Data Preprocessing

Raw data is messy. Learn normalization, standardization, and feature engineering — the critical steps that happen before any model sees data.

Learning Objectives

• →Normalize features to [0,1] range
• →Standardize with zero mean and unit variance
• →Handle missing values
• →Split data into train/validation/test sets

Practice