AWS Certified AI Practitioner AIF-C01 Practice Question
A retailer has collected millions of click-stream events, but the records are unlabeled-no predefined customer segments exist. The team wants a model that can automatically discover natural groupings of user behavior without being shown example labels during training. Which learning method best fits this requirement?
Unsupervised learning is designed to find patterns or structure in data that has no target labels. Clustering algorithms, for instance, can group customers who browse in similar ways without any prior examples. Supervised learning needs labeled examples, reinforcement learning relies on rewards from an environment, and transfer learning adapts knowledge from a different pre-trained task-none of which meets the goal of learning directly from unlabeled click-stream data.
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AWS Certified AI Practitioner AIF-C01
Fundamentals of AI and ML
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