Churn modelling for bank customers using Artificial Neural Network
Churn Modelling
It is very important in the customer retention analysis for any sector. The output of a predictive churn model is a measure of the immediate or future risk of a customer cancellation(in this case whether the customer will stay in the bank or leave the bank) use cases
- to understand why customers are leaving
- to provide incentives to certain customers to prevent them from leaving
- predicting the revenue of the business
Dataset
Kaggle dataset by the name Churn_Modelling.csv
model used
The model used here is a basic Artificial Neural Network(ANN) with 2 hidden layers run for 100 epochs.
Framework and Libraries
-Pandas
-Numpy
-Keras running on Tensorflow backend
-Code compiled and run on Colab
Tip 💡 Easy way to upload local dataset to Colab link
performance metrics
