A machine learning project to predict student dropout risks based on demographic, academic, and socio-economic factors. Includes data preprocessing, feature engineering, model training, and deployment scripts. Designed to help educational institutions identify at-risk students and improve retention rates.
education data-science machine-learning classification data-analysis predictive-modeling student-dropout streamlit student-retention academic-success
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Updated
Sep 3, 2024 - Jupyter Notebook