  The following paper explores the possibility of using Machine Learning
algorithms to detect the cases of corruption and malpractice by governments.
The dataset used by the authors contains information about several government
contracts in Colombia from year 2007 to 2012. The authors begin with exploring
and cleaning the data, followed by which they perform feature engineering
before finally implementing Machine Learning models to detect anomalies in the
given dataset.
