Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 36 · 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? “You won a free phone! Click now!” (a) not spam (b) spam
2. 2.🔍 Which is the odd one out? (a) wrong labels (b) labels added at random (c) many varied examples (d) very few examples
3. 3.True or false: “many varied examples” is bad for training a model. (a) False (b) True
4. 4.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
5. 5.Which of these is good for training a model? (a) testing on training data (b) copies of one photo (c) many varied examples (d) only one kind of example
6. 6.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True
7. 7.🏷️ 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
8. 8.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it may get it wrong (c) it will shut down (d) it will be perfect
9. 9.Which of these is good for training a model? (a) photos in many lights (b) blurry, unclear photos (c) labels added at random (d) very few examples
10. 10.True or false: “clear, sharp examples” is good for training a model. (a) False (b) True
11. 11.True or false: “wrong labels” is bad for training a model. (a) True (b) False
12. 12.Which of these is good for training a model? (a) blurry, unclear photos (b) correct labels (c) copies of one photo (d) labels added at random
13. 13.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
14. 14.Which of these is bad for training a model? (a) wrong labels (b) new data for testing (c) checking labels twice (d) many varied examples
15. 15.🔍 Which is the odd one out? (a) only one kind of example (b) correct labels (c) photos in many lights (d) many varied examples
16. 16.Which of these is bad for training a model? (a) checking labels twice (b) clear, sharp examples (c) testing on training data (d) correct labels
17. 17.🔍 Which is the odd one out? (a) blurry, unclear photos (b) only one kind of example (c) very few examples (d) photos in many lights
18. 18.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
19. 19.🏷️ What is a “label” in machine learning? (a) the price (b) the right answer tag (c) the font size (d) a sticker on a laptop
20. 20.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
21. 21.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
22. 22.🔍 Which is the odd one out? (a) correct labels (b) many varied examples (c) blurry, unclear photos (d) checking labels twice
23. 23.🐶 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) a song about dogs (d) many labelled photos
24. 24.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
25. 25.🔍 Which is the odd one out? (a) very few examples (b) photos in many lights (c) many varied examples (d) examples of every type
26. 26.🔍 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
27. 27.🧠 Machine learning is a way for computers to… (a) clean screens (b) charge faster (c) learn from data (d) print pages
28. 28.Which of these is bad for training a model? (a) photos in many lights (b) new data for testing (c) copies of one photo (d) checking labels twice
29. 29.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) False (b) True
30. 30.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
31. 31.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
32. 32.Which of these is good for training a model? (a) clear, sharp examples (b) copies of one photo (c) testing on training data (d) blurry, unclear photos
33. 33.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) True (b) False
34. 34.🏷️ 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
35. 35.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
36. 36.True or false: “only one kind of example” is bad for training a model. (a) True (b) False
37. 37.🔍 Which is the odd one out? (a) new data for testing (b) many varied examples (c) wrong labels (d) clear, sharp examples
38. 38.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) False (b) True
39. 39.🏷️ 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
40. 40.True or false: “clear, sharp examples” is bad for training a model. (a) False (b) True

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