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AI | Machine Learning | Tech on Instagram: "T-SNE (t-Distributed Stochastic Neighbor Embedding) is a dimensionality reduction technique that is remarkable at handling non-linear data by preserving the local structure of high-dimensional datasets in lower-dimensional spaces. For instance, given a spiral-like 3D dataset, t-SNE has no problem reducing it to lower dimensions, while other dimensionality reduction techniques such as PCA (principal component analysis) that have linear implementations s
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AI • Machine Learning • Tech on Instagram: "t-SNE (t-Distributed Stochastic Neighbor Embedding) is an improvement over SNE (Stochastic Neighbor Embedding) for visualizing high-dimensional data in lower dimensions (2D/3D). Both methods aim to preserve local similarities between points, but SNE struggles with a “crowding problem,” where distant points get pushed too close together in the lower-dimensional space. SNE is designed to visualize high-dimensional data by preserving pairwise similarities
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