Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 466 · 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: “blurry, unclear photos” is bad for training a model. (a) False (b) True
2. 2.🏷️ 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
3. 3.Which of these is good for training a model? (a) copies of one photo (b) only one kind of example (c) examples of every type (d) testing on training data
4. 4.Which of these is bad for training a model? (a) correct labels (b) copies of one photo (c) checking labels twice (d) examples of every type
5. 5.True or false: “testing on training data” is bad for training a model. (a) False (b) True
6. 6.True or false: “labels added at random” is good for training a model. (a) False (b) True
7. 7.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) False (b) True
8. 8.🔍 Which is the odd one out? (a) labels added at random (b) copies of one photo (c) very few examples (d) checking labels twice
9. 9.True or false: “checking labels twice” is good for training a model. (a) True (b) False
10. 10.🔍 Which is the odd one out? (a) testing on training data (b) clear, sharp examples (c) correct labels (d) many varied examples
11. 11.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
12. 12.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
13. 13.🐶 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
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) spam (b) not spam
15. 15.🏷️ 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
16. 16.True or false: “labels added at random” is bad for training a model. (a) True (b) False
17. 17.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
18. 18.🔍 Which is the odd one out? (a) copies of one photo (b) blurry, unclear photos (c) wrong labels (d) correct labels
19. 19.🧠 Machine learning is a way for computers to… (a) clean screens (b) learn from data (c) print pages (d) charge faster
20. 20.📚 Usually, more good examples make a model… (a) slower to switch on (b) better at its task (c) change colour (d) forget everything
21. 21.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
22. 22.🏷️ What is a “label” in machine learning? (a) the right answer tag (b) the font size (c) the price (d) a sticker on a laptop
23. 23.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
24. 24.Which of these is bad for training a model? (a) examples of every type (b) blurry, unclear photos (c) checking labels twice (d) many varied examples
25. 25.Which of these is good for training a model? (a) clear, sharp examples (b) testing on training data (c) blurry, unclear photos (d) very few examples
26. 26.🔍 Which is the odd one out? (a) labels added at random (b) only one kind of example (c) very few examples (d) examples of every type
27. 27.🔍 Which is the odd one out? (a) blurry, unclear photos (b) photos in many lights (c) new data for testing (d) clear, sharp examples
28. 28.True or false: “new data for testing” is good for training a model. (a) False (b) True
29. 29.True or false: “photos in many lights” is good for training a model. (a) True (b) False
30. 30.Which of these is bad for training a model? (a) checking labels twice (b) photos in many lights (c) wrong labels (d) clear, sharp examples
31. 31.🔍 Which is the odd one out? (a) blurry, unclear photos (b) wrong labels (c) labels added at random (d) many varied examples
32. 32.True or false: “new data for testing” is bad for training a model. (a) True (b) False
33. 33.Which of these is bad for training a model? (a) testing on training data (b) clear, sharp examples (c) examples of every type (d) correct labels
34. 34.Which of these is good for training a model? (a) blurry, unclear photos (b) copies of one photo (c) many varied examples (d) testing on training data
35. 35.🏷️ 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
36. 36.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) False (b) True
37. 37.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
38. 38.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
39. 39.🏷️ 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
40. 40.True or false: “many varied examples” is good for training a model. (a) True (b) False

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