Overview

A fully deployed machine learning system for house price prediction, built on AWS infrastructure with automated CI/CD pipelines.

Architecture

  • AWS Lambda — Serverless inference endpoint
  • AWS EC2 — Model training and data processing
  • AWS S3 — Model artifact and dataset storage
  • GitHub Actions — Automated CI/CD pipeline for continuous deployment

Features

  • Dynamic feature testing — Users can adjust input features and get instant predictions
  • Automated deployment — Push to main triggers model retraining and redeployment
  • Scalable inference — Lambda-based endpoints scale automatically with demand

Tech Stack

  • Python (Scikit-learn, Pandas)
  • AWS (Lambda, EC2, S3)
  • GitHub Actions
  • Docker

Key Takeaway

This project demonstrates end-to-end MLOps — from model development to cloud deployment with CI/CD. It covers the full lifecycle that production ML systems require.