A Model Created to predict if a person is eligible for loan or not.
The folder contains: -A csv file which is the dataset used for building the model. -A .ipynb file where EDA was done on the dataset and the model was built using a machine learning algorithm known as Logistic Regression. -A .pkl file which is the actual model saved in a pickle file. The model makes predictions taking inputs such as Gender, Married, Dependents, Education, Self_Employed, ApplicantIncome, CoapplicantIncome, LoanAmount, Loan_Amount_Term, Credit_History and Property_Area. An example of the model making prediction is in the notebook(.ipynb file).