Student Performance Predictor is an end-to-end machine learning project that implements a complete predictive modeling pipeline. It analyzes the impact of demographic, socioeconomic, and academic factors on student mathematics performance, performing data preprocessing, feature engineering, machine learning model & deployment using Flask & Render.
flask-web gradient-boosting lasso-regression random-forest-regressor decision-tree-regressor standardscaler xgboost-regressor linear-regression-model catboost-regressor adaboost-regressor one-hot-encoder render-deployment ridge-regresson matplotlib-seaborn-and-plotly data-ingestion-and-preprocessing k-neighbours-regressor pandas-and-numpy
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Updated
Feb 7, 2026 - Jupyter Notebook