+Dimensionality Reduction simplifies complex datasets by transforming them into a lower-dimensional space. This essential process in [Machine Learning](/wiki/machine_learning) reveals underlying patterns, making data easier to visualize and analyze. It aims to preserve crucial information while discarding noise, often through techniques like [Feature Extraction](/wiki/feature_extraction).
+## See also
+- [Data Compression](/wiki/data_compression)
+- [PCA](/wiki/pca)
+- [Unsupervised Learning](/wiki/unsupervised_learning)
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