2Exploratory Data Analysis

• 2.1Statistics and Distributions

  Know your data—understand summary statistics (mean/median/variance), distributions, outliers, class imbalance, and correlation. Grasp the data before modeling.

• 2.2Exploration with Visualization

  See to understand—learn when to use histograms, box plots, scatter plots, and correlation heatmaps. Quickly grasp data characteristics with the right chart.

• 2.3Preprocessing and Data Quality

  Prepare for the model—understand imputation, outlier handling, encoding/scaling, class-imbalance handling (SMOTE), and avoiding data leakage.