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Predicting churn helps in improving retention, reducing losses, and increasing profitability.\n\n💡 Features\n\n✅ Predict churn based on 19 input features\n✅ Clean and responsive UI with Bootstrap\n✅ Machine learning model trained and integrated\n✅ Preprocessing pipeline for real-time predictions\n✅ Probability-based feedback with clear messaging\n\n🖥️ Tech Stack\nLayer\tTools Used\nFrontend\tHTML, CSS, Bootstrap\nBackend\tFlask (Python)\nML Model\tPickle (trained model), Scikit-learn\nData Handling\tPandas, Custom Preprocessing\n\n🔍 Model Info\n\nTrained on Telco Customer Churn Dataset (Kaggle)\n\nPreprocessing: Label encoding, handling missing values\n\nAlgorithm: RandomForestClassifier (customizable)\n\nEvaluation: Accuracy, ROC-AUC, Precision-Recall\n\n🤝 Contributing\n\nContributions are welcome!\nFeel free to fork the repo and open a PR with improvements 🚀\n\n📃 License\n\nMIT License © 2025 Your Name\n\n🌟 Show Your Support\n\nIf you found this project useful or interesting, give it a ⭐ and share it with others!\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fritesh-cloud%2Fai-powered-customer-churn-prediction","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fritesh-cloud%2Fai-powered-customer-churn-prediction","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fritesh-cloud%2Fai-powered-customer-churn-prediction/lists"}