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student-success-metrics

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sngillard / student-outcome-classification

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Multiclass machine learning model to predict student success outcomes in higher education.

python machine-learning numpy scikit-learn exploratory-data-analysis jupyter-notebook data-visualization seaborn classification data-analysis matplotlib ipywidgets gradient-boosting-classifier supervised-machine-learning higher-education-data pandas-library google-colaboratory-notebooks multinomial-logistic-regression multiple-linear-regression-model student-success-metrics
  • Updated Jan 25, 2026
  • Jupyter Notebook

mgesteban / success-by-support-ml

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Machine learning classification project predicting student success from support service participation at California Community Colleges. Compares Logistic Regression, Decision Tree, and Random Forest models using data from SFCCD and Allan Hancock College. Decision Tree achieved 80% F1 score.

python machine-learning scikit-learn machine-learning-algorithms logistic-regression decision-tree-classifier community-college random-forest-classifier student-success-metrics city-college-of-san-francisco
  • Updated Jan 19, 2026
  • Jupyter Notebook

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