Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 133 · 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: “wrong labels” is bad for training a model. (a) False (b) True
2. 2.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
3. 3.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
4. 4.True or false: “labels added at random” is bad for training a model. (a) False (b) True
5. 5.🔍 Which is the odd one out? (a) labels added at random (b) only one kind of example (c) blurry, unclear photos (d) clear, sharp examples
6. 6.True or false: “examples of every type” is bad for training a model. (a) True (b) False
7. 7.Which of these is bad for training a model? (a) photos in many lights (b) many varied examples (c) only one kind of example (d) new data for testing
8. 8.🐶 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
9. 9.🔍 Which is the odd one out? (a) clear, sharp examples (b) correct labels (c) many varied examples (d) labels added at random
10. 10.Which of these is good for training a model? (a) wrong labels (b) very few examples (c) examples of every type (d) blurry, unclear photos
11. 11.🔍 Which is the odd one out? (a) correct labels (b) examples of every type (c) only one kind of example (d) many varied examples
12. 12.Which of these is bad for training a model? (a) blurry, unclear photos (b) photos in many lights (c) checking labels twice (d) clear, sharp examples
13. 13.Which of these is bad for training a model? (a) checking labels twice (b) many varied examples (c) correct labels (d) wrong labels
14. 14.🧠 Machine learning is a way for computers to… (a) print pages (b) charge faster (c) clean screens (d) learn from data
15. 15.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
16. 16.Which of these is good for training a model? (a) only one kind of example (b) many varied examples (c) testing on training data (d) labels added at random
17. 17.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
18. 18.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) True (b) False
19. 19.Which of these is good for training a model? (a) very few examples (b) checking labels twice (c) labels added at random (d) testing on training data
20. 20.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) False (b) True
21. 21.Which of these is good for training a model? (a) copies of one photo (b) new data for testing (c) labels added at random (d) testing on training data
22. 22.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) spam (b) not spam
23. 23.🏷️ 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
24. 24.True or false: “photos in many lights” is bad for training a model. (a) True (b) False
25. 25.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) not spam (b) spam
26. 26.🏷️ 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
27. 27.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
28. 28.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) spam (b) not spam
29. 29.True or false: “many varied examples” is bad for training a model. (a) False (b) True
30. 30.🔍 Which is the odd one out? (a) examples of every type (b) correct labels (c) photos in many lights (d) very few examples
31. 31.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) True (b) False
32. 32.Which of these is good for training a model? (a) copies of one photo (b) testing on training data (c) wrong labels (d) correct labels
33. 33.True or false: “testing on training data” is bad for training a model. (a) True (b) False
34. 34.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
35. 35.📚 Usually, more good examples make a model… (a) forget everything (b) change colour (c) slower to switch on (d) better at its task
36. 36.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
37. 37.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
38. 38.🏷️ 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
39. 39.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
40. 40.Which of these is bad for training a model? (a) copies of one photo (b) checking labels twice (c) photos in many lights (d) examples of every type

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