thommaskevin/TinyML

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.

First-principle implementations of groundbreaking AI algorithms using a wide range of deep learning frameworks, accompanied by supporting research papers and demos.

Minimal and clean examples of machine learning algorithms implementations

TinyML and Efficient AI Computing | MIT 6.S965/6.5940

Notes on Machine Learning on edge for embedded/sensor/IoT uses

Summary, Code for Deep Neural Network Quantization