Aws

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 Links Project Details 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. ...