Data Preprocessing

The set of transformations applied to raw data before it is fed into a model, including cleaning, normalization, tokenization, and feature extraction. Preprocessing bridges the gap between messy real-world data and the clean, structured input that models require.
See also: tokenization, data pipeline, training data.