{"id":23564073,"url":"https://github.com/coder5omkar/logistic-regression-customer-churn-prediction","last_synced_at":"2026-04-20T03:31:10.419Z","repository":{"id":269698194,"uuid":"908182840","full_name":"coder5omkar/Logistic-Regression-Customer-Churn-Prediction","owner":"coder5omkar","description":"This project uses Logistic Regression to predict customer churn in the telecom industry. 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The dataset includes churn data, customer data,\ninternet data. We preprocess the data, perform exploratory analysis, and build a Logistic Regression \nmodel using Scikit-learn. The model predicts whether a customer will churn or stay. Evaluation metrics like accuracy, precision, and \nrecall are used to assess performance. Visualizations and insights help interpret model results. The project is implemented in Python with \nlibraries such as Pandas, NumPy, and Matplotlib. To run, clone the repository, install dependencies, and run the Jupyter notebook for full \nanalysis and predictions.\n```\n\n## 🛠️ Technologies Used\n- [Python](https://www.python.org/) version: 3.12.4\n- [Numpy](https://numpy.org/) version: 1.26.4\n- [Pandas](https://pandas.pydata.org/) version: 2.2.2\n- [Seaborn](https://seaborn.pydata.org/) version: 0.13.2\n- [Matplotlib](https://matplotlib.org/) version: 3.9.2\n- [scikit-learn](https://scikit-learn.org/) version: 1.5.1\n- [statsmodels](https://statsmodels.org/) version: 0.14.2\n\n## 🚀 **Getting Started** (In Anaconda PowerShell Prompt)\n\n1. Clone the repository:\n   ```bash\n   git clone https://github.com/coder5omkar/Logistic-Regression-Customer-Churn-Prediction.git\n   ```\n\n2. Navigate to the project directory:\n   ```bash\n   cd Logistic-Regression-Customer-Churn-Prediction\n   ```\n\n3. Open the notebook:\n   ```bash\n   jupyter notebook LRG.ipynb\n   ```\n\n---\n\n\n## 🤝 Acknowledgements\n- This project was inspired by IIT-B AI-ML program at Upgrad\n\nDeveloped as part of the ML-1 Module assignment required for Post Graduate Diploma in Machine Learning and AI - IIIT,Bangalore.\n\nThis project is open source and available under the [MIT License](https://github.com/coder5omkar/Logistic-Regression-Customer-Churn-Prediction/blob/master/licence.txt).\n\n\n## Contact\nCreated by [@in/omkaramale](https://github.com/coder5omkar) - feel free to contact me!\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcoder5omkar%2Flogistic-regression-customer-churn-prediction","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcoder5omkar%2Flogistic-regression-customer-churn-prediction","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcoder5omkar%2Flogistic-regression-customer-churn-prediction/lists"}