Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 234 · 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: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) False (b) True
2. 2.True or false: “clear, sharp examples” is good for training a model. (a) False (b) True
3. 3.🔍 Which is the odd one out? (a) checking labels twice (b) examples of every type (c) testing on training data (d) many varied examples
4. 4.🔍 Which is the odd one out? (a) photos in many lights (b) examples of every type (c) correct labels (d) wrong labels
5. 5.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
6. 6.Which of these is good for training a model? (a) only one kind of example (b) wrong labels (c) correct labels (d) copies of one photo
7. 7.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
8. 8.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
9. 9.🔍 Which is the odd one out? (a) examples of every type (b) wrong labels (c) only one kind of example (d) blurry, unclear photos
10. 10.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
11. 11.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
12. 12.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
13. 13.🔍 Which is the odd one out? (a) photos in many lights (b) wrong labels (c) labels added at random (d) blurry, unclear photos
14. 14.Which of these is bad for training a model? (a) blurry, unclear photos (b) many varied examples (c) correct labels (d) new data for testing
15. 15.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the price (c) the right answer tag (d) the font size
16. 16.True or false: “very few examples” is good for training a model. (a) False (b) True
17. 17.True or false: “correct labels” is bad for training a model. (a) False (b) True
18. 18.True or false: “correct labels” is good for training a model. (a) True (b) False
19. 19.🔍 Which is the odd one out? (a) labels added at random (b) many varied examples (c) wrong labels (d) copies of one photo
20. 20.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) not spam (b) spam
21. 21.True or false: “only one kind of example” is good for training a model. (a) True (b) False
22. 22.🏷️ 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
23. 23.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
24. 24.📚 Usually, more good examples make a model… (a) slower to switch on (b) change colour (c) forget everything (d) better at its task
25. 25.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
26. 26.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) a song about dogs (c) one single photo (d) a list of rules only
27. 27.True or false: “many varied examples” is good for training a model. (a) False (b) True
28. 28.🔍 Which is the odd one out? (a) very few examples (b) many varied examples (c) examples of every type (d) correct labels
29. 29.Which of these is good for training a model? (a) copies of one photo (b) new data for testing (c) very few examples (d) blurry, unclear photos
30. 30.🏷️ 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
31. 31.Which of these is bad for training a model? (a) correct labels (b) very few examples (c) many varied examples (d) new data for testing
32. 32.🏷️ 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
33. 33.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) False (b) True
34. 34.🔍 Which is the odd one out? (a) photos in many lights (b) correct labels (c) many varied examples (d) only one kind of example
35. 35.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
36. 36.Which of these is good for training a model? (a) blurry, unclear photos (b) very few examples (c) testing on training data (d) many varied examples
37. 37.Which of these is bad for training a model? (a) testing on training data (b) checking labels twice (c) new data for testing (d) clear, sharp examples
38. 38.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
39. 39.🧠 Machine learning is a way for computers to… (a) learn from data (b) charge faster (c) clean screens (d) print pages
40. 40.True or false: “very few examples” is bad for training a model. (a) False (b) True

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