Intro to TinyML Part 2: Deploying a TensorFlow Lite Model to Arduino | DigiKey

In this tutorial series, Shawn introduces the concept of Tiny Machine Learning (TinyML), which consists of running machine learning algorithms on microcontrollers.

In this episode, we create an (as simple as possible) Arduino sketch to load our TensorFlow Lite model file and run inference. The model is used to predict values of a sinewave, which we can graph using the Serial Plotter. An LED is hooked up to the Arduino to demonstrate how to connect hardware to machine learning.

On the previous episode (%%%LINK%%%), we developed a simple 3-layer neural network that predicts values of the sine function when given a value between 0 and 2π. While this is a mostly useless way to calculate a sinewave, it provides a great demonstration for creating a neural network that is small enough to run on a microcontroller.

TensorFlow has a pre-built library that we can install in Arduino. We use the functions from this library to load our model and run inference to make predictions. Note that at the time this video was made, TensorFlow Lite for Microcontrollers is still under heavy development, so many of the features can change on a regular basis.