Trained on unlabeled data (data without known outputs)
Tries to find patterns and relationships in the data on its own
Used for clustering tasks (e.g., grouping customers together based on their purchase history) and dimensionality reduction tasks (e.g., reducing the number of features in a dataset without losing too much information)
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