Student Academic Performance Prediction
تفاصيل العمل
Built a machine learning classification model to predict students' academic performance categories based on behavioral and academic features. The project involved preprocessing a real-world student dataset — encoding categorical variables, splitting data, and training a Random Forest Classifier — achieving strong accuracy on unseen test data. What was done: - Cleaned and encoded categorical features using Label Encoding - Trained a Random Forest model with an 80/20 train-test split - Evaluated performance using accuracy score and a full classification report - Compared train vs. test accuracy to assess model generalization Tools & Libraries: Python, Pandas, NumPy, Scikit-learn
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بطاقة العمل
طلب عمل مماثل
