In this section, we are going to discuss how to use an ANN model to predict the customers at the risk of leaving, or customers who are highly likely to churn. By the end of this section, we will have built a customer churn prediction model using an ANN model. We will be mainly using the pandas, matplotlib, and keras packages to analyze, visualize, and build machine learning models. For those readers who would like to use R, instead of Python, for this exercise, you can skip to the next section.
For this exercise, we will be using one of the publicly available datasets from the IBM Watson Analytics community, which can be found at this link: https://www.ibm.com/communities/analytics/watson-analytics-blog/predictive-insights-in-the-telco-customer-churn-data-set/. You can follow this link and download the data, which is available in XLSX format...
