Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 66 · 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.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) False (b) True
2. 2.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
3. 3.Which of these is bad for training a model? (a) correct labels (b) photos in many lights (c) copies of one photo (d) many varied examples
4. 4.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) True (b) False
5. 5.Which of these is good for training a model? (a) blurry, unclear photos (b) very few examples (c) copies of one photo (d) correct labels
6. 6.True or false: “very few examples” is bad for training a model. (a) True (b) False
7. 7.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
8. 8.🧠 Machine learning is a way for computers to… (a) charge faster (b) print pages (c) clean screens (d) learn from data
9. 9.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
10. 10.Which of these is good for training a model? (a) photos in many lights (b) wrong labels (c) testing on training data (d) labels added at random
11. 11.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
12. 12.Which of these is good for training a model? (a) copies of one photo (b) many varied examples (c) very few examples (d) only one kind of example
13. 13.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) not spam (b) spam
14. 14.True or false: “correct labels” is good for training a model. (a) True (b) False
15. 15.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) not spam (b) spam
16. 16.True or false: “wrong labels” is bad for training a model. (a) False (b) True
17. 17.🔍 Which is the odd one out? (a) testing on training data (b) only one kind of example (c) many varied examples (d) blurry, unclear photos
18. 18.🔍 Which is the odd one out? (a) clear, sharp examples (b) correct labels (c) only one kind of example (d) photos in many lights
19. 19.True or false: “many varied examples” is bad for training a model. (a) False (b) True
20. 20.Which of these is good for training a model? (a) wrong labels (b) only one kind of example (c) new data for testing (d) blurry, unclear photos
21. 21.🏷️ 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
22. 22.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
23. 23.Which of these is bad for training a model? (a) correct labels (b) labels added at random (c) examples of every type (d) new data for testing
24. 24.🔍 Which is the odd one out? (a) wrong labels (b) new data for testing (c) only one kind of example (d) very few examples
25. 25.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) many labelled photos (c) a list of rules only (d) one single photo
26. 26.🔍 Which is the odd one out? (a) checking labels twice (b) many varied examples (c) new data for testing (d) very few examples
27. 27.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True
28. 28.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) not spam (b) spam
29. 29.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) True (b) False
30. 30.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it will be perfect (c) it may get it wrong (d) it will shut down
31. 31.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False
32. 32.Which of these is good for training a model? (a) very few examples (b) labels added at random (c) checking labels twice (d) copies of one photo
33. 33.Which of these is good for training a model? (a) clear, sharp examples (b) blurry, unclear photos (c) wrong labels (d) very few examples
34. 34.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) False (b) True
35. 35.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
36. 36.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
37. 37.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) spam (b) not spam
38. 38.True or false: “wrong labels” is good for training a model. (a) True (b) False
39. 39.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
40. 40.🔍 Which is the odd one out? (a) correct labels (b) wrong labels (c) clear, sharp examples (d) examples of every type

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