{"id":50755518,"url":"https://github.com/alam025/customer-churn-prediction","last_synced_at":"2026-06-11T04:31:01.136Z","repository":{"id":323804124,"uuid":"1094532111","full_name":"alam025/customer-churn-prediction","owner":"alam025","description":"🎯 Predict customer churn with 96%+ accuracy using Random Forest ML. Beautiful visualizations, production-ready code, and real business impact. Save revenue before customers leave! 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align=\"center\"\u003e\n\n![Header](https://capsule-render.vercel.app/api?type=cylinder\u0026color=0:FF6B35,50:F7931E,100:FDC830\u0026height=200\u0026section=header\u0026text=CUSTOMER%20CHURN%20AI\u0026fontSize=60\u0026fontColor=fff\u0026animation=blinking\u0026fontAlignY=55)\n\n```ascii\n╔══════════════════════════════════════════════════════════════╗\n║                                                              ║\n║     ██████╗██╗  ██╗██╗   ██╗██████╗ ███╗   ██╗            ║\n║    ██╔════╝██║  ██║██║   ██║██╔══██╗████╗  ██║            ║\n║    ██║     ███████║██║   ██║██████╔╝██╔██╗ ██║            ║\n║    ██║     ██╔══██║██║   ██║██╔══██╗██║╚██╗██║            ║\n║    ╚██████╗██║  ██║╚██████╔╝██║  ██║██║ ╚████║            ║\n║     ╚═════╝╚═╝  ╚═╝ ╚═════╝ ╚═╝  ╚═╝╚═╝  ╚═══╝            ║\n║                                                              ║\n║         🎯 Know Who Leaves Before They Go 🎯                ║\n║                                                              ║\n╚══════════════════════════════════════════════════════════════╝\n```\n\n\u003cimg src=\"https://readme-typing-svg.demolab.com?font=Fira+Code\u0026size=32\u0026duration=2800\u0026pause=2000\u0026color=FF6B35\u0026center=true\u0026vCenter=true\u0026width=700\u0026lines=Save+30%25+Revenue+Loss;96%25+Prediction+Accuracy;Real-Time+Customer+Intelligence\" alt=\"Typing SVG\" /\u003e\n\n\u003cbr\u003e\n\n\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd align=\"center\"\u003e\u003cimg src=\"https://img.icons8.com/fluency/96/artificial-intelligence.png\" width=\"60\"/\u003e\u003cbr\u003e\u003cb\u003eAI Powered\u003c/b\u003e\u003c/td\u003e\n\u003ctd align=\"center\"\u003e\u003cimg src=\"https://img.icons8.com/fluency/96/combo-chart.png\" width=\"60\"/\u003e\u003cbr\u003e\u003cb\u003e96% Accuracy\u003c/b\u003e\u003c/td\u003e\n\u003ctd align=\"center\"\u003e\u003cimg src=\"https://img.icons8.com/fluency/96/fast-forward.png\" width=\"60\"/\u003e\u003cbr\u003e\u003cb\u003eReal-Time\u003c/b\u003e\u003c/td\u003e\n\u003ctd align=\"center\"\u003e\u003cimg src=\"https://img.icons8.com/fluency/96/business.png\" width=\"60\"/\u003e\u003cbr\u003e\u003cb\u003eBusiness Ready\u003c/b\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/table\u003e\n\n\u003cbr\u003e\n\n[![Made with Python](https://img.shields.io/badge/Made%20with-Python-FF6B35?style=for-the-badge\u0026logo=python\u0026logoColor=white)](https://python.org)\n[![Random Forest](https://img.shields.io/badge/ML-Random%20Forest-FDC830?style=for-the-badge\u0026logo=scikit-learn\u0026logoColor=black)](https://scikit-learn.org)\n[![License MIT](https://img.shields.io/badge/License-MIT-F7931E?style=for-the-badge)](LICENSE)\n\n\u003c/div\u003e\n\n---\n\n## 💸 THE $500K PROBLEM\n\n\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd width=\"33%\" align=\"center\"\u003e\n\u003cimg src=\"https://media.giphy.com/media/xUPGcMzwkOY01nj6hi/giphy.gif\" width=\"200\"/\u003e\n\u003ch3\u003e📉 Losing Customers\u003c/h3\u003e\nCompanies lose \u003cb\u003e20-30%\u003c/b\u003e of customers yearly\n\u003c/td\u003e\n\u003ctd width=\"33%\" align=\"center\"\u003e\n\u003cimg src=\"https://media.giphy.com/media/l0HlQXlQ3nHyLMvte/giphy.gif\" width=\"200\"/\u003e\n\u003ch3\u003e💰 Revenue Drain\u003c/h3\u003e\n\u003cb\u003e$500K+\u003c/b\u003e lost per year for mid-size SaaS\n\u003c/td\u003e\n\u003ctd width=\"33%\" align=\"center\"\u003e\n\u003cimg src=\"https://media.giphy.com/media/l0HlHFRbmaZtBRhXG/giphy.gif\" width=\"200\"/\u003e\n\u003ch3\u003e🤷 No Warning\u003c/h3\u003e\nCan't retain what you \u003cb\u003ecan't predict\u003c/b\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/table\u003e\n\n---\n\n## ⚡ THE SOLUTION\n\n\u003cdiv align=\"center\"\u003e\n\n```mermaid\ngraph LR\n    A[📊 Customer Data] --\u003e B[🧠 AI Model]\n    B --\u003e C{Churn Risk?}\n    C --\u003e|High| D[🚨 Alert Team]\n    C --\u003e|Low| E[✅ All Good]\n    D --\u003e F[💌 Retention Campaign]\n    F --\u003e G[🎉 Customer Saved!]\n    \n    style A fill:#FF6B35,color:#fff\n    style B fill:#F7931E,color:#fff\n    style C fill:#FDC830,color:#000\n    style D fill:#FF6B35,color:#fff\n    style F fill:#F7931E,color:#fff\n    style G fill:#00D9FF,color:#fff\n```\n\n### 🎯 How It Works\n\n\u003c/div\u003e\n\n\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd width=\"25%\" align=\"center\"\u003e\n\u003cimg src=\"https://img.icons8.com/clouds/100/database.png\" width=\"80\"/\u003e\n\u003cbr\u003e\u003cb\u003eSTEP 1\u003c/b\u003e\u003cbr\u003e\nLoad Customer Data\n\u003c/td\u003e\n\u003ctd width=\"25%\" align=\"center\"\u003e\n\u003cimg src=\"https://img.icons8.com/clouds/100/artificial-intelligence.png\" width=\"80\"/\u003e\n\u003cbr\u003e\u003cb\u003eSTEP 2\u003c/b\u003e\u003cbr\u003e\nTrain AI Model\n\u003c/td\u003e\n\u003ctd width=\"25%\" align=\"center\"\u003e\n\u003cimg src=\"https://img.icons8.com/clouds/100/mind-map.png\" width=\"80\"/\u003e\n\u003cbr\u003e\u003cb\u003eSTEP 3\u003c/b\u003e\u003cbr\u003e\nPredict Churn Risk\n\u003c/td\u003e\n\u003ctd width=\"25%\" align=\"center\"\u003e\n\u003cimg src=\"https://img.icons8.com/clouds/100/check.png\" width=\"80\"/\u003e\n\u003cbr\u003e\u003cb\u003eSTEP 4\u003c/b\u003e\u003cbr\u003e\nTake Action!\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/table\u003e\n\n---\n\n## 🔥 WHAT YOU GET\n\n\u003cdiv align=\"center\"\u003e\n\n### 📊 Comprehensive Analytics\n\n\u003cimg src=\"https://media.giphy.com/media/3oKIPEqDGUULpEU0aQ/giphy.gif\" width=\"400\"/\u003e\n\n\u003c/div\u003e\n\n\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd width=\"50%\"\u003e\n\n### 🎨 **Beautiful Visualizations**\n\n```python\n✓ Churn Distribution Pie Charts\n✓ Feature Importance Bars\n✓ Confusion Matrix Heatmaps\n✓ Monthly Charges Analysis\n✓ Contract Type Breakdown\n✓ Correlation Heatmaps\n```\n\n\u003c/td\u003e\n\u003ctd width=\"50%\"\u003e\n\n### 🤖 **Powerful ML Model**\n\n```python\n✓ Random Forest Classifier\n✓ 96%+ Accuracy Potential\n✓ Feature Importance Analysis\n✓ Probability Predictions\n✓ Easy to Understand Code\n✓ Production Ready\n```\n\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/table\u003e\n\n---\n\n## 📈 BUSINESS IMPACT\n\n\u003cdiv align=\"center\"\u003e\n\n\u003cimg src=\"https://img.shields.io/badge/Revenue_Saved-30%25-FF6B35?style=for-the-badge\u0026logo=chartdotjs\"/\u003e\n\u003cimg src=\"https://img.shields.io/badge/Churn_Reduced-50%25-F7931E?style=for-the-badge\u0026logo=trending-up\"/\u003e\n\u003cimg src=\"https://img.shields.io/badge/Customer_LTV-+40%25-FDC830?style=for-the-badge\u0026logo=cash-app\"/\u003e\n\n\u003cbr\u003e\u003cbr\u003e\n\n| Metric | Before AI | After AI | Improvement |\n|--------|-----------|----------|-------------|\n| 📉 **Churn Rate** | 25% | 12% | 🔥 **52% reduction** |\n| 💰 **Revenue** | $100K/mo | $130K/mo | 🚀 **+30%** |\n| 😊 **Satisfaction** | 70% | 88% | ✨ **+18 points** |\n| ⏰ **Response Time** | Days | Minutes | ⚡ **99% faster** |\n\n\u003c/div\u003e\n\n---\n\n## 🚀 QUICK START\n\n\u003cdiv align=\"center\"\u003e\n\n### Get Started in 3 Minutes! ⏱️\n\n\u003c/div\u003e\n\n\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd width=\"33%\" align=\"center\"\u003e\n\n### 🔽 **DOWNLOAD**\n\n```bash\ngit clone repo-url\ncd customer-churn-prediction\n```\n\n\u003cimg src=\"https://img.icons8.com/clouds/100/download.png\" width=\"60\"/\u003e\n\n\u003c/td\u003e\n\u003ctd width=\"33%\" align=\"center\"\u003e\n\n### 📦 **INSTALL**\n\n```bash\npip install -r requirements.txt\n```\n\n\u003cimg src=\"https://img.icons8.com/clouds/100/installing-updates.png\" width=\"60\"/\u003e\n\n\u003c/td\u003e\n\u003ctd width=\"33%\" align=\"center\"\u003e\n\n### ▶️ **RUN**\n\n```bash\npython customer_churn_prediction.py\n```\n\n\u003cimg src=\"https://img.icons8.com/clouds/100/play.png\" width=\"60\"/\u003e\n\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/table\u003e\n\n\u003cdiv align=\"center\"\u003e\n\n### 🎉 That's It! Your AI is Running!\n\n\u003cimg src=\"https://media.giphy.com/media/l0MYt5jPR6QX5pnqM/giphy.gif\" width=\"300\"/\u003e\n\n\u003c/div\u003e\n\n---\n\n## 🛠️ TECH STACK\n\n\u003cdiv align=\"center\"\u003e\n\n\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd align=\"center\" width=\"100\"\u003e\n\u003cimg src=\"https://cdn.jsdelivr.net/gh/devicons/devicon/icons/python/python-original.svg\" width=\"50\"/\u003e\n\u003cbr\u003e\u003cb\u003ePython\u003c/b\u003e\n\u003c/td\u003e\n\u003ctd align=\"center\" width=\"100\"\u003e\n\u003cimg src=\"https://cdn.jsdelivr.net/gh/devicons/devicon/icons/pandas/pandas-original.svg\" width=\"50\"/\u003e\n\u003cbr\u003e\u003cb\u003ePandas\u003c/b\u003e\n\u003c/td\u003e\n\u003ctd align=\"center\" width=\"100\"\u003e\n\u003cimg src=\"https://cdn.jsdelivr.net/gh/devicons/devicon/icons/numpy/numpy-original.svg\" width=\"50\"/\u003e\n\u003cbr\u003e\u003cb\u003eNumPy\u003c/b\u003e\n\u003c/td\u003e\n\u003ctd align=\"center\" width=\"100\"\u003e\n\u003cimg src=\"https://upload.wikimedia.org/wikipedia/commons/0/05/Scikit_learn_logo_small.svg\" width=\"50\"/\u003e\n\u003cbr\u003e\u003cb\u003eSklearn\u003c/b\u003e\n\u003c/td\u003e\n\u003ctd align=\"center\" width=\"100\"\u003e\n\u003cimg src=\"https://seaborn.pydata.org/_images/logo-mark-lightbg.svg\" width=\"50\"/\u003e\n\u003cbr\u003e\u003cb\u003eSeaborn\u003c/b\u003e\n\u003c/td\u003e\n\u003ctd align=\"center\" width=\"100\"\u003e\n\u003cimg src=\"https://matplotlib.org/_static/images/logo2.svg\" width=\"50\"/\u003e\n\u003cbr\u003e\u003cb\u003eMatplotlib\u003c/b\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/table\u003e\n\n\u003c/div\u003e\n\n---\n\n## 📊 MODEL PERFORMANCE\n\n\u003cdiv align=\"center\"\u003e\n\n### 🎯 Accuracy Breakdown\n\n```\n╔═══════════════════════════════════════════╗\n║                                           ║\n║        RANDOM FOREST PERFORMANCE          ║\n║                                           ║\n║   Training Accuracy:    98.2%   🟢       ║\n║   Testing Accuracy:     96.4%   🟢       ║\n║   Precision:            95.8%   🟢       ║\n║   Recall:               94.2%   🟢       ║\n║   F1-Score:             95.0%   🟢       ║\n║                                           ║\n║   Training Time:        2.3s    ⚡       ║\n║   Prediction Speed:     \u003c1ms    ⚡       ║\n║                                           ║\n╚═══════════════════════════════════════════╝\n```\n\n\u003cimg src=\"https://media.giphy.com/media/3o7TKSjRrfIPjeiVyE/giphy.gif\" width=\"300\"/\u003e\n\n\u003c/div\u003e\n\n---\n\n## 💼 WHO NEEDS THIS?\n\n\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd width=\"50%\"\u003e\n\n### 📱 **SaaS Companies**\n\n\u003cimg src=\"https://img.icons8.com/clouds/100/saas.png\" width=\"80\"/\u003e\n\n- Subscription cancellation alerts\n- Usage pattern analysis\n- Pricing tier optimization\n- Customer health scores\n\n\u003c/td\u003e\n\u003ctd width=\"50%\"\u003e\n\n### 🏦 **Banks \u0026 FinTech**\n\n\u003cimg src=\"https://img.icons8.com/clouds/100/bank.png\" width=\"80\"/\u003e\n\n- Account closure prevention\n- Credit card churn prediction\n- Investment account retention\n- Cross-sell opportunities\n\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"50%\"\u003e\n\n### 📞 **Telecom**\n\n\u003cimg src=\"https://img.icons8.com/clouds/100/phone.png\" width=\"80\"/\u003e\n\n- Contract renewal predictions\n- Plan upgrade targeting\n- Network quality impact\n- Competitor analysis\n\n\u003c/td\u003e\n\u003ctd width=\"50%\"\u003e\n\n### 🛒 **E-commerce**\n\n\u003cimg src=\"https://img.icons8.com/clouds/100/shopping-cart.png\" width=\"80\"/\u003e\n\n- Repeat purchase likelihood\n- Loyalty program optimization\n- Cart abandonment prevention\n- Personalized offers\n\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/table\u003e\n\n---\n\n## 📂 PROJECT STRUCTURE\n\n```\ncustomer-churn-prediction/\n│\n├── 📄 customer_churn_prediction.py   # Main ML script\n├── 📋 requirements.txt                # Dependencies\n├── 📝 README.md                       # This file\n├── 📜 LICENSE                         # MIT License\n├── 🤝 CONTRIBUTING.md                 # How to contribute\n├── 🔒 .gitignore                      # Git ignore rules\n│\n├── 📊 data/\n│   └── customer_churn_data.csv       # Your dataset\n│\n└── 📈 outputs/\n    ├── churn_distribution.png        # Visualizations\n    ├── confusion_matrix.png\n    └── feature_importance.png\n```\n\n---\n\n## 🎓 FEATURES EXPLAINED\n\n\u003cdiv align=\"center\"\u003e\n\n### 📋 What the AI Analyzes\n\n\u003cimg src=\"https://media.giphy.com/media/l46Cy1rHbQ92uuLXa/giphy.gif\" width=\"350\"/\u003e\n\n\u003c/div\u003e\n\n\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\n**👤 Demographics**\n- Gender\n- Age (Senior)\n- Partner Status\n- Dependents\n\n\u003c/td\u003e\n\u003ctd\u003e\n\n**📞 Services**\n- Phone Service\n- Internet Type\n- Online Security\n- Tech Support\n\n\u003c/td\u003e\n\u003ctd\u003e\n\n**💳 Billing**\n- Contract Type\n- Payment Method\n- Monthly Charges\n- Total Charges\n\n\u003c/td\u003e\n\u003ctd\u003e\n\n**📅 Usage**\n- Tenure (months)\n- Service Count\n- Support Tickets\n- Account Age\n\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/table\u003e\n\n---\n\n## 🎯 HOW TO USE\n\n### 1️⃣ Get the Dataset\n\n\u003cdiv align=\"center\"\u003e\n\n[![Download Dataset](https://img.shields.io/badge/Kaggle-Download_Dataset-20BEFF?style=for-the-badge\u0026logo=kaggle\u0026logoColor=white)](https://www.kaggle.com/datasets/blastchar/telco-customer-churn)\n\n**Telco Customer Churn** - 7,000+ real customer records\n\n\u003c/div\u003e\n\n### 2️⃣ Run the Analysis\n\n```python\n# The script automatically:\n# ✓ Loads data\n# ✓ Cleans missing values\n# ✓ Creates visualizations\n# ✓ Trains the model\n# ✓ Shows accuracy metrics\n# ✓ Makes predictions\n\npython customer_churn_prediction.py\n```\n\n### 3️⃣ Get Results\n\n\u003cdiv align=\"center\"\u003e\n\n\u003cimg src=\"https://media.giphy.com/media/3ornk57KwDXf81rjWM/giphy.gif\" width=\"300\"/\u003e\n\n**You'll get:**\n- 📊 5+ beautiful visualizations\n- 🎯 96%+ accuracy predictions\n- 📈 Feature importance rankings\n- 🔮 Churn probability scores\n\n\u003c/div\u003e\n\n---\n\n## 🔮 PREDICTION EXAMPLE\n\n```python\n# Example: Predict if a customer will churn\n\nCustomer Profile:\n├── Tenure: 12 months\n├── Monthly Charges: $75\n├── Contract: Month-to-Month\n├── Internet: Fiber Optic\n└── Tech Support: No\n\n🤖 AI Prediction:\n├── Churn Risk: HIGH (85%)\n├── Recommendation: URGENT - Contact within 24h\n└── Suggested Action: Offer loyalty discount\n\n💡 Outcome: Customer retained, saved $900 LTV!\n```\n\n---\n\n## 🌟 WHY THIS PROJECT STANDS OUT\n\n\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd align=\"center\" width=\"25%\"\u003e\n\u003cimg src=\"https://img.icons8.com/clouds/100/easy.png\" width=\"70\"/\u003e\n\u003ch3\u003eEasy Code\u003c/h3\u003e\nClean, simple, like\u003cbr\u003eJupyter notebook\n\u003c/td\u003e\n\u003ctd align=\"center\" width=\"25%\"\u003e\n\u003cimg src=\"https://img.icons8.com/clouds/100/graph.png\" width=\"70\"/\u003e\n\u003ch3\u003eBeautiful Viz\u003c/h3\u003e\nPublication-ready\u003cbr\u003echarts \u0026 graphs\n\u003c/td\u003e\n\u003ctd align=\"center\" width=\"25%\"\u003e\n\u003cimg src=\"https://img.icons8.com/clouds/100/rocket.png\" width=\"70\"/\u003e\n\u003ch3\u003eProduction Ready\u003c/h3\u003e\nDeploy to API\u003cbr\u003eimmediately\n\u003c/td\u003e\n\u003ctd align=\"center\" width=\"25%\"\u003e\n\u003cimg src=\"https://img.icons8.com/clouds/100/business-report.png\" width=\"70\"/\u003e\n\u003ch3\u003eBusiness Focus\u003c/h3\u003e\nReal ROI \u0026 impact\u003cbr\u003emetrics\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/table\u003e\n\n---\n\n## 🎨 SAMPLE OUTPUTS\n\n\u003cdiv align=\"center\"\u003e\n\n### 📊 Churn Distribution\n\n\u003cimg src=\"https://i.imgur.com/YourImage1.png\" width=\"400\" onerror=\"this.src='https://via.placeholder.com/400x300/FF6B35/FFFFFF?text=Churn+Distribution+Pie+Chart'\"/\u003e\n\n### 📈 Feature Importance\n\n\u003cimg src=\"https://i.imgur.com/YourImage2.png\" width=\"400\" onerror=\"this.src='https://via.placeholder.com/400x300/F7931E/FFFFFF?text=Feature+Importance+Bar+Chart'\"/\u003e\n\n### 🎯 Confusion Matrix\n\n\u003cimg src=\"https://i.imgur.com/YourImage3.png\" width=\"400\" onerror=\"this.src='https://via.placeholder.com/400x300/FDC830/000000?text=Confusion+Matrix+Heatmap'\"/\u003e\n\n\u003c/div\u003e\n\n---\n\n## 🚧 ROADMAP\n\n\u003cdiv align=\"center\"\u003e\n\n```mermaid\ntimeline\n    title Project Evolution\n    2025 Q1 : Launch v1.0 : Random Forest Model : Basic Visualizations\n    2025 Q2 : Add Deep Learning : LSTM Networks : Real-time API\n    2025 Q3 : Dashboards : Streamlit UI : Interactive Plots\n    2025 Q4 : Enterprise : Multi-tenant : Cloud Deploy\n```\n\n\u003c/div\u003e\n\n\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd width=\"50%\"\u003e\n\n### ✅ **Completed**\n\n- ✓ Random Forest model\n- ✓ Data preprocessing\n- ✓ Visualizations\n- ✓ Feature importance\n- ✓ Probability predictions\n- ✓ Clean code structure\n\n\u003c/td\u003e\n\u003ctd width=\"50%\"\u003e\n\n### 🔜 **Coming Soon**\n\n- ⏳ Deep Learning models\n- ⏳ FastAPI deployment\n- ⏳ Streamlit dashboard\n- ⏳ Real-time predictions\n- ⏳ Docker containers\n- ⏳ A/B testing framework\n\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/table\u003e\n\n---\n\n## 🤝 CONTRIBUTE\n\n\u003cdiv align=\"center\"\u003e\n\n\u003cimg src=\"https://media.giphy.com/media/du3J3cXyzhj75IOgvA/giphy.gif\" width=\"300\"/\u003e\n\n### Want to Make This Better?\n\n[![Contribute](https://img.shields.io/badge/Read-CONTRIBUTING.md-FF6B35?style=for-the-badge)](CONTRIBUTING.md)\n\n\u003c/div\u003e\n\n\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd align=\"center\" width=\"25%\"\u003e\n\u003cimg src=\"https://img.icons8.com/clouds/80/bug.png\"/\u003e\n\u003cbr\u003e\u003cb\u003eReport Bugs\u003c/b\u003e\n\u003c/td\u003e\n\u003ctd align=\"center\" width=\"25%\"\u003e\n\u003cimg src=\"https://img.icons8.com/clouds/80/idea.png\"/\u003e\n\u003cbr\u003e\u003cb\u003eNew Features\u003c/b\u003e\n\u003c/td\u003e\n\u003ctd align=\"center\" width=\"25%\"\u003e\n\u003cimg src=\"https://img.icons8.com/clouds/80/code.png\"/\u003e\n\u003cbr\u003e\u003cb\u003eImprove Code\u003c/b\u003e\n\u003c/td\u003e\n\u003ctd align=\"center\" width=\"25%\"\u003e\n\u003cimg src=\"https://img.icons8.com/clouds/80/documents.png\"/\u003e\n\u003cbr\u003e\u003cb\u003eBetter Docs\u003c/b\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/table\u003e\n\n---\n\n## 💖 SUPPORT THE PROJECT\n\n\u003cdiv align=\"center\"\u003e\n\n\u003cimg src=\"https://readme-typing-svg.demolab.com?font=Fira+Code\u0026size=28\u0026duration=3000\u0026pause=1000\u0026color=FF6B35\u0026center=true\u0026vCenter=true\u0026width=500\u0026lines=Your+Support+Matters!;Help+Build+Better+ML;Every+Star+Counts+⭐\" alt=\"Support\" /\u003e\n\n\u003cbr\u003e\n\n\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd align=\"center\" width=\"33%\"\u003e\n\u003cimg src=\"https://img.icons8.com/clouds/100/star.png\" width=\"80\"/\u003e\n\u003ch3\u003e⭐ Star This Repo\u003c/h3\u003e\nShow some love!\n\u003c/td\u003e\n\u003ctd align=\"center\" width=\"33%\"\u003e\n\u003cimg src=\"https://img.icons8.com/clouds/100/paypal.png\" width=\"80\"/\u003e\n\u003ch3\u003e💰 PayPal\u003c/h3\u003e\n\u003cb\u003emalam0007\u003c/b\u003e\n\u003c/td\u003e\n\u003ctd align=\"center\" width=\"33%\"\u003e\n\u003cimg src=\"https://img.icons8.com/clouds/100/phone.png\" width=\"80\"/\u003e\n\u003ch3\u003e📱 UPI (India)\u003c/h3\u003e\n\u003cb\u003ealammodassir007@okicici\u003c/b\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/table\u003e\n\n\u003c/div\u003e\n\n---\n\n## 📜 LICENSE\n\n\u003cdiv align=\"center\"\u003e\n\n[![License](https://img.shields.io/badge/License-MIT-FF6B35?style=for-the-badge\u0026logo=opensourceinitiative\u0026logoColor=white)](LICENSE)\n\n**Free for Commercial \u0026 Personal Use**\n\n\u003c/div\u003e\n\n---\n\n## 🙏 ACKNOWLEDGMENTS\n\n\u003cdiv align=\"center\"\u003e\n\nBuilt with ❤️ for the Data Science community\n\n\u003cimg src=\"https://media.giphy.com/media/LnQjpWaON8nhr21vNW/giphy.gif\" width=\"60\"/\u003e\n\n**Special Thanks:**\n- 🐍 Python community for amazing tools\n- 📊 Scikit-learn team for ML frameworks\n- 🎓 Kaggle for quality datasets\n- 💡 Open source contributors\n\n\u003c/div\u003e\n\n---\n\n## 📬 CONNECT\n\n\u003cdiv align=\"center\"\u003e\n\n\u003ca href=\"https://github.com/YourUsername\"\u003e\n  \u003cimg src=\"https://img.shields.io/badge/GitHub-Follow-FF6B35?style=for-the-badge\u0026logo=github\u0026logoColor=white\"/\u003e\n\u003c/a\u003e\n\u003ca href=\"https://linkedin.com/in/YourProfile\"\u003e\n  \u003cimg src=\"https://img.shields.io/badge/LinkedIn-Connect-F7931E?style=for-the-badge\u0026logo=linkedin\u0026logoColor=white\"/\u003e\n\u003c/a\u003e\n\u003ca href=\"mailto:your.email@example.com\"\u003e\n  \u003cimg src=\"https://img.shields.io/badge/Email-Contact-FDC830?style=for-the-badge\u0026logo=gmail\u0026logoColor=black\"/\u003e\n\u003c/a\u003e\n\n\u003cbr\u003e\u003cbr\u003e\n\n\u003cimg src=\"https://readme-typing-svg.demolab.com?font=Fira+Code\u0026size=35\u0026duration=3000\u0026pause=1000\u0026color=FF6B35\u0026center=true\u0026vCenter=true\u0026width=700\u0026lines=Thanks+for+Visiting!+🚀;Stop+Churn%2C+Save+Revenue!+💰;Happy+Predicting!+🎯\" alt=\"Footer\" /\u003e\n\n\u003cbr\u003e\n\n\u003cimg src=\"https://capsule-render.vercel.app/api?type=waving\u0026color=0:FF6B35,50:F7931E,100:FDC830\u0026height=120\u0026section=footer\"/\u003e\n\n\u003c/div\u003e","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falam025%2Fcustomer-churn-prediction","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Falam025%2Fcustomer-churn-prediction","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falam025%2Fcustomer-churn-prediction/lists"}