Project Overview

An Artificial Neural Network (ANN) model for predicting customer churn in the banking sector. This binary classification system analyzes customer data including credit score, geography, gender, age, tenure, balance, and account activity to predict whether a customer is likely to leave the bank.

The project includes comprehensive data preprocessing with label encoding and one-hot encoding for categorical features, feature scaling, and a trained neural network model ready for deployment with a Streamlit application interface.

Key Features

• Binary classification using Artificial Neural Networks
• Data preprocessing with Label & One-Hot Encoding
• Feature scaling for numerical attributes
• Trained model saved in H5 format
• Interactive prediction interface with Streamlit