Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 362 · 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: testing on training data? (a) good for training (b) bad for training
2. 2.True or false: “wrong labels” is bad for training a model. (a) True (b) False
3. 3.🔍 Which is the odd one out? (a) new data for testing (b) checking labels twice (c) clear, sharp examples (d) wrong labels
4. 4.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
5. 5.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) False (b) True
6. 6.True or false: “examples of every type” is good for training a model. (a) False (b) True
7. 7.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) False (b) True
8. 8.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
9. 9.🔍 Which is the odd one out? (a) correct labels (b) testing on training data (c) new data for testing (d) examples of every type
10. 10.🏷️ 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
11. 11.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
12. 12.True or false: “many varied examples” is bad for training a model. (a) False (b) True
13. 13.🧠 Machine learning is a way for computers to… (a) print pages (b) clean screens (c) charge faster (d) learn from data
14. 14.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) True (b) False
15. 15.🔍 Which is the odd one out? (a) wrong labels (b) copies of one photo (c) testing on training data (d) many varied examples
16. 16.True or false: “correct labels” is bad for training a model. (a) False (b) True
17. 17.True or false: “labels added at random” is good for training a model. (a) False (b) True
18. 18.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it will be perfect (c) it will turn yellow (d) it may get it wrong
19. 19.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a list of rules only (c) many labelled photos (d) a song about dogs
20. 20.True or false: “very few examples” is good for training a model. (a) True (b) False
21. 21.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True
22. 22.🏷️ 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
23. 23.🔍 Which is the odd one out? (a) labels added at random (b) wrong labels (c) testing on training data (d) correct labels
24. 24.Which of these is good for training a model? (a) testing on training data (b) many varied examples (c) blurry, unclear photos (d) wrong labels
25. 25.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) False (b) True
26. 26.True or false: “labels added at random” is bad for training a model. (a) False (b) True
27. 27.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) True (b) False
28. 28.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) spam (b) not spam
29. 29.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
30. 30.True or false: “testing on training data” is good for training a model. (a) True (b) False
31. 31.🔍 Which is the odd one out? (a) blurry, unclear photos (b) clear, sharp examples (c) wrong labels (d) copies of one photo
32. 32.🔍 Which is the odd one out? (a) labels added at random (b) blurry, unclear photos (c) examples of every type (d) wrong labels
33. 33.🏷️ 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
34. 34.True or false: “correct labels” is good for training a model. (a) False (b) True
35. 35.True or false: “blurry, unclear photos” is good for training a model. (a) True (b) False
36. 36.Which of these is bad for training a model? (a) new data for testing (b) examples of every type (c) testing on training data (d) clear, sharp examples
37. 37.Which of these is bad for training a model? (a) correct labels (b) examples of every type (c) very few examples (d) new data for testing
38. 38.True or false: “only one kind of example” 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 “spam”. (a) True (b) False
40. 40.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) True (b) False

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