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.

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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.

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Feb 20, 2024

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