Hugging Face Live Deployment

Customer Churn ML Predictor

Robust Machine Learning Classifier & Analytics Pipeline

⚡ Model Management

Train Random Forest Churn Classifier on synthetic customer telemetry.

Current Model Performance
85.50%
Accuracy
83.20%
F1-Score
84.10%
Precision
82.30%
Recall
🎬 Demo Video

Watch the pipeline walkthrough video demonstration below.

🔍 Single Customer Churn Inference

Prediction Outcome:

High Churn Risk! 🔴

Estimated Churn Probability: 55.3%

📌 Model Architecture & Features
  • Features: Age, Monthly Charges, Contract Length, Support Calls, Tech Support.
  • Algorithm: Scikit-Learn RandomForestClassifier with standard scaling and binary encoding.
  • CLI Usage: python -m src.predict --age 45 --monthly_charges 85.5 --contract_length 12 --support_calls 3 --tech_support no