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Unsupervised Learning

Unsupervised Learning is the process of learning data which is given only by an input and no tags (labels). The goal is to model the underlying structure or distribution in the data in order to learn more about the data. It is called this way because there is no “correct answer”. Unsupervised Learning can be grouped into Clustering and Association problems.

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