Machine learning project predicting financial distress risk (Low/Medium/High) for gig economy workers — delivery partners, ride-hailing drivers, and platform-based workers — using demographic, income, expense, savings, and well-being data. Built with pandas, scikit-learn, and statsmodels.
python data-science machine-learning random-forest svm scikit-learn machine-learning-algorithms jupyter-notebook data-visualization python3 classification logistic-regression decision-trees predictive-analytics gig-economy financial-vulnerability financial-risk
-
Updated
Aug 6, 2026 - Jupyter Notebook