The goal of this project is to build a spam filter that can effectively categorise an incoming mail or text message as either “spam” or “ham”. Using dataset that consists of 5574 observations of 2 variables, the project was able to build a classifier that is able to accurately classifier an incoming mail as either "spam" or "ham".

This project has a data set of 614 observations and 13 variables with the purpose of predicting the possibility of a customer defaulting his or her loan obligation.

This is just an academic research work and analysis is not to be relied upon. Its just an academic exercise.

Variable importance