Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 415 · 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.🔍 Which is the odd one out? (a) labels added at random (b) many varied examples (c) very few examples (d) copies of one photo
2. 2.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False
3. 3.True or false: “wrong labels” is bad for training a model. (a) True (b) False
4. 4.🔍 Which is the odd one out? (a) correct labels (b) examples of every type (c) photos in many lights (d) blurry, unclear photos
5. 5.True or false: “clear, sharp examples” is good for training a model. (a) True (b) False
6. 6.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
7. 7.🥭 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 be perfect (d) it will turn yellow
8. 8.🏷️ 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
9. 9.🏷️ 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
10. 10.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
11. 11.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
12. 12.Which of these is good for training a model? (a) very few examples (b) labels added at random (c) new data for testing (d) wrong labels
13. 13.True or false: “labels added at random” is bad for training a model. (a) False (b) True
14. 14.🔍 Which is the odd one out? (a) correct labels (b) new data for testing (c) clear, sharp examples (d) very few examples
15. 15.🔍 Which is the odd one out? (a) labels added at random (b) blurry, unclear photos (c) testing on training data (d) examples of every type
16. 16.Which of these is good for training a model? (a) blurry, unclear photos (b) correct labels (c) testing on training data (d) wrong labels
17. 17.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) spam (b) not spam
18. 18.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) not spam (b) spam
19. 19.Which of these is bad for training a model? (a) checking labels twice (b) very few examples (c) examples of every type (d) clear, sharp examples
20. 20.📚 Usually, more good examples make a model… (a) better at its task (b) change colour (c) slower to switch on (d) forget everything
21. 21.True or false: “testing on training data” is bad for training a model. (a) False (b) True
22. 22.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) True (b) False
23. 23.Which of these is good for training a model? (a) wrong labels (b) labels added at random (c) checking labels twice (d) testing on training data
24. 24.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
25. 25.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) True (b) False
26. 26.Which of these is good for training a model? (a) clear, sharp examples (b) labels added at random (c) wrong labels (d) testing on training data
27. 27.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) True (b) False
28. 28.True or false: “correct labels” is good for training a model. (a) False (b) True
29. 29.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) False (b) True
30. 30.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
31. 31.🏷️ 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
32. 32.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
33. 33.🏷️ 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
34. 34.🧠 Machine learning is a way for computers to… (a) print pages (b) clean screens (c) learn from data (d) charge faster
35. 35.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) a song about dogs (c) one single photo (d) many labelled photos
36. 36.True or false: “labels added at random” is good for training a model. (a) False (b) True
37. 37.Which of these is bad for training a model? (a) correct labels (b) photos in many lights (c) clear, sharp examples (d) only one kind of example
38. 38.🔍 Which is the odd one out? (a) wrong labels (b) very few examples (c) correct labels (d) blurry, unclear photos
39. 39.True or false: “very few examples” is bad for training a model. (a) False (b) True
40. 40.Which of these is good for training a model? (a) copies of one photo (b) wrong labels (c) many varied examples (d) only one kind of example

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