In this repository you will find TinyML course syllabi, assignments/labs, code walkthroughs, links to student projects, and lecture videos (where applicable).

This repository holds the Google Colabs for the EdX TinyML Specialization

A Python package with command-line utilities and scripts to aid the development of machine learning models for Silicon Lab's embedded platforms

This repository holds the Arduino Library for the EdX TinyML Specialization

TinyOdom: Hardware-Aware Efficient Neural Inertial Navigation

Collection of STM32 projects making use of Tensorflow Lite Micro

Auritus: An Open-Source Optimization Toolkit for Training and Development of Human Movement Models and Filters Using Earables

Code for IEEE Internet Computing Journal paper 'OTA-TinyML: Over the Air Deployment of TinyML Models and Execution on IoT Devices'

TinyNS: Platform-Aware Neurosymbolic Auto Tiny Machine Learning

Tensorflow Lite Micro is a DL inference framework for microcontrollers based on Google Tensorflow Lite

TensorFlow Lite for Microcontrollers Python package for Raspberry Pi Zero

TensorFlow Lite for BL602

Sleep state prediction in embedded systems based on sensor data.

This repo contains all the necessary files to build a MNIST TinyML application, that works with an OV7670 camera module and TFT LCD module.

A PlatformIO library with the complete and (As of Aug 20, 2023) up-to-date version of Tensorflow Lite for Microcontrollers.

Web GUI to collect and categorize images from web cam (ESP-CAM, ESP-WHO) for ML training

A holistic device for safer and smarter contactless elevator system using Embedded Machine Learning on an Arduino Nano 33 BLE Sense, complete with a deployable PCB and fire safety system pipeline.

weights of MobileNetV1 and MobileNetV2 trained on greyscale images. supports 96x96 image inputs only. Useful for developing models for Edge devices like Android, IOS and Microcontrollers.

Detect a MokaPot with Tensorflow Lite Micro and an Arduino Portenta or OpenMV cam

MoonMakers-Pinball in a game that works in the browser, where we use our Arduino Nano 33 BLE Sense, as a command to control the imposition of our ball thanks to AI.