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Unsupervised Learning

Unsupervised Learning is a type of machine learning in which the algorithms are provided with data that does not contain any labels or explicit instructions on what to do with it.

The goal is for the learning algorithm to find structure in the input data on its own.

To put it simply—Unsupervised Learning is a kind of self-learning where the algorithm can find previously hidden patterns in the unlabeled datasets and give the required output without any interference.

Identifying these hidden patterns helps in clustering, association, and detection of anomalies and errors in data.

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