Build a Teachable Machine Image Classifier With Your Kid

Issue 9 • April 26, 2023

Most children today are passive consumers of artificial intelligence, interacting with algorithms through video recommendations, voice assistants, and gaming filters. To prepare the next generation for a technology-driven future, we must shift their perspective from consumption to creation. By building a functional image classifier, children aged eight to sixteen can demystify how computers learn to see. Using Google's free Teachable Machine platform, you and your child can train a custom computer vision model in under fifteen minutes. This hands-on project requires no coding experience, no paid subscriptions, and no specialized hardware, making it the perfect weekend activity to introduce core computer science concepts.

What is Teachable Machine?

Google's Teachable Machine is a web-based tool that makes creating machine learning models fast, accessible, and easy for everyone. It runs entirely in the web browser, meaning your data, including webcam feeds, stays private and is processed locally on your computer.

To begin this project, open a web browser on any computer with a webcam and navigate directly to https://teachablemachine.withgoogle.com/ . Click on the "Get Started" button and select "Image Project," followed by "Standard Image Model." This setup provides a clean interface with two default classes, a training panel, and a preview panel.

The Project: Healthy Snack vs. Treat Classifier

While you can classify anything, a highly engaging project for kids is building a "Healthy Snack vs. Treat Classifier." Gather two items from your kitchen: one healthy item, such as an apple or a banana, and one treat, such as a cookie or a juice box. Your goal is to teach the computer to recognize which is which.

Step 1: Define the Classes

In the first box, labeled "Class 1," click the pencil icon to rename it. Type "Healthy Snack." In the second box, labeled "Class 2," rename it to "Treat." These classes represent the categories that your artificial intelligence model will learn to distinguish.

Step 2: Gather the Training Data