Machine Learning Basics
How machine learning works at a conceptual level: show the computer many examples, it finds patterns, then it makes predictions about new things; hands-on experience with Teachable Machine or similar tool
Teaching approaches
Gakuva’s recommended starting approach is selected. You can still compare every option.
1 approach
Could your child describe how you teach a computer to recognise something — by showing it lots of examples until it spots the pattern?
How machine learning works at a conceptual level: show the computer many examples, it finds patterns, then it makes predictions about new things; hands-on experience with Teachable Machine or similar tool
Learning resources
Reviewed external links that reinforce this concept. They do not replace Gakuva’s teaching approach.
Teachable Machine · Image
Hands-on machine-learning basics: gather examples, train, and test. Emphasize that the computer only learns from the examples you give it.
Proof: Save before/after screenshots (classes filled → prediction) and a parent note in the learner’s words: “It learned from my examples.”
AI for Oceans
Guided story-mode introduction to training data and model testing for younger learners before open-ended Teachable Machine work.
Proof: Save a progress screenshot and a parent note explaining training data vs a later test in kid language.
Explore the learning path
2 before · 5 after
This concept
Check understanding
- Describe the three steps of machine learning in simple terms (give examples, find patterns, make predictions)
- Train a simple model using a tool like Teachable Machine and describe what happened
- Explain why showing more and better examples makes the model more accurate
“Could your child describe how you teach a computer to recognise something — by showing it lots of examples until it spots the pattern?”
Curriculum record
- Type
- Conceptual
- Subject
- Computing
- Domain
- Artificial Intelligence
- Age range
- Ages 7–9