Data Scaling

Topic

Data scaling, also known as feature scaling or data normalization, is a crucial preprocessing step in data processing and machine learning used to standardize the range of independent variables or features. By adjusting the values of different features to a common scale, it prevents variables with larger magnitudes from disproportionately dominating model training and improves the convergence speed of optimization algorithms.