This project is a Node.js application deployed with MongoDB using Docker Compose. The application is containerized with a custom Dockerfile that encapsulates all dependencies and runtime configurations. MongoDB runs in a separate container, linked to the application via Docker Compose networking. Both containers are built, tagged, and pushed to AWS

This project helps streamline the visa approval process by using machine learning to predict the likelihood of US visa approval for employees. It can assist immigration officials in making quicker, data-driven decisions, reduce manual work, and enhance accuracy.

This is a simple 2-tier microservice web application with backend written in Python (Flask) and frontend written in Nodejs (Express). The frontend microservice serves the http request while the backend microservice fetches and display messages upon clicking any images in the frontend.

Mini Social Network