Level up your TinyML skills
An hub of resources to learn TinyML development on Arduino and Esp32 boards, from beginners to expert skills.
Posts & Guides
A collection of guides with complete code samples and ready-to-use sketches for Arduino and Micropython
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Esp32 Camera Object Detection
The beginner-friendly guide to run Edge Impulse FOMO Object Detection on the Esp32 Camera with little effort
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Mastering the Esp32 Camera
Want to use your Esp32-cam like an expert? Not a programming genius? I can help!
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Real-Time image recognition
30-minutes walkthrough to create a working Esp32-cam image recognition system that runs at 80 FPS in 1 Kb of RAM
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Motion detection without PIR
Implement real-time motion detection from Esp32-cam frames like an expert in less than 30 minutes!
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Arduino WiFi Indoor Positioning
Localize people and objects as they move around your building with the power of Machine Learning
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Esp32 and Arduino Person Detection
Detect humans in images using a pre-trained neural network that works out of the box on Esp32 and Arduino boards
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TensorFlow Lite on Esp32
Convert an existing TensorFlow Lite model to be deployed on your ESP32 board using the Arduino IDE
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Get started with Arduino Machine Learning
A ready to use layout project to get up and running quickly with your next TinyML project
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Esp32-cam Color Tracking
Detect blobs of color and track their position in real-time, directly on the Esp32-cam
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Attiny Machine Learning
Can an Attiny85 really run Machine Learning? Let's find out in this article!
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Color classification with TinyML
Get familiar with data collection and pre-processing for Machine Learning tasks
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Gesture classification
Classify accelerometer's data with blazing fast spectral features extraction
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Iris flower classification with TinyML
An introduction to Machine Learning development for Arduino
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Machine Learning for MicroPython
Run your favourite Machine Learning algorithms on MicroPython and CircuitPython boards
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Write Arduino sketches from Python
Automate Arduino sketches creation and deployment with Python and the arduino-cli
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Separable Conv2D kernels: a benchmark
Real world numbers on 2D convolution optimization strategies for embedded microcontrollers
Eloquent Libraries

EloquentTinyML for Arduino
An Arduino library to make TensorFlow Lite for Microcontrollers neural networks more accessible and easy to use

Eloquent Edge Impulse for Arduino
An Arduino library to make Edge Impulse neural networks more accessible and easy to use

TinyMLgen for Python
A Python package to export TensorFlow Lite neural networks to C++ for microcontrollers

MicroMLGen for Python
A Python library to export scikit-learn models into C format with a single line of code