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anu-gtb/campusPlacement

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data.csv -> training data on which models to be trained


test.csv -> testing data to test model performance


model.ipynb -> contains steps - data loading, data preprocessing, data visualization, model training, evaluation, model selection


app.py -> Streamlit app development


backend.py -> loading scaler, trained model and preprocessing functions to be applied on the new data and prediction


dockerfile -> building docker image of streamlit app


deployment.yaml -> deployment of docker image to kubernetes cluster through CI/CD pipeline