📱 Telecom Customer Churn Prediction
An end-to-end machine learning system for predicting customer churn in the telecommunications industry.
The project covers the complete ML lifecycle, including data preprocessing, exploratory data analysis, feature engineering, model training, hyperparameter optimization, evaluation, and deployment.
🚀 Key Features
- 📊 Exploratory Data Analysis
- 🧹 Data preprocessing and feature engineering
- 🤖 Machine learning classification
- ⚙️ Hyperparameter optimization
- 📈 Model evaluation
- 🔮 Churn prediction
- 🌐 Interactive Streamlit application
- 🔄 End-to-end ML pipeline
🖼️ Project Preview
🏗️ System Architecture
🧠 ML Pipeline
Customer Data
↓
Data Validation
↓
Exploratory Data Analysis
↓
Data Preprocessing
↓
Feature Engineering
↓
Model Training
↓
Hyperparameter Optimization
↓
Model Evaluation
↓
Churn Prediction
↓
Deployment
📋 Model Details
| Property | Details |
|---|---|
| Task | Binary Classification |
| Domain | Telecommunications |
| Target | Customer Churn |
| Framework | Scikit-learn |
| Data Type | Tabular |
| Optimization | Hyperparameter Tuning |
| Deployment | Streamlit |
📤 Output
The model predicts whether a customer is likely to churn:
Prediction: Churn / No Churn
Probability: <VALUE>
💻 Run Locally
git clone https://github.com/mdzaheerjk/Telecom-Customer-Churn-Prediction.git
cd Telecom-Customer-Churn-Prediction
pip install -r requirements.txt
streamlit run app.py
🛠️ Tech Stack
Python • Pandas • NumPy • Scikit-learn • Matplotlib • Seaborn • Optuna • Streamlit
⚠️ Limitations
Model performance depends on the quality, representativeness, and distribution of the training data.
Predictions should be treated as decision-support signals, not guaranteed outcomes. Real-world performance may differ when customer behavior or telecom market conditions change.
🔮 Future Improvements
- Advanced ensemble models
- Real-time churn monitoring
- Explainable AI with SHAP
- Automated model retraining
- MLOps monitoring
- Customer-specific retention recommendations
👨💻 Author
Md Zaheer JK
AI/ML • Deep Learning • Generative AI • Computer Vision • NLP • MLOps
GitHub: https://github.com/mdzaheerjk
Hugging Face: https://huggingface.co/zaheerjk
📜 License
MIT License