
ScholarSafe Nigeria
Showcasing project
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Summary
An ML-powered web application using a Random Forest model trained on localized Nigerian dropout drivers to predict student risk weeks in advance. It features an accessible user interface that translates raw data into color-coded risk scores and plain-language, actionable recommendations to prevent student dropouts.






