Initial folder structure created

.gitignore

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+# Python-generated files
+__pycache__/
+*.py[oc]
+build/
+dist/
+wheels/
+*.egg-info
+
+# Virtual environments
+.venv

.python-version

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+3.12

README.md

@@ -1,12 +1,24 @@
----
-title: Telco Churn Predictor
-emoji: 🔥
-colorFrom: gray
-colorTo: pink
-sdk: gradio
-sdk_version: 6.11.0
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+title: Telco Churn Predictor
+emoji: 🔥
+colorFrom: gray
+colorTo: pink
+sdk: gradio
+sdk_version: 6.11.0
+app_file: app.py
+pinned: false
+---
+
+# Customer Churn Prediction
+
+A machine learning model to predict the likelihood of customer churn in the telecom industry.
+
+## Features
+- **FastAPI Backend**: High-performance REST API for programmatic access.
+- **Gradio UI**: User-friendly web interface for manual testing.
+- **XGBoost Model**: Trained on historical customer data for high accuracy.
+
+## Dataset used
+- Telco Customer Churn (from Kaggle)
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

main.py

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+def main():
+    print("Hello from churn!")
+
+
+if __name__ == "__main__":
+    main()

pyproject.toml

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+[project]
+name = "churn"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.12"
+dependencies = [
+    "lightgbm>=4.6.0",
+    "matplotlib>=3.10.8",
+    "mlflow>=1.27.0",
+    "optuna>=4.8.0",
+    "pandas>=3.0.2",
+    "scikit-learn>=1.8.0",
+    "seaborn>=0.13.2",
+    "statsmodels>=0.14.6",
+    "xgboost>=3.2.0",
+]