MLOps Pipeline Deployment
Project
This project demonstrates a MLOps pipeline for deploying a machine learning model into a production-ready web application. The goal is to help an insurance company forecast patient charges using input like age, BMI, and smoking status.
The solution includes:
- A machine learning model trained to predict insurance charges
- A Flask back-end to serve predictions
- A HTML / CSS front-end for user input
- Containerization with Docker
- Cloud deployment on Microsoft Azure
- A CI/CD pipeline with Github Actions
