Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 363 · 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 of these is good for training a model? (a) labels added at random (b) photos in many lights (c) very few examples (d) only one kind of example
2. 2.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
3. 3.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) True (b) False
4. 4.🥭 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 be perfect (d) it will shut down
5. 5.Which of these is bad for training a model? (a) many varied examples (b) new data for testing (c) blurry, unclear photos (d) photos in many lights
6. 6.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
7. 7.True or false: “clear, sharp examples” is good for training a model. (a) True (b) False
8. 8.True or false: “only one kind of example” is bad for training a model. (a) False (b) True
9. 9.📚 Usually, more good examples make a model… (a) change colour (b) forget everything (c) better at its task (d) slower to switch on
10. 10.🔍 Which is the odd one out? (a) many varied examples (b) correct labels (c) clear, sharp examples (d) only one kind of example
11. 11.Which of these is good for training a model? (a) labels added at random (b) wrong labels (c) correct labels (d) only one kind of example
12. 12.🔍 Which is the odd one out? (a) blurry, unclear photos (b) correct labels (c) testing on training data (d) very few examples
13. 13.Which of these is bad for training a model? (a) checking labels twice (b) labels added at random (c) correct labels (d) photos in many lights
14. 14.🏷️ 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
15. 15.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
16. 16.Which of these is bad for training a model? (a) photos in many lights (b) testing on training data (c) examples of every type (d) correct labels
17. 17.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
18. 18.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
19. 19.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) False (b) True
20. 20.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
21. 21.🏷️ 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
22. 22.True or false: “many varied examples” is bad for training a model. (a) True (b) False
23. 23.True or false: “very few examples” is bad for training a model. (a) False (b) True
24. 24.🔍 Which is the odd one out? (a) testing on training data (b) only one kind of example (c) new data for testing (d) copies of one photo
25. 25.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
26. 26.True or false: “correct labels” is good for training a model. (a) False (b) True
27. 27.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
28. 28.🔍 Which is the odd one out? (a) testing on training data (b) wrong labels (c) labels added at random (d) clear, sharp examples
29. 29.🔍 Which is the odd one out? (a) checking labels twice (b) blurry, unclear photos (c) only one kind of example (d) copies of one photo
30. 30.True or false: “many varied examples” is good for training a model. (a) True (b) False
31. 31.🔍 Which is the odd one out? (a) very few examples (b) labels added at random (c) photos in many lights (d) copies of one photo
32. 32.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) True (b) False
33. 33.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
34. 34.🔍 Which is the odd one out? (a) labels added at random (b) checking labels twice (c) many varied examples (d) examples of every type
35. 35.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) many labelled photos (c) one single photo (d) a list of rules only
36. 36.True or false: “examples of every type” is bad for training a model. (a) True (b) False
37. 37.🔍 Which is the odd one out? (a) photos in many lights (b) new data for testing (c) very few examples (d) correct labels
38. 38.Which of these is bad for training a model? (a) examples of every type (b) photos in many lights (c) only one kind of example (d) correct labels
39. 39.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) True (b) False
40. 40.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False

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