Built a pipeline using stats + SHAP to detect grading bias and evaluate teacher impact via attendance and marks data. Identified sensitive attribute influence (e.g., gender/religion) on student performance using explainable AI.
python numpy plotly pandas data-visualization data-analysis anova interactive-visualization csv-validator regression-analysis explainable-ai bias-detection shap streamlit teacher-evaluation student-performance multi-page-app academic-analysis education-analytics fairness-in-education
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Updated
Sep 26, 2025 - Python