Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 405 · 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 “Your library book is due on Monday” should be labelled “not spam”. (a) True (b) False
2. 2.🔍 Which is the odd one out? (a) very few examples (b) labels added at random (c) many varied examples (d) testing on training data
3. 3.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
4. 4.Which of these is good for training a model? (a) copies of one photo (b) blurry, unclear photos (c) wrong labels (d) photos in many lights
5. 5.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) spam (b) not spam
6. 6.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
7. 7.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
8. 8.🔍 Which is the odd one out? (a) only one kind of example (b) testing on training data (c) labels added at random (d) new data for testing
9. 9.Which of these is bad for training a model? (a) new data for testing (b) correct labels (c) testing on training data (d) many varied examples
10. 10.Which of these is bad for training a model? (a) many varied examples (b) clear, sharp examples (c) only one kind of example (d) examples of every type
11. 11.True or false: “labels added at random” is bad for training a model. (a) True (b) False
12. 12.Which of these is good for training a model? (a) only one kind of example (b) correct labels (c) labels added at random (d) copies of one photo
13. 13.Which of these is bad for training a model? (a) labels added at random (b) checking labels twice (c) clear, sharp examples (d) many varied examples
14. 14.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a song about dogs (c) a list of rules only (d) many labelled photos
15. 15.📚 Usually, more good examples make a model… (a) better at its task (b) slower to switch on (c) change colour (d) forget everything
16. 16.🧠 Machine learning is a way for computers to… (a) learn from data (b) clean screens (c) charge faster (d) print pages
17. 17.Which of these is good for training a model? (a) wrong labels (b) many varied examples (c) testing on training data (d) blurry, unclear photos
18. 18.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
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.Which of these is good for training a model? (a) copies of one photo (b) wrong labels (c) very few examples (d) checking labels twice
21. 21.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
22. 22.True or false: “correct labels” is bad for training a model. (a) False (b) True
23. 23.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) False (b) True
24. 24.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) not spam (b) spam
25. 25.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it may get it wrong (c) it will turn yellow (d) it will be perfect
26. 26.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
27. 27.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
28. 28.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
29. 29.Which of these is bad for training a model? (a) photos in many lights (b) new data for testing (c) copies of one photo (d) many varied examples
30. 30.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
31. 31.Which of these is bad for training a model? (a) correct labels (b) blurry, unclear photos (c) new data for testing (d) checking labels twice
32. 32.🔍 Which is the odd one out? (a) checking labels twice (b) examples of every type (c) very few examples (d) correct labels
33. 33.🏷️ 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
34. 34.Which of these is good for training a model? (a) very few examples (b) only one kind of example (c) copies of one photo (d) examples of every type
35. 35.🔍 Which is the odd one out? (a) clear, sharp examples (b) many varied examples (c) only one kind of example (d) examples of every type
36. 36.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) spam (b) not spam
37. 37.🏷️ 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
38. 38.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
39. 39.Which of these is bad for training a model? (a) correct labels (b) checking labels twice (c) very few examples (d) many varied examples
40. 40.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training

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