Advanced Student Performance Prediction Model

Create a comprehensive machine learning pipeline in Python that predicts student academic performance using advanced feature engineering and ensemble learning techniques. Integrate multiple data sources including historical academic records, socioeconomic indicators, and extracurricular participation. Implement gradient boosting, random forest, and neural network models, with a robust cross-validation framework. Generate interpretable model insights and feature importance rankings.