ankur-one/student-performance-prediction

Student Performance Prediction is a Streamlit application that predicts a student’s mathematics score from demographic details and reading/writing scores. The training workflow loads and splits the student dataset, preprocesses features, compares and tunes regression models, evaluates them, and saves the selected model and preprocessor. At runtime, the app collects inputs, builds a dataframe, applies the saved preprocessor and model, and displays the predicted score. Training wiring is evidenced by the executable in data_ingestion.py; cloud deployment is described in the README but its implementation is not shown.