Data Preprocessing

Data preprocessing involves a series of techniques to transform raw data into a clean dataset suitable for analysis. This includes handling missing values, removing duplicates, and normalizing or scaling the data. Effective preprocessing is crucial as it directly impacts the quality of the insights derived from the data and the performance of machine learning models trained on it.