{"id":19580640,"url":"https://github.com/blurred-machine/ann-based-banking-churn-prediction","last_synced_at":"2025-04-27T08:32:22.116Z","repository":{"id":39728321,"uuid":"257800657","full_name":"blurred-machine/ANN-based-Banking-Churn-Prediction","owner":"blurred-machine","description":"This repository will have all the necessary files for machine learning and deep learning based Banking Churn Prediction ANN model which will analyze tha probablity for a customer to leave the bank services in near future. 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ANN-based-Banking-Churn-Prediction\n- This repository will have complete machine learning and deep learning based banking churn prediction ANN model which will analyze tha probablity for a customer to leave.\n- The project was deployed on Google Cloud Platform as well as completely tested on Localhost.\n\u003c/br\u003e\n\n## Project Description\n### Welcome Screen\n- The main welcome screen is made in **HTML5** and **CSS3** with a basic and simple design.\n- Here is the main screen for the **Bank Churn Prediction** Interface for the bank admin.\u003c/br\u003e\n\n![Welcome Screen](https://github.com/paras009/ANN-based-Banking-Churn-Prediction/blob/master/images/3welcome_screen.PNG)\n\n### Bank Admin Input\n- The bank employee has to enter the details of the customer whose churn they want to analyze.\n- Below is the screenshot of the input being filled by bank employee.\u003c/br\u003e\n\n![Filled Screen](https://github.com/paras009/ANN-based-Banking-Churn-Prediction/blob/master/images/4filled_index.png)\n\n## Analysis and Accuracy\n- The Prediction engine is built over a deep **Artificial Neural Network** backed with **[Keras](https://www.tensorflow.org/guide/keras)**.\n- I have achieved an accuracy of around **~85%** on both training and testing data.\u003c/br\u003e\n- The ANN is trained over K-fold cross validation testing over 10 rounds to find if it was underfit or overfit over the data based on the variance betweent the accuracies of the 10 rotations.\n- The model is Tuned over the Hyerparametes to find the best **batch_size**, **epoch** and **optimizer** for generating the best possible combination for best fit model.\n\n![Accuracy Python Console](https://github.com/paras009/ANN-based-Banking-Churn-Prediction/blob/master/images/1accuracy_console.PNG)\n\n## Deployment and Production\n-  The **API interfacing** for the deplyment on [Localhost](http://localhost:8080/index) is done using [Flask](https://flask.palletsprojects.com/en/1.1.x/).\n- The server is run on Local system during the staging of the project.\n- Older deployment was done on [Google Cloud Platform](https://cloud.google.com/)\n- Recently, the final deployment was done on **Heloku** platform and can be accessed from the link below.\n- LINK: [https://banking-churn-pediction](https://banking-churn-pediction.herokuapp.com)\n\n## Predictions\n- The final prediction of the model is the percentage of churn for that customer.\n-  The prediction signifies the chances of the customer to leave the services of the bank which makes the bank to _focus more on such such customers_ and try to retain them using **[Sales and Marketing strategies](https://github.com/paras009/Sales-and-Marketing-Analytics)** about which I have worked in this [GitHub](https://github.com/paras009/Sales-and-Marketing-Analytics) module.\u003c/br\u003e\n\n![Prediction Screenshot](https://github.com/paras009/ANN-based-Banking-Churn-Prediction/blob/master/images/5prediction.PNG)\n\n## Contribution\n- The project is built completely by Paras Varshney.\u003c/br\u003e\nConnect on [LinkedIn](https://www.linkedin.com/in/pv009)\u003c/br\u003e\nFollow on [Medium](https://medium.com/@pv009)\u003c/br\u003e\nFollow on [Github](https://github.com/paras009)\u003c/br\u003e\n\n#### Thank You!\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fblurred-machine%2Fann-based-banking-churn-prediction","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fblurred-machine%2Fann-based-banking-churn-prediction","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fblurred-machine%2Fann-based-banking-churn-prediction/lists"}