student-performance

An interpretable early-warning engine that detects academic instability before grades collapse. Instead of predicting performance, it models pressure accumulation, buffer strength, and transition risk using attendance, engagement, and study load to explain fragility and identify high-leverage interventions.

Professional Data Science project analyzing student performance factors using XGBoost, SHAP implementation, and K-Means Clustering for student segmentation.

AI-powered Student Performance Prediction System using Machine Learning and Gemini AI Study Coaching. Predicts exam scores based on study habits and provides personalized study recommendations.

Analyze and Predict student performance using ( SPAPS )

An end-to-end MLOps project demonstrating a modular machine learning pipeline for predicting student performance, featuring a Flask web interface and deployment on AWS.