Introduction to Machine Learning Systems
TinyML & Edge AI: On-device inference, model quantization, embedded ML, ultra-low-power AI for microcontrollers and IoT devices.
Curated Edge AI resources for computer vision & audio: hardware, frameworks, benchmarks, literature, and communities (excluding mobile).
This is open source library for creating artificial neural network in c programming language for general purpose use.
Notes and resources from Qualcomm On-device AI course, provided by DeepLearningAI
Real-time motor speed classification using TinyML on Raspberry Pi Pico W. MLP neural network trained with TensorFlow deployed on embedded hardware (5.3 KB model). Classifies motor vibration into 4 speed levels using MPU6050 accelerometer with live OLED display feedback. Complete ML workflow from data collection to edge deployment.
Multiposition heart sound analysis
Don't Think It Twice: Exploit Shift Invariance for Efficient Online Streaming Inference of CNNs
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