on-device-learning

LauzHack Deep Learning Bootcamp

On-Device Learning for Human Activity Recognition on Low-Power Microcontrollers

Sofia is an advanced artificial intelligence model designed for natural language processing (NLP) with quantum-inspired neural architecture. This system combines cutting-edge deep learning techniques with quantum computing principles to achieve unprecedented levels of language

Code for "A Federated Approach for Adaptive Urban Sound Classification on TinyML Edge Devices" (Sensors 2026, 26, 2854). Federated on-device learning on ESP32, a 231-parameter head trains locally and syncs over MQTT at 1.2 kB per round.

AegisFL is a cloud-native, privacy-preserving federated learning platform. It uses TensorFlow Federated, Differential Privacy, and Secure Aggregation to train models across decentralized clients, ensuring HIPAA/GDPR compliance with cost-optimized Kubernetes deployment and real-time monitoring.

An anomaly detector that trains on the machine it watches. Unsupervised on-device learning in fixed point on an ESP32 - no labels, no cloud, no pre-trained fault classes.