Machine Learning

Unsupervised Learning

Finding structure with no labels — grouping, compressing and spotting the unusual.

Without labels there is no accuracy score to optimise, so you are looking for structure that already exists: natural groupings, lower-dimensional shape, points that do not fit.

The catch is validation. You cannot prove a clustering is correct, only that it is stable and that a domain expert finds the groups meaningful. That makes communication part of the technical work.

Also in Machine Learning

Supervised Learning K-Means K-Nearest Neighbours Logistic Regression Linear Regression PCA

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