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ANN model which identifies why a customer is churning from a bank

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This project utilizes an Artificial Neural Network (ANN) to predict customer churn for a bank, based on various customer attributes like demographics, financial details, and account behavior. The model performs binary classification to identify whether a customer is likely to leave the bank (churn) or stay.

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This project uses an Artificial Neural Network (ANN) to predict customer churn based on input features such as Geography, Gender, Age, Balance, CreditScore, EstimatedSalary, Tenure, Number of Products, HasCreditCard, and IsActiveMember. The model classifies whether a customer is likely to churn or stay.

This project involves building an ANN-based churn model that can determine whether certain bank customers will continue using their service or not. The ANN model analyzes the relationship between customer churn & multiple independent variables affecting churn. Recommendations for improvements in service were suggested based on the results of the analysis. Skills and Tools Neural Networks, Classification, Keras, Tensorflow

Client-Retention-Insight is a churn classification project to predict whether the customer will Exited or not using the ANN implementation by tensorflow. We have also performed regression on the EstimatedSalary feature and done the HyperparameterTunning to find the best possible parameters for the model.

Churn Classification (ANN)

Churn-rate ANN classification

this is ann classification churn

Here I've created a simple ann which is trained on Churn Modelling dataset

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This project involves building an Artificial Neural Network (ANN) model to predict customer churn — whether a customer is likely to leave a company's services. The dataset used is a typical Churn Modeling Dataset, which contains customer demographics, account information, and behavioral data from a telecom or banking domain.

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Customer Churn Prediction: This project uses a neural network to predict customer churn based on demographic and account data. It also visualizes churn probability, identifies reasons for potential churn, and provides retention strategies in a user-friendly interface.

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Customer Churn Prediction using an ANN model built with TensorFlow. Data is preprocessed with encoding and scaling. The model is deployed via a Streamlit app where users can input customer details to predict churn probability. The project includes data preprocessing, model training, and deployment.

Churn Prediction using Tensorflow and keras

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This is a simple ANN deep learning classification technique

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Prediction with ann trained model and churn