Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 357 · 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: checking labels twice? (a) good for training (b) bad for training
2. 2.📚 Usually, more good examples make a model… (a) change colour (b) better at its task (c) forget everything (d) slower to switch on
3. 3.True or false: “correct labels” is bad for training a model. (a) False (b) True
4. 4.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
5. 5.True or false: “clear, sharp examples” is bad for training a model. (a) False (b) True
6. 6.🧠 Machine learning is a way for computers to… (a) learn from data (b) clean screens (c) charge faster (d) print pages
7. 7.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
8. 8.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) False (b) True
9. 9.True or false: “testing on training data” is bad for training a model. (a) False (b) True
10. 10.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) True (b) False
11. 11.True or false: “wrong labels” is bad for training a model. (a) False (b) True
12. 12.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) not spam (b) spam
13. 13.Which of these is good for training a model? (a) testing on training data (b) only one kind of example (c) correct labels (d) very few examples
14. 14.🔍 Which is the odd one out? (a) very few examples (b) wrong labels (c) correct labels (d) blurry, unclear photos
15. 15.🔍 Which is the odd one out? (a) testing on training data (b) wrong labels (c) many varied examples (d) labels added at random
16. 16.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
17. 17.🏷️ 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
18. 18.True or false: “many varied examples” is bad for training a model. (a) True (b) False
19. 19.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
20. 20.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
21. 21.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) True (b) False
22. 22.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) True (b) False
23. 23.True or false: “labels added at random” is good for training a model. (a) False (b) True
24. 24.🔍 Which is the odd one out? (a) clear, sharp examples (b) examples of every type (c) copies of one photo (d) checking labels twice
25. 25.🥭 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 may get it wrong (d) it will shut down
26. 26.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) True (b) False
27. 27.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
28. 28.True or false: “testing on training data” is good for training a model. (a) True (b) False
29. 29.🔍 Which is the odd one out? (a) checking labels twice (b) very few examples (c) many varied examples (d) examples of every type
30. 30.True or false: “blurry, unclear photos” is bad for training a model. (a) True (b) False
31. 31.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True
32. 32.📚 Good or bad for training a model: blurry, unclear photos? (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? “Please buy milk on the way home” (a) not spam (b) spam
34. 34.🔍 Which is the odd one out? (a) labels added at random (b) wrong labels (c) testing on training data (d) photos in many lights
35. 35.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) spam (b) not spam
36. 36.🔍 Which is the odd one out? (a) correct labels (b) testing on training data (c) photos in many lights (d) examples of every type
37. 37.Which of these is good for training a model? (a) testing on training data (b) labels added at random (c) clear, sharp examples (d) copies of one photo
38. 38.Which of these is bad for training a model? (a) new data for testing (b) labels added at random (c) many varied examples (d) correct labels
39. 39.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) True (b) False
40. 40.Which of these is bad for training a model? (a) photos in many lights (b) testing on training data (c) new data for testing (d) many varied examples

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