Overview / Usage

About Company Dream Housing Finance company deals in all home loans. They have a presence across all urban, semi urban and rural areas. Customer first applies for the home loan after that company validates the customer eligibility for the loan.

Problem Company wants to automate the loan eligibility process (real-time) based on customer detail provided while filling an 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.

Methodology / Approach

I created a model to predict the approval of home loans. In the first notebook, I tackled the null data. Then I conducted an exploratory data analysis to gain a better understanding of the data. Finally, I used a gradient boosting classifier to make predictions on the test set.

Technologies Used

Python and its library, Machine Learning and its framework.