Build a Teachable Machine Image Classifier With Your Kid

Demystify artificial intelligence for your children by building a custom, functional computer vision model in fifteen minutes.

Most children consume artificial intelligence passively through video recommendations, search tools, or gaming filters.

To prepare the next generation for an AI-driven economy, we must shift their relationship with technology from passive consumption to active creation. For children aged 8 to 16, learning the mechanics of AI does not require writing complex lines of code. By using Google's free Teachable Machine platform, you and your child can build, train, and test a custom computer vision model in real-time, using nothing more than a standard web browser and a webcam.

The Project: Creating an Object Detector

This hands-on project allows your child to act as the lead AI engineer. Together, you will train a computer to recognize the difference between two distinct objects (for example, a favorite toy car versus a building block, or a thumbs-up gesture versus a thumbs-down gesture).

There are no paid subscriptions, software installations, or specialized hardware requirements. The entire process runs locally in your browser, ensuring privacy and security.

Step-by-Step Implementation Guide

Step 1: Access the Platform

Open a web browser on your laptop or desktop computer and navigate directly to Teachable Machine . Click on the Get Started button, then select Image Project , followed by Standard Image Model .

Step 2: Define Your Classes

In machine learning, a "class" is a category or label that the computer uses to group similar pieces of information. On the screen, you will see two default boxes labeled "Class 1" and "Class 2". Have your child rename these boxes. For this example, let us use "Class 1: Toy Car" and "Class 2: Building Block".

Step 3: Gather the Training Data

Click the Webcam button inside the "Toy Car" box. Hold the toy car up to the camera. Instruct your child to click and hold the Hold to Record button.

While recording, slowly rotate the toy car, move it closer to the lens, and then further away. This variation is critical. It teaches the computer what the car looks like from different angles and in different lighting conditions. Aim to capture at least 100 to 150 image samples. Repeat this exact process for "Class 2: Building Block" using the building block.