Customer-Churn-Prediction-using-Artificial-Neural-Network and Bank-Customer-Churn-Prediction

About Customer-Churn-Prediction-using-Artificial-Neural-Network

vishal815/Customer-Churn-Prediction-using-Artificial-Neural-Network

This project involves building an Artificial Neural Network (ANN) for predicting customer churn. The dataset used contains various customer attributes, and the ANN is trained to predict whether a customer is likely to leave the bank.

Implements a sequential neural network with two hidden layers using TensorFlow/Keras, incorporating standard preprocessing pipelines (label encoding, one-hot encoding, feature scaling) and binary crossentropy optimization. The model achieves 86.3% accuracy through 100 epochs of training on the Churn_Modelling dataset. Includes prediction examples with detailed formatting requirements for categorical variable encoding.

About Bank-Customer-Churn-Prediction

ErayMericDev/Bank-Customer-Churn-Prediction

Predicting bank customer churn using Artificial Neural Networks (ANN) and Python.