Preprocessing#
Preprocess your data to remove noise and enhance the chemical information contained in the spectra. Common preprocessing techniques include baseline correction, smoothing, normalization, and derivative transformations. These steps help eliminate unwanted variations caused by instrumental drift or sample inconsistencies, allowing the model to focus on the true chemical signals that drive accurate predictions.