t-distributed Stochastic Neighbor Embedding

t-Distributed Stochastic Neighbor Embedding (t-SNE) is a technique used to visualize high-dimensional data (like complex datasets with many features) in a simple, two- or three-dimensional space. It works by modeling the similarities between data points in the original high-dimensional space and then finding a layout in low dimensions that preserves these relationships. This helps reveal patterns, groupings, or structures that might be hidden, making it easier to understand and interpret complex data visually. Essentially, t-SNE translates complicated information into an intuitive map that highlights relationships between data points.