Ever wondered how to build a small intelligent device that reacts to sounds like a keyword being spoken, recognizes gestures like waving a magic wand, or even recognize faces? With this kit …

Learn the fundamentals of TinyML implementation and training. To program your board, you can use the Arduino Cloud Editor or install the Arduino IDE. We’ll give you more details on how to …

You don't have to either master machine learning nor C++ to successfully train, convert and deploy a machine learning model to your Arduino board starting from scratch. In this post, I'll …

In this post, I will show you the easiest way to deploy your TensorFlow Lite model to an ESP32 using the Arduino IDE without any compilation stuff. So I finally settled on giving a try to …

A modified verison of the 0.0.2 version of the OV767X Library for Arduino (Copyright (c) 2020 Arduino SA) which is based on Linux Kernel V4L2 driver for OmniVision OV7670 cameras - …

Here we will walk through setting up the software you’ll need in the projects, the Arduino integrated development environment (IDE). We will be using the Arduino IDE to program your …

Feb 21, 2022 · TinyML is a sub-field of Machine Learning that studies the way to run ML models on small and low-powered devices. In this article, I will show an easy way to get started with …

Install up the Python libraries and Linux tools for the code in the notebook. Drag the punch.csv and flex.csv files from your computer to the tab to upload them into colab. Plot the CSV data …

Apr 20, 2020 · In this tutorial, we will load our model in Arduino using the TensorFlow Lite library and use it to run inference to generate an approximation of a sinewave.

Feb 10, 2022 · TinyML is faster, real-time, power-efficient and privacy-friendly more than any other form of edge analytics. Here's how Arduino Pro is making it possible for everyone.