Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 393 · 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) correct labels (b) only one kind of example (c) examples of every type (d) photos in many lights
2. 2.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
3. 3.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True
4. 4.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
5. 5.🔍 Which is the odd one out? (a) examples of every type (b) labels added at random (c) photos in many lights (d) clear, sharp examples
6. 6.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
7. 7.🔍 Which is the odd one out? (a) copies of one photo (b) labels added at random (c) checking labels twice (d) very few examples
8. 8.🔍 Which is the odd one out? (a) wrong labels (b) checking labels twice (c) photos in many lights (d) many varied examples
9. 9.🏷️ 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
10. 10.🐶 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) many labelled photos (d) a song about dogs
11. 11.📚 Usually, more good examples make a model… (a) better at its task (b) slower to switch on (c) change colour (d) forget everything
12. 12.Which of these is bad for training a model? (a) correct labels (b) blurry, unclear photos (c) many varied examples (d) checking labels twice
13. 13.🔍 Which is the odd one out? (a) many varied examples (b) new data for testing (c) photos in many lights (d) copies of one photo
14. 14.🥭 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
15. 15.True or false: “checking labels twice” is good for training a model. (a) False (b) True
16. 16.True or false: “copies of one photo” is bad for training a model. (a) False (b) True
17. 17.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
18. 18.🏷️ 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
19. 19.True or false: “only one kind of example” is bad for training a model. (a) False (b) True
20. 20.🏷️ 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
21. 21.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
22. 22.Which of these is good for training a model? (a) only one kind of example (b) clear, sharp examples (c) testing on training data (d) very few examples
23. 23.🏷️ 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) not spam (b) spam
24. 24.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
25. 25.True or false: “examples of every type” is bad for training a model. (a) False (b) True
26. 26.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the price (c) the font size (d) the right answer tag
27. 27.🧠 Machine learning is a way for computers to… (a) charge faster (b) clean screens (c) learn from data (d) print pages
28. 28.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) True (b) False
29. 29.Which of these is good for training a model? (a) correct labels (b) only one kind of example (c) very few examples (d) testing on training data
30. 30.True or false: “only one kind of example” is good for training a model. (a) True (b) False
31. 31.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
32. 32.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
33. 33.True or false: “clear, sharp examples” is good for training a model. (a) False (b) True
34. 34.True or false: “checking labels twice” is bad for training a model. (a) True (b) False
35. 35.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
36. 36.Which of these is bad for training a model? (a) checking labels twice (b) many varied examples (c) clear, sharp examples (d) testing on training data
37. 37.Which of these is good for training a model? (a) copies of one photo (b) many varied examples (c) testing on training data (d) labels added at random
38. 38.Which of these is bad for training a model? (a) checking labels twice (b) many varied examples (c) examples of every type (d) labels added at random
39. 39.🔍 Which is the odd one out? (a) blurry, unclear photos (b) labels added at random (c) copies of one photo (d) many varied examples
40. 40.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training

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