Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 113 · 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.🏷️ 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
2. 2.True or false: “copies of one photo” is bad for training a model. (a) False (b) True
3. 3.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) False (b) True
4. 4.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
5. 5.True or false: “many varied examples” is bad for training a model. (a) False (b) True
6. 6.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) False (b) True
7. 7.Which of these is bad for training a model? (a) examples of every type (b) new data for testing (c) many varied examples (d) testing on training data
8. 8.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
9. 9.Which of these is bad for training a model? (a) very few examples (b) photos in many lights (c) correct labels (d) many varied examples
10. 10.🔍 Which is the odd one out? (a) correct labels (b) new data for testing (c) wrong labels (d) checking labels twice
11. 11.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) many labelled photos (c) a song about dogs (d) a list of rules only
12. 12.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
13. 13.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
14. 14.True or false: “labels added at random” is good for training a model. (a) False (b) True
15. 15.Which of these is good for training a model? (a) copies of one photo (b) wrong labels (c) photos in many lights (d) only one kind of example
16. 16.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
17. 17.True or false: “examples of every type” is good for training a model. (a) False (b) True
18. 18.Which of these is good for training a model? (a) wrong labels (b) very few examples (c) only one kind of example (d) checking labels twice
19. 19.🔍 Which is the odd one out? (a) many varied examples (b) correct labels (c) testing on training data (d) checking labels twice
20. 20.True or false: “blurry, unclear photos” is bad for training a model. (a) False (b) True
21. 21.True or false: “photos in many lights” is good for training a model. (a) False (b) True
22. 22.🔍 Which is the odd one out? (a) blurry, unclear photos (b) clear, sharp examples (c) copies of one photo (d) very few examples
23. 23.🧠 Machine learning is a way for computers to… (a) learn from data (b) clean screens (c) print pages (d) charge faster
24. 24.True or false: “very few examples” is good for training a model. (a) False (b) True
25. 25.📚 Usually, more good examples make a model… (a) forget everything (b) slower to switch on (c) better at its task (d) change colour
26. 26.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
27. 27.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True
28. 28.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
29. 29.Which of these is good for training a model? (a) only one kind of example (b) copies of one photo (c) testing on training data (d) clear, sharp examples
30. 30.🏷️ 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
31. 31.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) True (b) False
32. 32.🔍 Which is the odd one out? (a) wrong labels (b) copies of one photo (c) blurry, unclear photos (d) new data for testing
33. 33.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) True (b) False
34. 34.Which of these is bad for training a model? (a) copies of one photo (b) clear, sharp examples (c) photos in many lights (d) examples of every type
35. 35.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it will shut down (c) it will be perfect (d) it may get it wrong
36. 36.Which of these is good for training a model? (a) correct labels (b) labels added at random (c) blurry, unclear photos (d) very few examples
37. 37.True or false: “labels added at random” is bad for training a model. (a) False (b) True
38. 38.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) False (b) True
39. 39.True or false: “clear, sharp examples” is bad for training a model. (a) False (b) True
40. 40.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False

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