AI-Based Student Dropout Detection & Prevention System – Data Labeling for ML Model
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I developed a machine learning model to predict student dropout risk using academic and behavioral data. Data was labeled as high, medium, or low risk based on input features and validated through iterative testing. The project involved creating a prevention framework and pitching the AI solution under tight deadlines.
• Labeled student records with categorical risk classes.
• Used labeled data to train and evaluate the AI model.
• Collaborated with a multidisciplinary team for annotation strategies.
• Performed quality assurance on label consistency and accuracy.
I developed a machine learning model to predict student dropout risk using academic and behavioral data. Data was labeled as high, medium, or low risk based on input features and validated through iterative testing. The project involved creating a prevention framework and pitching the AI solution under tight deadlines. • Labeled student records with categorical risk classes. • Used labeled data to train and evaluate the AI model. • Collaborated with a multidisciplinary team for annotation strategies. • Performed quality assurance on label consistency and accuracy.
2025 - 2025