The aim of this project is to perform exploratory data analysis on Ames housing data. This data has information about the characteristics of houses in Ames, lowa and the price of those houses.

The aim of this project is to build a model that can predict with a high degree of accuracy whether the customer churned. We will also explore which factors increase the probability of customer churning. We have customers’ data from a telco company including whether the customer churned. We will use this data to build multiple classification models and select the one that does a good job at predicting whether the customer churned.