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The project involves developing a machine learning model to predict customer churn using Artificial Neural Networks (ANN). Customer churn refers to the loss of clients or subscribers. Accurately predicting churn helps businesses implement strategies to retain customers, thereby increasing profitability.

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ShubhaMahobia/ANN-Classification

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CHURN RATE PREDICTION - ANN

The project involves developing a machine learning model to predict customer churn using Artificial Neural Networks (ANN). Customer churn refers to the loss of clients or subscribers. Accurately predicting churn helps businesses implement strategies to retain customers, thereby increasing profitability.

Live Deployement

Live Demo - https://ann-classification-churnrate-qjzu6hqbh4epstlaylkypc.streamlit.app/

Run Locally

  1. Clone this repo into your system.
  2. Create virtual environment using the command -
 python -m venv env
  1. Now install all the packages which are listed in requirements.txt
 pip install -r requirements.txt
  1. Now run all the cell in the Experiments.ipynb And Prediction.ipynb as per your need.

  2. To run on streamlit -

    streamlit run ChurnRate.py

Tech Stack

Frontend Client: Streamlit Services

Model Used: Artificial Neural Network - ANN

Dataset Used: Custom

Feedback

If you have any feedback or just to say Hi!, please reach out to me at mahobiashubham4@gmail.com

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The project involves developing a machine learning model to predict customer churn using Artificial Neural Networks (ANN). Customer churn refers to the loss of clients or subscribers. Accurately predicting churn helps businesses implement strategies to retain customers, thereby increasing profitability.

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