A full-stack web application that leverages machine learning to detect real-time security threats, combining object and facial recognition to identify potential weapons, track personnel, and flag unauthorized individuals through a central monitoring dashboard.

A web application that leverages pre-trained machine learning models to detect objects in images. It utilizes the React framework, Vite for efficient development, TensorFlow to deploy machine learning models, and Groq for AI-generated insights.

This web application allows users to explore their Spotify listening history over three time periods: 1 month, 6 months, and 1 year. Users can copy and share their listening history easily. The app integrates with the Spotify API to provide personalized insights into top artists and tracks.

A Next.js web application that allows you to explore the MET Museum's extensive art collection. It features advanced search capabilities, session history tracking, and the ability to save your favourites for easy access.

This SQL-based Database Management System (DBMS) project is designed for managing sports tournaments. It features an Entity-Relationship Diagram (ERD) to visualize the relationships between entities, and a SQL script to create and populate the database. This design has been validated with 100+ rows of data, and is ready to be used by tournament organizers.

A website for a record store with responsive design, genre-filtered music catalog, and a contact form. Backend powered by Node.js and Express.js.

A C++ Point-of-Sale Application to manage inventory and sales.