This project allows users to create personalized movie lists and receive real-time movie recommendations powered by AI. The recommendations adapt based on the content of the movie list as users add films, making suggestions more accurate over time.
This app is a second-year Bachelor's project and is composed of two main services: a Next.js front-end and a Flask back-end, both containerized via Docker. The back-end handles data with MySQL and provides AI recommendations using ChromaDB.
C programing focused on system calls, including file locking, file copying, and client-server architecture, culminating in the development of a custom shell capable of compiling itself.
Co-creation of a networked game using Unity. The game supports multiple players connected via a network, demonstrating complex real-time interactions and synchronization between clients.
