Automated Feature Engineering

Automated Feature Engineering is the process of automatically creating new data points, or "features," from existing data to improve machine learning models. Think of it as discovering hidden insights or patterns that help computers better understand information. For example, if you have data on people's ages and incomes, automated feature engineering might create new features like "age groups" or "income brackets." This helps the model make more accurate predictions without manual intervention, saving time and effort while enhancing performance. Essentially, it's about making data smarter for analysis.