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Introduction

The aim of this project is to introduce a contextual investigation of utilization of one of the data mining techniques, neural network, in knowledge discovery from databases in the banking industry. Churn prediction models are created by academics and specialists to viably oversee and control customer churn so as to hold existing clients. As churn management is an important activity for organizations to hold faithful customers, the capacity to precisely anticipate customer churn is significant. In this project, we tend to use one of the data mining techniques, neural network to predict customer churn in bank. the main focus on customer churn is to determinate the clients who are at risk of going away and analyzing whether or not those customers are value retaining. we want to find out the customers who are probable to churn therefore bank ought to concentrate on those clients, and offer them product according to their needs.

Google Collab Link

https://colab.research.google.com/drive/1PjNBwQHNO4pOMmAEas3wjIgAS-drw8bJ

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