This project takes a dataset of 10000 customers and their 12 attributes like their age, gender, geography etc. Feature selection and data preprocessing is done on the dataset and fed into a 3 layer sequential neural network. The trained model achieves about 85% accuracy on both train and test sets.
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This project takes a dataset of 10000 customers and their 12 attributes like their age, gender, geography etc. Feature selection and data preprocessing is done on the dataset and fed into a 3 layer sequential neural network. The trained model achieves about 85% accuracy on both train and test sets.
uday147/customer_churn_prediction
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This project takes a dataset of 10000 customers and their 12 attributes like their age, gender, geography etc. Feature selection and data preprocessing is done on the dataset and fed into a 3 layer sequential neural network. The trained model achieves about 85% accuracy on both train and test sets.
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