Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 418 · 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.🔍 Which is the odd one out? (a) labels added at random (b) only one kind of example (c) copies of one photo (d) checking labels twice
2. 2.True or false: “examples of every type” is good for training a model. (a) True (b) False
3. 3.Which of these is bad for training a model? (a) correct labels (b) new data for testing (c) checking labels twice (d) testing on training data
4. 4.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it may get it wrong (b) it will shut down (c) it will turn yellow (d) it will be perfect
5. 5.Which of these is good for training a model? (a) correct labels (b) testing on training data (c) copies of one photo (d) blurry, unclear photos
6. 6.Which of these is good for training a model? (a) testing on training data (b) copies of one photo (c) labels added at random (d) new data for testing
7. 7.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) True (b) False
8. 8.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the font size (c) the right answer tag (d) the price
9. 9.True or false: “correct labels” is good for training a model. (a) True (b) False
10. 10.🏷️ 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
11. 11.True or false: “new data for testing” is bad for training a model. (a) True (b) False
12. 12.Which of these is good for training a model? (a) many varied examples (b) blurry, unclear photos (c) copies of one photo (d) labels added at random
13. 13.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) many labelled photos (c) a list of rules only (d) one single photo
14. 14.True or false: “correct labels” is bad for training a model. (a) False (b) True
15. 15.Which of these is good for training a model? (a) very few examples (b) wrong labels (c) copies of one photo (d) checking labels twice
16. 16.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
17. 17.🏷️ 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
18. 18.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
19. 19.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
20. 20.🔍 Which is the odd one out? (a) new data for testing (b) photos in many lights (c) many varied examples (d) wrong labels
21. 21.Which of these is bad for training a model? (a) many varied examples (b) very few examples (c) clear, sharp examples (d) new data for testing
22. 22.🏷️ 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
23. 23.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
24. 24.🔍 Which is the odd one out? (a) only one kind of example (b) testing on training data (c) clear, sharp examples (d) blurry, unclear photos
25. 25.🔍 Which is the odd one out? (a) examples of every type (b) correct labels (c) testing on training data (d) clear, sharp examples
26. 26.True or false: “testing on training data” is good for training a model. (a) True (b) False
27. 27.🔍 Which is the odd one out? (a) many varied examples (b) correct labels (c) clear, sharp examples (d) labels added at random
28. 28.📚 Usually, more good examples make a model… (a) slower to switch on (b) change colour (c) forget everything (d) better at its task
29. 29.🏷️ 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
30. 30.Which of these is bad for training a model? (a) correct labels (b) examples of every type (c) many varied examples (d) copies of one photo
31. 31.🔍 Which is the odd one out? (a) photos in many lights (b) only one kind of example (c) wrong labels (d) blurry, unclear photos
32. 32.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
33. 33.🧠 Machine learning is a way for computers to… (a) learn from data (b) print pages (c) clean screens (d) charge faster
34. 34.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) False (b) True
35. 35.True or false: “many varied examples” is bad for training a model. (a) False (b) True
36. 36.🔍 Which is the odd one out? (a) wrong labels (b) very few examples (c) testing on training data (d) correct labels
37. 37.True or false: “clear, sharp examples” is good for training a model. (a) True (b) False
38. 38.🏷️ 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
39. 39.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) spam (b) not spam
40. 40.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) False (b) True

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