Academic performance prediction based on multistore multi feature behavioural data
To develop a predictive model that leverages multistore and multi-feature behavioral data to accurately forecast students’ academic performance, enabling early identification of at-risk students and supporting personalized educational interventions.
Project ID: 0279
Sub domains: Data mining
Domain: Java
Project Year: 2020
Keywords: Academic Performance Prediction Behavioural Data Analysis Multi-Feature Data
Project Cost : â‚ą6500
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