Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 359 · 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.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
2. 2.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) False (b) True
3. 3.True or false: “checking labels twice” is good for training a model. (a) False (b) True
4. 4.🏷️ 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
5. 5.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
6. 6.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
7. 7.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
8. 8.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
9. 9.True or false: “many varied examples” is bad for training a model. (a) True (b) False
10. 10.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
11. 11.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) one single photo (c) a song about dogs (d) many labelled photos
12. 12.True or false: “testing on training data” is bad for training a model. (a) False (b) True
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) not spam (b) spam
14. 14.🔍 Which is the odd one out? (a) wrong labels (b) very few examples (c) clear, sharp examples (d) copies of one photo
15. 15.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) False (b) True
16. 16.True or false: “copies of one photo” is bad for training a model. (a) True (b) False
17. 17.🔍 Which is the odd one out? (a) blurry, unclear photos (b) wrong labels (c) correct labels (d) testing on training data
18. 18.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) False (b) True
19. 19.Which of these is good for training a model? (a) wrong labels (b) clear, sharp examples (c) very few examples (d) only one kind of example
20. 20.Which of these is good for training a model? (a) labels added at random (b) checking labels twice (c) only one kind of example (d) very few examples
21. 21.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
22. 22.🔍 Which is the odd one out? (a) checking labels twice (b) photos in many lights (c) new data for testing (d) blurry, unclear photos
23. 23.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) True (b) False
24. 24.True or false: “very few examples” is bad for training a model. (a) True (b) False
25. 25.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
26. 26.🏷️ 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
27. 27.🏷️ 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
28. 28.Which of these is good for training a model? (a) wrong labels (b) very few examples (c) labels added at random (d) examples of every type
29. 29.🏷️ 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
30. 30.True or false: “clear, sharp examples” is good for training a model. (a) False (b) True
31. 31.True or false: “checking labels twice” is bad for training a model. (a) True (b) False
32. 32.True or false: “only one kind of example” is bad for training a model. (a) True (b) False
33. 33.Which of these is good for training a model? (a) testing on training data (b) only one kind of example (c) wrong labels (d) new data for testing
34. 34.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it will turn yellow (c) it may get it wrong (d) it will shut down
35. 35.Which of these is good for training a model? (a) copies of one photo (b) labels added at random (c) wrong labels (d) many varied examples
36. 36.🏷️ 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
37. 37.Which of these is bad for training a model? (a) many varied examples (b) examples of every type (c) checking labels twice (d) very few examples
38. 38.🏷️ 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
39. 39.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
40. 40.🔍 Which is the odd one out? (a) examples of every type (b) many varied examples (c) correct labels (d) very few examples

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