churn_machine_learning_project
1. Introduction
We aim to accomplist the following for this study:
Identify and visualize which factors contribute to customer churn:
Build a prediction model that will perform the following:
Classify if a customer is going to churn or not Preferably and based on model performance, choose a model that will attach a probability to the churn to make it easier for customer service to target low hanging fruits in their efforts to prevent churn
2. Data set review & preparation
In this section we will seek to explore the structure of our data:
To understand the input space the data set And to prepare the sets for exploratory and prediction tasks as described in section 1