ML-Churn Prediction of a telecom Company

The goal of this project was to utilize classification models to predict whether or not a customer would churn. I went through the entire machine learning pipeline, discovered drivers of churn, and created many different models. Ultimately, my best Random Forest Classifier model was able to predict churned customers with an accuracy of about 80%.

Getting Started

1. Requirment.txt

• pandas
• scikit_learn
• Numpy
• Seaborn
• Flask
• Html

2.Fork this repository click on the symbol at the top right corner and Clone the forked repository.

  git clone https://github.com/<your-github-username>/Churn_Prediction_ML

3. Navigate to the project directory.

cd Churn_Prediction_ML
 

4. Create a New branch

git checkout -b <your_branch_name>
 

MAKE CHANGES IN SOURCE CODE

5. Stage your changes and commit

#Add changes to Index
git add .

#Commit to the local repo
git commit -m "<your_commit_message>"
 

6.Push your local commits to the remote repo.

git push -u origin <your_branch_name>
 

7. Create a PR !

8. Congratulations! Sit and relax, you've made your contribution to Churn_Prediction_ML.

Run on Local System

• Install packages given in requirements.txt (packages need Python 3.11.0).

pip install -r requirements.txt

• Run the below command to start your local server.

python run app.py

-The server will be running on your local computer on PORT:5000

Need help? Feel free to contact me @ amaddheshiya637@gmail.com

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