Finding hidden patterns in unlabeled data with clustering and dimensionality reduction.
Grouping data into 'k' distinct, non-overlapping clusters.
Building a tree of clusters, also known as a dendrogram.
A dimensionality reduction technique to simplify complex data.
Identifying rare items or outliers that deviate from the norm.