The dataset can be viewed at https://www.kaggle.com/barun2104/telecom-churn
With the rapid development of telecommunication industry, the service providers are inclined more towards expansion of the subscriber base. To meet the need of surviving in the competitive environment, the retention of existing customers has become a huge challenge. It is stated that the cost of acquiring a new customer is far more than that for retaining the existing one. Therefore, it is imperative for the telecom industries to use advanced analytics to understand consumer behavior and in-turn predict the association of the customers as whether or not they will leave the company.
This data set contains customer level information for a telecom company. Various attributes related to the services used are recorded for each customer.
It is one of the important concepts that can be used in the dataset. When we perform operations like feature engineering, data preprocessing, Feature scaling the code becomes messy. If we want to handle this problem we use the concept of pipelining. Machine learning pipeline is used to help automate machine learning workflows.