Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 262 · 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.True or false: “wrong labels” is good for training a model. (a) False (b) True
2. 2.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) many labelled photos (c) a song about dogs (d) one single photo
3. 3.📚 Usually, more good examples make a model… (a) slower to switch on (b) better at its task (c) change colour (d) forget everything
4. 4.🏷️ 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
5. 5.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) False (b) True
6. 6.🔍 Which is the odd one out? (a) wrong labels (b) very few examples (c) checking labels twice (d) testing on training data
7. 7.🥭 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
8. 8.True or false: “correct labels” is bad for training a model. (a) False (b) True
9. 9.🏷️ 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) spam (b) not spam
10. 10.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
11. 11.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True
12. 12.🔍 Which is the odd one out? (a) labels added at random (b) photos in many lights (c) copies of one photo (d) only one kind of example
13. 13.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True
14. 14.🏷️ 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
15. 15.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) True (b) False
16. 16.Which of these is bad for training a model? (a) examples of every type (b) correct labels (c) very few examples (d) clear, sharp examples
17. 17.🔍 Which is the odd one out? (a) blurry, unclear photos (b) examples of every type (c) wrong labels (d) very few examples
18. 18.True or false: “blurry, unclear photos” is bad for training a model. (a) False (b) True
19. 19.🔍 Which is the odd one out? (a) many varied examples (b) examples of every type (c) photos in many lights (d) blurry, unclear photos
20. 20.🔍 Which is the odd one out? (a) checking labels twice (b) photos in many lights (c) copies of one photo (d) new data for testing
21. 21.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) not spam (b) spam
22. 22.🔍 Which is the odd one out? (a) wrong labels (b) correct labels (c) copies of one photo (d) very few examples
23. 23.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
24. 24.Which of these is good for training a model? (a) labels added at random (b) copies of one photo (c) blurry, unclear photos (d) new data for testing
25. 25.True or false: “correct labels” is good for training a model. (a) False (b) True
26. 26.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
27. 27.Which of these is bad for training a model? (a) clear, sharp examples (b) correct labels (c) checking labels twice (d) only one kind of example
28. 28.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) True (b) False
29. 29.🏷️ 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
30. 30.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) not spam (b) spam
31. 31.🔍 Which is the odd one out? (a) blurry, unclear photos (b) very few examples (c) many varied examples (d) only one kind of example
32. 32.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) False (b) True
33. 33.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
34. 34.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) True (b) False
35. 35.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
36. 36.True or false: “photos in many lights” is bad for training a model. (a) False (b) True
37. 37.Which of these is bad for training a model? (a) copies of one photo (b) photos in many lights (c) many varied examples (d) clear, sharp examples
38. 38.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) True (b) False
39. 39.🏷️ 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
40. 40.Which of these is good for training a model? (a) testing on training data (b) very few examples (c) wrong labels (d) many varied examples

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