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Unsupervised learning deals with finding patterns in data without labeled outputs from "summary" of Machine Learning by Stephen Marsland
In unsupervised learning, the goal is to find patterns in data without having any labeled outputs to guide the process. This means that the algorithm must discover the underlying structure or relationships in the data on its own, without being given explicit examples to learn from. This type of learning is often used when the data is unlabelled or when it is too costly or time-consuming to obtain labels for the data. Unsupervised learning can reveal hidden patterns, groupings, or associations in the data that may not be immediately apparent to the huma...
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