Practical Data Science using Python - EDA Project - 5

The video tutorial explains how to create categorical features from numeric data, focusing on funded amounts and annual income. It analyzes default ratios across different funded amount ranges and visualizes the relationship between funded amounts and income brackets. The tutorial also examines mean values of numeric features for defaulted and non-defaulted loans, and compares requested loan amounts with disbursed amounts to identify discrepancies. Insights are provided for potential improvements in loan default rates.

What new insight or understanding did you gain from this video?

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