ISM 415 InClass Machine Learning Competition
This Kaggle is a project from the course ISM 415: Special Topics at Pan Atlantic University in Nigeria. All students must create a Kaggle account and submit a solution.
CASE STUDY: ZOC GROUP OF COMPANIES - CUSTOMER CHURN PREDICTION
Customer churn is a major problem and one of the most important concerns for large companies. Due to the direct effect on the revenues of the companies, especially in the telecom field, companies are seeking to develop means to predict potential customers to churn. Therefore, finding factors that increase customer churn is important to take necessary actions to reduce this churn.
You have been called in by ZOC GROUP OF COMPANIES  to use your machine learning skills to study the pattern of customers churn (exit). With this insight, they can understand the important features among available features that can be used to predict the customers that are likely to churn out of their service in the future.
The dataset contains these variables as explained below:
- CustomerId: System-generated unique customer's ID
- Surname: Customer's Surname
- CreditScore: System generated scores
- Geography: Customer's Country
- Gender
- Age
- Tenure: How long he/she has been a customer
- Balance: Available Balance
- NumOfProducts: Number of products bought
- HasCrCard: Does customer has a credit card
- IsActiveMember: States if the customer is active or not
- EstimatedSalary: Customer's estimated salary