Intelligent Student Engagement and Retention Prediction System

Build an advanced Python-based predictive modeling system using TensorFlow and Keras that forecasts student engagement and potential dropout risks with 85%+ accuracy. The system must integrate multiple data sources including learning management system interactions, academic performance, demographic data, and psychological assessment metrics. Develop a comprehensive machine learning pipeline that includes automated feature engineering, model selection, hyperparameter tuning, and real-time risk scoring. Create an intuitive Django-based administrative interface for intervention tracking and personalized support recommendations.