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This repository provides a simple implementation of churn prediction using Artificial Neural Networks for beginners in deep learning.

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Churn Modelling

This repository contains code for predicting Customer Churn using Artificial Neural Networks (ANN) implemented with TensorFlow and Keras. The dataset used for this analysis is sourced from a fictional bank's customer data.

Overview

Customer churn, also known as customer attrition, refers to the phenomenon where customers cease doing business with a company. Predicting churn is crucial for businesses to identify at-risk customers and take proactive measures to retain them.

Artificial Neural Network

Artificial Neural Network Hyperparameter Tuned

Getting Started

To get started with the project, follow these steps:

  1. Clone the repository:
git clone https://github.com/SannketNikam/Churn-Modelling
  1. Install dependencies:
pip install -r requirements.txt

Conclusion

Predicting customer churn is essential for businesses to devise effective retention strategies. In this project the Artificial Neural Network models demonstrate promising performance in predicting customer churn using bank customer data. Further optimizations and fine-tuning could potentially enhance the predictive accuracy of the models.

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This repository provides a simple implementation of churn prediction using Artificial Neural Networks for beginners in deep learning.

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