This is an Financial Analysis project that deals with finding out how customers will behave based on certain parameters using two ML models - Decision Trees and Random Forest 📈

For this project, I explored publicly available data from LendingClub.com. Lending Club connects people who need money (borrowers) with people who have money (investors). As an investor, you would want to invest in people who showed a profile with a high probability of paying you back. I aimed to create a model to help predict this. Lending Club had a very interesting year in 2016, so I checked out some of their data with this context in mind. This data was from before they even went public. I used lending data from 2007-2010 to classify and predict whether or not the borrower paid back their loan in full. You can download the data from here or use the CSV already provided. It's recommended to use the provided CSV as it has been cleaned of NA values.