Unsupervised Learning — Microsoft Azure AI Fundamentals (AI-900) Practice Questions
Unsupervised learning refers to training a model on data that has no labels, allowing the algorithm to identify patterns, structures, or groupings on its own. The AI-900 exam uses unsupervised learning primarily to contrast with supervised learning, helping candidates decide which paradigm fits a given business problem. Clustering is the most commonly tested unsupervised technique, but the exam also touches on the general principle that unsupervised approaches are used when labeling data is impractical or when the goal is exploration rather than prediction.
Free questions on unsupervised learning
What is the difference between classification and clustering in machine learning?
Free question · medium · full answer + explanation
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