https://github.com/anusha-me/customer_churn_analysis
Predict and analyze telecom customer churn using machine learning techniques and business dashboards. This end-to-end project includes data preprocessing, EDA, model evaluation (SVM, XGBoost), real-time Streamlit deployment, and Power BI dashboard reporting. Built for actionable insights and decision support.
https://github.com/anusha-me/customer_churn_analysis
churn-prediction classification-model customer-analytics dashboard data-science eda machine-learning powerbi predictive-analytics python scikit-learn streamlit svm telecom xgboost
Last synced: 2 months ago
JSON representation
Predict and analyze telecom customer churn using machine learning techniques and business dashboards. This end-to-end project includes data preprocessing, EDA, model evaluation (SVM, XGBoost), real-time Streamlit deployment, and Power BI dashboard reporting. Built for actionable insights and decision support.
- Host: GitHub
- URL: https://github.com/anusha-me/customer_churn_analysis
- Owner: Anusha-me
- License: mit
- Created: 2025-06-10T15:41:44.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-06-10T16:27:32.000Z (4 months ago)
- Last Synced: 2025-06-10T17:33:34.701Z (4 months ago)
- Topics: churn-prediction, classification-model, customer-analytics, dashboard, data-science, eda, machine-learning, powerbi, predictive-analytics, python, scikit-learn, streamlit, svm, telecom, xgboost
- Language: Jupyter Notebook
- Homepage:
- Size: 3.91 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- License: LICENSE.md