AI-Powered Educational Equity Index (Classification Pipeline)
Classification
I built a supervised classification pipeline to identify underserved students using synthetic tabular data as part of my Master's project. Responsible and fairness-aware modeling techniques were employed to ensure equitable results in the classification task. The project included the integration of fairness metrics, dashboard visualization, and a policy simulation tool for educational interventions.
• Applied supervised classification to synthetic tabular student data
• Used fairness metrics such as equal opportunity and demographic parity
• Visualized results and model explanations using Tableau dashboards and SHAP
• Integrated with an educational policy simulator via FastAPI
I built a supervised classification pipeline to identify underserved students using synthetic tabular data as part of my Master's project. Responsible and fairness-aware modeling techniques were employed to ensure equitable results in the classification task. The project included the integration of fairness metrics, dashboard visualization, and a policy simulation tool for educational interventions. • Applied supervised classification to synthetic tabular student data • Used fairness metrics such as equal opportunity and demographic parity • Visualized results and model explanations using Tableau dashboards and SHAP • Integrated with an educational policy simulator via FastAPI
2024 - 2026