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How can AI be used to reduce dimensionality?
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Answer / Mohammad Safi Khan
AI can reduce dimensionality by techniques such as Principal Component Analysis (PCA), t-distributed Stochastic Neighbor Embedding (t-SNE), and Autoencoders. These methods aim to represent high-dimensional data in a lower-dimensional space while preserving the essential structure and relationships between data points.
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