Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 468 · 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 “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
2. 2.🏷️ What is a “label” in machine learning? (a) the font size (b) the price (c) a sticker on a laptop (d) the right answer tag
3. 3.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not 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.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
6. 6.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
7. 7.🏷️ 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
8. 8.🔍 Which is the odd one out? (a) wrong labels (b) examples of every type (c) clear, sharp examples (d) new data for testing
9. 9.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
10. 10.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a song about dogs (c) a list of rules only (d) many labelled photos
11. 11.🏷️ 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
12. 12.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) spam (b) not spam
13. 13.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) spam (b) not spam
14. 14.🏷️ 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
15. 15.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
16. 16.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
17. 17.True or false: “very few examples” is good for training a model. (a) True (b) False
18. 18.🔍 Which is the odd one out? (a) very few examples (b) correct labels (c) clear, sharp examples (d) new data for testing
19. 19.📚 Usually, more good examples make a model… (a) slower to switch on (b) better at its task (c) forget everything (d) change colour
20. 20.🔍 Which is the odd one out? (a) very few examples (b) copies of one photo (c) clear, sharp examples (d) blurry, unclear photos
21. 21.True or false: “new data for testing” is good for training a model. (a) False (b) True
22. 22.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) not spam (b) spam
23. 23.True or false: “only one kind of example” is bad for training a model. (a) False (b) True
24. 24.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
25. 25.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) True (b) False
26. 26.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
27. 27.Which of these is bad for training a model? (a) checking labels twice (b) new data for testing (c) examples of every type (d) labels added at random
28. 28.Which of these is good for training a model? (a) copies of one photo (b) correct labels (c) only one kind of example (d) very few examples
29. 29.True or false: “testing on training data” is bad for training a model. (a) False (b) True
30. 30.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) True (b) False
31. 31.True or false: “blurry, unclear photos” is good for training a model. (a) True (b) False
32. 32.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) True (b) False
33. 33.True or false: “many varied examples” is good for training a model. (a) False (b) True
34. 34.True or false: “blurry, unclear photos” is bad for training a model. (a) False (b) True
35. 35.🔍 Which is the odd one out? (a) clear, sharp examples (b) correct labels (c) many varied examples (d) only one kind of example
36. 36.True or false: “only one kind of example” is good for training a model. (a) True (b) False
37. 37.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True
38. 38.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it may get it wrong (c) it will turn yellow (d) it will be perfect
39. 39.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
40. 40.🔍 Which is the odd one out? (a) copies of one photo (b) only one kind of example (c) correct labels (d) testing on training data

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