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Feature learning is a machine learning technique that enables systems to automatically discover the representations needed for feature detection or classification from raw data. It plays a crucial role in improving the performance of algorithms by reducing the need for manual feature engineering.
Dimensionality reduction is a process in data analysis and machine learning that transforms data from a high-dimensional space into a lower-dimensional space while preserving essential properties. It facilitates visualization, reduces storage requirements, and helps improve the performance of algorithms by eliminating redundant or irrelevant features.