Predicts loan approval using demographic and financial data. Includes data cleaning, EDA, feature engineering, and ML models (Logistic Regression, Random Forest). Achieved ~79% accuracy. Full notebook, predictions, and insights documented.
python machine-learning random-forest scikit-learn insights jupyter-notebook eda seaborn logistic-regression feature-engineering financial-data loan-approval loan-prediction data-cleaning-and-preprocessing
-
Updated
May 27, 2025 - Jupyter Notebook