This project aims to automate the loan eligibility validation process for a housing finance company. The company offers interest-free home loans and wants to predict loan decisions and amounts based on customer details provided in the loan application form.
- Linear Regression Model for predicting loan amounts.
- Logistic Regression Model for predicting loan status.
- Data preprocessing, analysis, and visualization.
- Evaluation metrics: R2 score for linear regression, accuracy for logistic regression.
loan_old.csv:Contains 614 records of applicants' data with 10 feature columns and 2 target columns.loan_new.csv:Contains 367 records of new applicants' data with the same structure.