How can EDA help in feature engineering?

Exploratory Data Analysis (EDA) is an essential step in any data science or machine learning workflow, and its role in feature engineering is both foundational and transformative. Feature engineering involves creating new input features or modifying existing ones to improve the performance of a predictive model. EDA plays a critical role in this process by helping data scientists understand the underlying structure, patterns, and relationships in the data, thereby informing which features may be most useful or how they should be transformed. https://massivelyop.com/author/Jatin_Singh/

EDA helps uncover the distribution and nature of each feature. Through visualizations such as histograms, box plots, and density plots, one can determine whether a feature is normally distributed, skewed, or contains outliers. This insight is crucial because many machine learning algorithms, like linear regression or logistic regression, assume normality in the d