Developed a machine learning model to predict loan approval status. Key steps include EDA, handling missing values & outliers, feature engineering, and training an SVC model. Achieved 82.73% accuracy, highlighting Credit History's importance, with recommendations for imbalance and model improvement.
☆44Sep 23, 2025Updated last year
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