Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 204 · 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: examples of every type? (a) good for training (b) bad for training
2. 2.🔍 Which is the odd one out? (a) copies of one photo (b) very few examples (c) photos in many lights (d) labels added at random
3. 3.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) many labelled photos (c) a song about dogs (d) a list of rules only
4. 4.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
5. 5.🔍 Which is the odd one out? (a) very few examples (b) only one kind of example (c) wrong labels (d) many varied examples
6. 6.Which of these is good for training a model? (a) wrong labels (b) only one kind of example (c) labels added at random (d) new data for testing
7. 7.Which of these is bad for training a model? (a) checking labels twice (b) copies of one photo (c) correct labels (d) examples of every type
8. 8.Which of these is bad for training a model? (a) correct labels (b) checking labels twice (c) wrong labels (d) new data for testing
9. 9.🥭 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
10. 10.🔍 Which is the odd one out? (a) copies of one photo (b) examples of every type (c) correct labels (d) many varied examples
11. 11.True or false: “blurry, unclear photos” is bad for training a model. (a) False (b) True
12. 12.🏷️ 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
13. 13.True or false: “examples of every type” is bad for training a model. (a) False (b) True
14. 14.Which of these is bad for training a model? (a) examples of every type (b) blurry, unclear photos (c) checking labels twice (d) many varied examples
15. 15.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) spam (b) not spam
16. 16.📚 Good or bad for training a model: blurry, unclear photos? (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? “Happy birthday! See you at lunch” (a) not spam (b) spam
18. 18.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
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 “Last chance! Free gift card inside” should be labelled “not spam”. (a) True (b) False
21. 21.🔍 Which is the odd one out? (a) testing on training data (b) blurry, unclear photos (c) wrong labels (d) checking labels twice
22. 22.Which of these is good for training a model? (a) correct labels (b) very few examples (c) only one kind of example (d) testing on training data
23. 23.🔍 Which is the odd one out? (a) checking labels twice (b) examples of every type (c) clear, sharp examples (d) testing on training data
24. 24.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
25. 25.🧠 Machine learning is a way for computers to… (a) print pages (b) learn from data (c) clean screens (d) charge faster
26. 26.🏷️ 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
27. 27.True or false: “new data for testing” is good for training a model. (a) True (b) False
28. 28.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
29. 29.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) False (b) True
30. 30.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) True (b) False
31. 31.True or false: “new data for testing” is bad for training a model. (a) False (b) True
32. 32.True or false: “correct labels” is bad for training a model. (a) True (b) False
33. 33.🔍 Which is the odd one out? (a) new data for testing (b) only one kind of example (c) checking labels twice (d) clear, sharp examples
34. 34.True or false: “photos in many lights” is bad for training a model. (a) False (b) True
35. 35.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
36. 36.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) True (b) False
37. 37.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
38. 38.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
39. 39.Which of these is good for training a model? (a) wrong labels (b) only one kind of example (c) many varied examples (d) testing on training data
40. 40.True or false: “wrong labels” is bad for training a model. (a) False (b) True

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