In this tutorial we will teach a board to recognise gestures! We'll capture motion data from the Arduino Nano 33 BLE Sense board, import it into TensorFlow to train a model, and deploy a classifier onto the board using TensorFlow Lite for microcontrollers.

This tutorial is adapted from the workshop Sandeep Mistry, Arduino and Don Coleman, Chariot Solutions presented at AI/ML Devfest in September 2019.

• Exercise 1: Development Environment
• Exercise 2: Connecting the Board
• Exercise 3: Visualizing the IMU Data
• Exercise 4: Gather the Training Data
• Exercise 5: Machine Learning
• Exercise 6: Classifying IMU Data
• Exercise 7: Gesture Controlled USB Emoji Keyboard
• Exercise 8: Next Steps