A carefully curated collection of high-quality libraries, projects, tutorials, research papers, and other essential resources focused on TinyML — the intersection of machine learning and ultra-low-power embedded systems.
🧠 Singular values-driven automated filter pruning
Peer-to-peer video calling with live transcription and translation using MoonshineJS
EyeDriveSafe: A portable, IoT-enabled driver drowsiness detection system utilizing MobileNetV2 transfer learning on Arduino Uno Q for real-time edge AI facial analysis.
AI-powered study companion that detects phone pickups using Edge Impulse ML | Edge Impulse Competition 2025
On-device TinyML on the Silicon Labs Thunderboard Sense 2 (EFR32MG12, no NPU): an 85% IMU gesture recognizer running fully on-chip at ~87.5ms, plus a deep-audited hardware reference set.
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