Overview

Note: This Dataset is taken from MachineHack - Deloitte Hackathon

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Banks run into losses when a customer doesn't pay their loans on time. Because of this, every year, banks have losses in crores, and this also impacts the country's economic growth to a large extent. In this hackathon, we look at various attributes such as funded amount, location, loan, balance, etc., to predict if a person will be a loan defaulter or not.

To solve this problem, MachineHack has created a training dataset of 67,463 rows and 35 columns and a testing dataset of 28,913 rows and 34 columns. The hackathon demands a few pre-requisite skills like big dataset, underfitting vs overfitting, and the ability to optimise “log_loss” to generalise well on unseen data.