physical machines


How can machine learning enhance the creativity of physical computing?

• Dates TBD
• Based at ACUD in Berlin, Germany
• One week, full-time
• Small class of participants

Artist / Student (Full Time)*
€725 until 30. Jun., €845 regular fee

€925 until 30. Jun., €1045 regular fee

€1125 until 30. Jun., €1265 regular fee


While machine learning models are getting smaller, and microcontrollers are getting more computing power, machine learning is moving towards edge devices. This class explores the idea of how machine learning algorithms can be used on microcontrollers along with sensor data to build Physical Computing projects.

In this class, we will learn about TensorFlow Lite, a library that allows you to run machine learning algorithms on microcontrollers. We will talk about common machine learning algorithms and techniques and apply them to build hands-on interactive projects that enrich our daily lives.

Students will learn to use pre-trained models, and re-train the models with sensor data. We are going to talk about Image Classification, Transfer Learning, Gesture and Speech Detection. For each topic, we will first discuss its history, theory, datasets, and applications, and then build simple experiments based on the topic.

Previous knowledge of physical computing or equivalent programming experience with Arduino and JavaScript is encouraged but not required.

in this course,
you will be
introduced to

  • Introduction to machine learning
  • Image Classification and Transfer Learning
  • Running and training models using Tensorflow Lite for Microcontrollers
  • Gesture detection and speech recognition as time allows
  • How to get started with machine learning on arduino.
  • Ideal participants have previous experience with arduino and basic understanding of javascript or code in general
  • An amazing network and community of like-minded creative beings and potential future collaborators

who is this
program for?

This course is for anyone who is interested in machine learning and it's application within hardware-based projects. This class aims to make ML approachable for a broad audience of artists, designers, researchers, creative coders, programming beginners, and anyone else excited by the prospect!

meet the