Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 547 · 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 “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
2. 2.🔍 Which is the odd one out? (a) labels added at random (b) only one kind of example (c) correct labels (d) very few examples
3. 3.🏷️ 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
4. 4.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
5. 5.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
6. 6.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) many labelled photos (c) one single photo (d) a list of rules only
7. 7.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True
8. 8.🏷️ What is a “label” in machine learning? (a) the price (b) a sticker on a laptop (c) the font size (d) the right answer tag
9. 9.True or false: “examples of every type” is bad for training a model. (a) True (b) False
10. 10.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it may get it wrong (c) it will shut down (d) it will turn yellow
11. 11.🧠 Machine learning is a way for computers to… (a) print pages (b) clean screens (c) learn from data (d) charge faster
12. 12.🔍 Which is the odd one out? (a) very few examples (b) checking labels twice (c) copies of one photo (d) labels added at random
13. 13.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) not spam (b) spam
14. 14.True or false: “very few examples” 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? “Science project groups are on the board” (a) spam (b) not spam
16. 16.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) True (b) False
17. 17.🔍 Which is the odd one out? (a) copies of one photo (b) many varied examples (c) only one kind of example (d) blurry, unclear photos
18. 18.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
19. 19.Which of these is good for training a model? (a) wrong labels (b) only one kind of example (c) very few examples (d) checking labels twice
20. 20.🏷️ 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
21. 21.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
22. 22.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
23. 23.🔍 Which is the odd one out? (a) many varied examples (b) correct labels (c) very few examples (d) examples of every type
24. 24.Which of these is bad for training a model? (a) blurry, unclear photos (b) new data for testing (c) examples of every type (d) many varied examples
25. 25.🔍 Which is the odd one out? (a) only one kind of example (b) clear, sharp examples (c) labels added at random (d) blurry, unclear photos
26. 26.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True
27. 27.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
28. 28.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) not spam (b) spam
29. 29.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
30. 30.Which of these is good for training a model? (a) wrong labels (b) only one kind of example (c) correct labels (d) testing on training data
31. 31.🏷️ 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
32. 32.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
33. 33.Which of these is bad for training a model? (a) many varied examples (b) wrong labels (c) checking labels twice (d) examples of every type
34. 34.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) not spam (b) spam
35. 35.True or false: “correct labels” is bad for training a model. (a) True (b) False
36. 36.True or false: “checking labels twice” is bad for training a model. (a) False (b) True
37. 37.🔍 Which is the odd one out? (a) blurry, unclear photos (b) correct labels (c) many varied examples (d) new data for testing
38. 38.True or false: “labels added at random” is bad for training a model. (a) True (b) False
39. 39.True or false: “clear, sharp examples” is good for training a model. (a) True (b) False
40. 40.Which of these is bad for training a model? (a) testing on training data (b) correct labels (c) many varied examples (d) checking labels twice

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