AbhishekMali21/STUDENT-GRADE-ANALYSIS-PREDICTION

Given a dataset containing attribute of 396 Portuguese students where using the features available from dataset and define classification algorithms to identify whether the student performs good in final grade exam, also to evaluate different machine learning models on the dataset.

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Implements exploratory data analysis and feature engineering on 30+ sociodemographic and behavioral attributes (family education, study habits, alcohol consumption, absences) beyond basic grades, then compares multiple classification models using scikit-learn. The pipeline addresses the practical challenge of predicting final grades (G3) while handling multicollinearity with prior period grades (G1, G2), enabling early intervention systems to identify at-risk students before semester completion.

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85

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34

Language

Jupyter Notebook

License

MIT

Last pushed

Jan 30, 2024

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