Company wants to automate the loan eligibility process (real time) based on customer detail provided while filling online application form. These details are Gender, Marital Status, Education, Number of Dependents, Income, Loan Amount, Credit History and others. To automate this process, they have given a problem to identify the customers segments, those are eligible for loan amount so that they can specifically target these customers. Here they have provided a partial data set. We will create a model with the following steps: ● Import the relevant packages ● Download and explore the dataset Also visualised data from CSV file ● Prepare the dataset for training ● Use any prediction algorithm based upon the EDA I used Naive bayes classifier model for this project ● Train the model to fit the data ● Make predictions using the trained model ● Create a test case and generate a predicted result from the system DATE CREATED: 18-12-2021