Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 550 · 40 questions

AI tip (Show, label, learn): Machine learning learns patterns from many labelled examples — a label is the right answer tag on each example. Good for training: many varied examples, correct labels, every type the model will meet, and separate new data for testing. Bad for training: very few examples, wrong or random labels, only one kind of example, blurry examples, testing on the training data.

1. 1.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
2. 2.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
3. 3.🧠 Machine learning is a way for computers to… (a) print pages (b) clean screens (c) learn from data (d) charge faster
4. 4.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
5. 5.Which of these is bad for training a model? (a) examples of every type (b) correct labels (c) copies of one photo (d) photos in many lights
6. 6.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) spam (b) not spam
7. 7.True or false: “many varied examples” is good for training a model. (a) True (b) False
8. 8.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
9. 9.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
10. 10.True or false: “labels added at random” is good for training a model. (a) False (b) True
11. 11.True or false: “correct labels” is bad for training a model. (a) False (b) True
12. 12.🔍 Which is the odd one out? (a) new data for testing (b) labels added at random (c) only one kind of example (d) very few examples
13. 13.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) spam (b) not spam
14. 14.🔍 Which is the odd one out? (a) labels added at random (b) copies of one photo (c) checking labels twice (d) only one kind of example
15. 15.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
16. 16.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) spam (b) not spam
17. 17.Which of these is bad for training a model? (a) only one kind of example (b) new data for testing (c) examples of every type (d) correct labels
18. 18.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) one single photo (c) many labelled photos (d) a song about dogs
19. 19.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
20. 20.True or false: “examples of every type” is bad for training a model. (a) True (b) False
21. 21.Which of these is good for training a model? (a) new data for testing (b) testing on training data (c) very few examples (d) only one kind of example
22. 22.🔍 Which is the odd one out? (a) many varied examples (b) checking labels twice (c) clear, sharp examples (d) wrong labels
23. 23.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True
24. 24.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) not spam (b) spam
25. 25.🔍 Which is the odd one out? (a) photos in many lights (b) copies of one photo (c) examples of every type (d) new data for testing
26. 26.True or false: “wrong labels” is good for training a model. (a) False (b) True
27. 27.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
28. 28.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it may get it wrong (b) it will turn yellow (c) it will be perfect (d) it will shut down
29. 29.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) False (b) True
30. 30.True or false: “blurry, unclear photos” is good for training a model. (a) False (b) True
31. 31.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) not spam (b) spam
32. 32.🔍 Which is the odd one out? (a) new data for testing (b) many varied examples (c) blurry, unclear photos (d) checking labels twice
33. 33.True or false: “copies of one photo” is bad for training a model. (a) False (b) True
34. 34.Which of these is bad for training a model? (a) wrong labels (b) new data for testing (c) clear, sharp examples (d) examples of every type
35. 35.Which of these is bad for training a model? (a) labels added at random (b) clear, sharp examples (c) checking labels twice (d) many varied examples
36. 36.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
37. 37.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “The class picnic is on Friday at 8 am” (a) spam (b) not spam
38. 38.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
39. 39.True or false: “clear, sharp examples” is good for training a model. (a) True (b) False
40. 40.True or false: “examples of every type” is good for training a model. (a) False (b) True

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