This project is an end-to-end MLOps demo for house price prediction using:

• MLflow for experiment tracking and model registry
• DVC for data and model versioning
• FastAPI for model serving

• Activate the virtual environment mlops-env\Scripts\activate
• mlflow ui
• Fast API run the server uvicorn serve.fastapi_app:app --reload

Run the FastAPI instance named app inside the file serve/fastapi_app.py

POST http://127.0.0.1:8000/predict

{ "CRIM": 0.00632, "ZN": 18.0, "INDUS": 2.31, "CHAS": 0.0, "NOX": 0.538, "RM": 6.575, "AGE": 65.2, "DIS": 4.09, "RAD": 1.0, "TAX": 296.0, "PTRATIO": 15.3, "B": 396.9, "LSTAT": 4.98 }