This project focuses on building a customer churn prediction model using an Artificial Neural Network (ANN). Customer churn is a critical metric for understanding why and how customers are leaving a business, and predicting this can help in implementing strategies to retain them.
We use the Telecom Customer Churn dataset from Kaggle to build a deep learning model for predicting customer churn. The model is developed using an Artificial Neural Network (ANN) to classify whether a customer is likely to churn or not.
We evaluate the model's performance using key metrics such as precision, recall, and accuracy. Additionally, we utilize a confusion matrix and a classification report to get deeper insights into the model's effectiveness and to understand its prediction capabilities. Dataset The dataset used in this project is the Telecom Customer Churn dataset, which can be accessed via the following link: https://www.kaggle.com/datasets/blastchar/telco-customer-churn