use Azure Machine Learning designer to publish an inference pipeline.
Which two parameters should you use to consume the pipeline? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
https://docs.microsoft.com/en-in/learn/modules/create-regression-model-azure-machine-learning-designer/deploy-service
Which Azure Machine Learning capability should you use to quickly build and deploy a predictive model without extensive coding?
During the process of Machine Learning, when should you review evaluation metrics?
- Select Question Types you want
- Set your Desired Pass Percentage
- Allocate Time (Hours : Minutes)
- Create Multiple Practice tests with Limited Questions
- Customer Support
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