The project aims to analyze factors influencing loan approval decisions using a comprehensive dataset of loan applicants. Jupyter Notebook will be used to implement machine learning models, including logistic regression and decision trees, to uncover trends and relationships that can improve fairness and reduce bias in the loan approval process.
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The project aims to analyze factors influencing loan approval decisions using a comprehensive dataset of loan applicants. Jupyter Notebook will be used to implement machine learning models, including logistic regression and decision trees, to uncover trends and relationships that can improve fairness and reduce bias in the loan approval process.
riddhima109/Loan-Approval-Prediction
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The project aims to analyze factors influencing loan approval decisions using a comprehensive dataset of loan applicants. Jupyter Notebook will be used to implement machine learning models, including logistic regression and decision trees, to uncover trends and relationships that can improve fairness and reduce bias in the loan approval process.
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