Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 12 · 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.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) False (b) True
2. 2.🏷️ 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
3. 3.🔍 Which is the odd one out? (a) only one kind of example (b) testing on training data (c) copies of one photo (d) correct labels
4. 4.🧠 Machine learning is a way for computers to… (a) charge faster (b) learn from data (c) print pages (d) clean screens
5. 5.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) False (b) True
6. 6.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
7. 7.🔍 Which is the odd one out? (a) new data for testing (b) photos in many lights (c) examples of every type (d) testing on training data
8. 8.🏷️ 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) spam (b) not spam
9. 9.🏷️ 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
10. 10.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
11. 11.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
12. 12.🏷️ 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
13. 13.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
14. 14.🔍 Which is the odd one out? (a) checking labels twice (b) clear, sharp examples (c) wrong labels (d) correct labels
15. 15.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) False (b) True
16. 16.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) spam (b) not spam
17. 17.Which of these is bad for training a model? (a) examples of every type (b) many varied examples (c) wrong labels (d) photos in many lights
18. 18.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
19. 19.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) True (b) False
20. 20.True or false: “photos in many lights” is good for training a model. (a) True (b) False
21. 21.🏷️ 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
22. 22.📚 Usually, more good examples make a model… (a) change colour (b) better at its task (c) slower to switch on (d) forget everything
23. 23.🐶 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) many labelled photos (d) one single photo
24. 24.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) False (b) True
25. 25.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
26. 26.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
27. 27.Which of these is bad for training a model? (a) photos in many lights (b) very few examples (c) examples of every type (d) clear, sharp examples
28. 28.🥭 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
29. 29.🏷️ 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
30. 30.True or false: “wrong labels” is good for training a model. (a) False (b) True
31. 31.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
32. 32.🏷️ 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
33. 33.True or false: “photos in many lights” is bad for training a model. (a) False (b) True
34. 34.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
35. 35.Which of these is bad for training a model? (a) many varied examples (b) blurry, unclear photos (c) photos in many lights (d) correct labels
36. 36.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True
37. 37.🏷️ What is a “label” in machine learning? (a) the font size (b) the right answer tag (c) a sticker on a laptop (d) the price
38. 38.🔍 Which is the odd one out? (a) labels added at random (b) many varied examples (c) blurry, unclear photos (d) copies of one photo
39. 39.True or false: “wrong labels” is bad for training a model. (a) False (b) True
40. 40.True or false: “blurry, unclear photos” is good for training a model. (a) True (b) False

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