t-Distributed Stochastic Neighbor Embedding (t-SNE) is a powerful dimensionality reduction technique particularly well-suited for visualizing high-dimensional datasets by preserving local structures and revealing complex patterns. It works by converting similarities between data points into joint probabilities and minimizing the Kullback-Leibler divergence between these probabilities in a lower-dimensional space, often used to create insightful two or three-dimensional visualizations.
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