skprasad117/Predicting-Student-Performance-Using-Machine-Learning
Using machine learning algorithms, this project aims to predict student performance in standardized tests based on demographic and academic data.
Implements a Flask web interface with a modular pipeline architecture (data processing, model training, artifact management) using CatBoost for regression-based math score prediction. Achieves 85% accuracy by analyzing feature importance across socioeconomic factors like parental education and test preparation, with exploratory notebooks documenting the data analysis workflow.
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Jun 04, 2023
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