GitHub Copilot
Use an AI explanation to investigate a coding bug without skipping the reasoning.
Explore this workflow →Train a small model to recognize images, sounds, or poses, then test how its examples affect its predictions.
Open Google Teachable Machine ↗Official getting-started help ↗For: Educators demonstrating machine learning with teacher-prepared examples. Documentation reviewed November 7, 2026.
A visible demonstration of classification, testing, and dataset limitations.
Identifying students, inferring personal traits, or making assessment decisions.
Photograph two ordinary objects against several backgrounds. Reserve some photos for testing rather than training.
Use this sample prompt or task input as a starting point. Adapt the subject and level to your learners.
Class A: a pencil. Class B: a marker. Train with varied angles, then test each object on a different desk.
Check performance on unseen examples. Discuss why confident predictions can still be wrong.
Use non-sensitive object samples. A classroom model is an experiment, not a reliable decision system for people.
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This workflow is an editorial suggestion based on documentation, not a hands-on test or a claim of learning gains. Check school approval, current pricing, and student account eligibility before a classroom rollout. Use public or permitted samples and keep identifiable student information out of unapproved services.