Data Preprocessing

Data preprocessing is the process of transforming raw data into a clean and usable format for analysis. It involves various techniques such as data cleaning, normalization, transformation, and feature extraction. The primary goal is to enhance the quality of data, making it suitable for machine learning models or statistical analysis. Common use cases include preparing datasets for predictive modeling, ensuring data consistency, and improving model performance by eliminating noise and irrelevant features.