Web component for removing image backgrounds in the browser

Cat & Dog Classifier is a browser-based machine learning application that classifies uploaded images as either cat or dog using a convolutional neural network. The project demonstrates how deep learning models can be integrated into a modern frontend stack using React, TypeScript, and TensorFlow.js, enabling real-time inference directly in the brow

Neural Networks can learn (almost!) anything.

Browser-based audio similarity search — no server, no uploads, runs entirely in your browser.

Enterprise-grade NLU bot trainer with 5-classifier stacking ensemble (171K params) — runs entirely in the browser

Innovative AI-powered music player built with Next.js 14. Integrates TensorFlow.js for real-time, browser-based hand gesture controls and the Spotify Web API for seamless audio streaming, backed by a robust NextAuth and MongoDB architecture.

In-browser neural network playground — train CNNs and dense nets on MNIST, Fashion-MNIST, and CIFAR-10 in real time

An AI-powered, vibe-aware location discovery app combining ML, LLMs, and Maps.

Interactive machine learning demos with TensorFlow.js featuring linear regression and binary classification with Materialize CSS framework

North Korean military activity risk analysis — fine-tuned LFM2-350M running in-browser via WebGPU