Bank Customer Churn Prediction

• Tech Stack: Matplotlib, Sklearn, Python, ANN, H2O AutoML, Pandas, Numpy
• Github URL: Project Link

In general, churn is expressed as a degree of customer inactivity or disengagement, observed over a given time. This manifests within the data in various forms such as the recency of account actions or change in the account balance

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

We will be using ANN models and H2O Auto ML in this project