ahmedshahriar / Telco-Customer-Churn-Prediction-Streamlit-App

This streamlit app predicts the churn rate using Gradient Boosting models (XGBoost, Catboost, LightGBM) on IBM Customer Churn Dataset

Telco Customer Churn Prediction Streamlit App

This app was featured in Streamlit Weekly Roundup

Install packages pip install requirements.txt

Requires

pandas==1.3.3
numpy~=1.21.2
matplotlib==3.4.3
streamlit==0.88.0
xgboost==0.90
catboost==1.0.0
lightgbm==2.2.3
scikit-learn==1.0.1

To run this app streamlit run app.py

Dataset Source

• Kaggle Dataset URL
• GitHub Dataset URL

GitHub Project Repository

• Customer-Churn-Prediction

View The Project

• View the Project in Jupyter Notebook Html :

• Open The GitHub Project in Binder :

View this notebook on kaggle

1. Churn Prediction I : EDA+Statistical Analysis
2. Churn Prediction II : Triple Boost Stacking+ Optuna