Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 28 · 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.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) spam (b) not spam
2. 2.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it will be perfect (c) it will shut down (d) it may get it wrong
3. 3.🔍 Which is the odd one out? (a) many varied examples (b) only one kind of example (c) clear, sharp examples (d) photos in many lights
4. 4.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
5. 5.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
6. 6.🏷️ 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
7. 7.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
8. 8.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) True (b) False
9. 9.🔍 Which is the odd one out? (a) very few examples (b) wrong labels (c) only one kind of example (d) new data for testing
10. 10.Which of these is good for training a model? (a) only one kind of example (b) labels added at random (c) copies of one photo (d) photos in many lights
11. 11.🔍 Which is the odd one out? (a) correct labels (b) very few examples (c) blurry, unclear photos (d) testing on training data
12. 12.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
13. 13.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
14. 14.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
15. 15.Which of these is bad for training a model? (a) new data for testing (b) blurry, unclear photos (c) many varied examples (d) examples of every type
16. 16.True or false: “testing on training data” is good for training a model. (a) False (b) True
17. 17.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False
18. 18.🏷️ 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
19. 19.True or false: “copies of one photo” is bad for training a model. (a) False (b) True
20. 20.🏷️ 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) not spam (b) spam
21. 21.🔍 Which is the odd one out? (a) checking labels twice (b) clear, sharp examples (c) examples of every type (d) testing on training data
22. 22.🏷️ 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
23. 23.🔍 Which is the odd one out? (a) checking labels twice (b) testing on training data (c) wrong labels (d) copies of one photo
24. 24.🔍 Which is the odd one out? (a) new data for testing (b) wrong labels (c) examples of every type (d) correct labels
25. 25.🔍 Which is the odd one out? (a) many varied examples (b) labels added at random (c) clear, sharp examples (d) examples of every type
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) spam (b) not spam
27. 27.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
28. 28.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) False (b) True
29. 29.True or false: “labels added at random” is bad for training a model. (a) True (b) False
30. 30.🔍 Which is the odd one out? (a) new data for testing (b) examples of every type (c) blurry, unclear photos (d) checking labels twice
31. 31.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) True (b) False
32. 32.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
33. 33.Which of these is bad for training a model? (a) correct labels (b) new data for testing (c) wrong labels (d) many varied examples
34. 34.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
35. 35.True or false: “clear, sharp examples” is good for training a model. (a) False (b) True
36. 36.🏷️ 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
37. 37.Which of these is bad for training a model? (a) photos in many lights (b) very few examples (c) many varied examples (d) new data for testing
38. 38.True or false: “correct labels” is bad for training a model. (a) False (b) True
39. 39.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) True (b) False
40. 40.🔍 Which is the odd one out? (a) blurry, unclear photos (b) copies of one photo (c) labels added at random (d) many varied examples

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