Each row in the dataset corresponds to a loan. You are given information about the loan (starting dates, maturity date, amount, interest rate etc) as well as some information on the customer applying for the loan. You must predict whether or not that person has money overdue. This is encoded in the target column - a 1 indicates that the loan has an unpaid payment due, a 0 indicates that all is well. See the VariableDescription file for more info on the individual columns.

Files available for download:

• Train.csv - contains the input variables and the target, ‘Target’
• Test.csv - matches Train.csv but without the Target
• SampleSubmission.csv - is an example of what your submission file should look like. The order of the rows does not matter, but the names of the Loan_IDs must be correct.
• VariableDescription.csv - contains definitions of the data headers
• Starter_Notebook_Updated.ipynb - this Python starter notebook will help you make your first submission onto the leaderboard. Download the data and run this notebook on your local machine and you will be able to make a submission on the leaderboard.