TatevKaren/artificial-neural-network-business_case_study

Business Case Study to predict customer churn rate based on Artificial Neural Network (ANN), with TensorFlow and Keras in Python. This is a customer churn analysis that contains training, testing, and evaluation of an ANN model. (Includes: Case Study Paper, Code)

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The implementation uses a three-layer architecture with Rectifier activation in hidden layers and Sigmoid output activation, optimized via Adam optimizer with Binary Cross Entropy loss over 100 epochs on batches of 25. Beyond the predictive model, the repository includes a detailed academic paper documenting the theoretical foundations of ANNs and their advantages over multiple linear regression for non-linear pattern recognition. The dataset comprises 10,000 anonymized bank customer records with demographic and behavioral features, enabling reproducible evaluation of churn prediction performance.

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May 04, 2021

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