Image Classification
Upload or drag an image to classify it using MobileNet, a pre-trained neural network.
Drop an image here or click to upload
Experience cutting-edge AI running entirely client-side. LLM chat, voice emotion detection, computer vision, and more - all with complete privacy.
Advanced ML capabilities running completely in your browser
Chat with a local LLM running entirely in your browser
Analyze emotions from voice using audio ML
Upload any image and identify objects using MobileNet
Analyze text sentiment in real-time
Detect and locate objects using COCO-SSD
Draw a digit and watch AI recognize it
Upload or drag an image to classify it using MobileNet, a pre-trained neural network.
Drop an image here or click to upload
Machine learning models that run directly in your web browser using JavaScript, without sending data to servers. All computation happens on your device using libraries like TensorFlow.js and Transformers.js.
Your data never leaves your device. Images, text, voice, and chat messages are processed locally, ensuring complete privacy and data security. No server uploads, no tracking, no storage.
Modern browsers use WebGL and WebAssembly for hardware acceleration, enabling real-time ML inference. Models are cached locally for instant subsequent loads.
This platform uses TensorFlow.js for neural networks, Transformers.js for language models, pre-trained models like MobileNet and COCO-SSD, and Web Audio API for voice processing.
After initial load, models are cached. The entire platform can work offline, making ML accessible even without internet connectivity.
Perfect for privacy-sensitive applications, edge computing, offline tools, interactive education, conversational AI, and rapid prototyping without backend infrastructure.
Browser ML Studio is an educational platform demonstrating advanced client-side machine learning capabilities. Built with modern web technologies, this project showcases how powerful AI models - including language models and audio processing - can run entirely in the browser without requiring server infrastructure.
No. Everything runs entirely in your browser. Your images, text, voice recordings, and chat messages never leave your device. All ML inference happens locally using JavaScript.
We use a lightweight language model optimized to run in browsers. The model downloads once, caches locally, and runs inference using WebAssembly for acceleration. It's not as powerful as GPT-4, but it's completely private and offline-capable.
The voice emotion demo uses audio feature extraction (pitch, energy, spectral features) combined with pattern matching. It's experimental and works best with clear speech. Professional emotion detection uses more complex deep learning models, but this demonstrates the concept entirely client-side.
All modern browsers including Chrome, Firefox, Safari, and Edge. WebGL support is required for optimal performance. Mobile browsers are fully supported.
Yes! After the initial load, all models are cached in your browser. The entire platform works offline, including the LLM chat. The first visit requires internet to download models.