Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 271 · 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? “Please buy milk on the way home” (a) spam (b) not spam
2. 2.Which of these is good for training a model? (a) only one kind of example (b) copies of one photo (c) photos in many lights (d) wrong labels
3. 3.🏷️ What is a “label” in machine learning? (a) the price (b) a sticker on a laptop (c) the font size (d) the right answer tag
4. 4.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
5. 5.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) a list of rules only (c) one single photo (d) many labelled photos
6. 6.True or false: “many varied examples” is good for training a model. (a) False (b) True
7. 7.📚 Usually, more good examples make a model… (a) better at its task (b) change colour (c) slower to switch on (d) forget everything
8. 8.🔍 Which is the odd one out? (a) clear, sharp examples (b) checking labels twice (c) photos in many lights (d) only one kind of example
9. 9.True or false: “testing on training data” is bad for training a model. (a) True (b) False
10. 10.True or false: “copies of one photo” is bad for training a model. (a) True (b) False
11. 11.🔍 Which is the odd one out? (a) many varied examples (b) examples of every type (c) copies of one photo (d) new data for testing
12. 12.Which of these is good for training a model? (a) labels added at random (b) clear, sharp examples (c) very few examples (d) only one kind of example
13. 13.🥭 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 be perfect (d) it will turn yellow
14. 14.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
15. 15.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) True (b) False
16. 16.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
17. 17.Which of these is good for training a model? (a) wrong labels (b) labels added at random (c) examples of every type (d) only one kind of example
18. 18.🔍 Which is the odd one out? (a) checking labels twice (b) many varied examples (c) labels added at random (d) examples of every type
19. 19.🏷️ 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
20. 20.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) not spam (b) spam
21. 21.🔍 Which is the odd one out? (a) many varied examples (b) photos in many lights (c) testing on training data (d) new data for testing
22. 22.Which of these is bad for training a model? (a) photos in many lights (b) very few examples (c) clear, sharp examples (d) correct labels
23. 23.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
24. 24.Which of these is good for training a model? (a) blurry, unclear photos (b) checking labels twice (c) very few examples (d) wrong labels
25. 25.True or false: “correct labels” is bad for training a model. (a) True (b) False
26. 26.True or false: “only one kind of example” is bad for training a model. (a) False (b) True
27. 27.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
28. 28.True or false: “clear, sharp examples” is good for training a model. (a) True (b) False
29. 29.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
30. 30.True or false: “checking labels twice” is good for training a model. (a) False (b) True
31. 31.🧠 Machine learning is a way for computers to… (a) charge faster (b) print pages (c) learn from data (d) clean screens
32. 32.Which of these is good for training a model? (a) wrong labels (b) only one kind of example (c) very few examples (d) new data for testing
33. 33.Which of these is bad for training a model? (a) photos in many lights (b) correct labels (c) new data for testing (d) testing on training data
34. 34.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
35. 35.🏷️ 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
36. 36.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
37. 37.True or false: “checking labels twice” is bad for training a model. (a) False (b) True
38. 38.🔍 Which is the odd one out? (a) new data for testing (b) checking labels twice (c) correct labels (d) very few examples
39. 39.🔍 Which is the odd one out? (a) photos in many lights (b) only one kind of example (c) wrong labels (d) testing on training data
40. 40.True or false: “correct labels” is good for training a model. (a) True (b) False

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