Student Result Predictor
A small machine-learning demonstration with a Flask prediction form and a saved training pipeline.
Explore the buildThe challenge
The problem behind the build
A learning exercise needs a complete path from a tabular dataset to a model-backed web form.
The approach
How the pieces fit together
A Random Forest training script prepares encoded features and a saved scaler. Flask loads the exported model to serve demonstration predictions.
Capabilities
Inside the implementation
Tabular feature preparation and model training
Saved model and scaler artifacts
Flask form-based inference
Technology
The stack behind this project
PythonFlaskscikit-learnpandas
Project scope
An academic demonstration only, not a tool for real student selection or educational decisions.
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