Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 15 · 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.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
2. 2.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
3. 3.🔍 Which is the odd one out? (a) testing on training data (b) blurry, unclear photos (c) correct labels (d) copies of one photo
4. 4.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) True (b) False
5. 5.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it will be perfect (c) it will turn yellow (d) it may get it wrong
6. 6.Which of these is good for training a model? (a) labels added at random (b) testing on training data (c) copies of one photo (d) photos in many lights
7. 7.🏷️ 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
8. 8.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
9. 9.Which of these is bad for training a model? (a) examples of every type (b) many varied examples (c) very few examples (d) clear, sharp examples
10. 10.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) True (b) False
11. 11.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
12. 12.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) not spam (b) spam
13. 13.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) True (b) False
14. 14.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) False (b) True
15. 15.🏷️ 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
16. 16.True or false: “blurry, unclear photos” is good for training a model. (a) True (b) False
17. 17.📚 Usually, more good examples make a model… (a) change colour (b) forget everything (c) better at its task (d) slower to switch on
18. 18.🔍 Which is the odd one out? (a) correct labels (b) many varied examples (c) copies of one photo (d) new data for testing
19. 19.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
20. 20.Which of these is good for training a model? (a) many varied examples (b) blurry, unclear photos (c) copies of one photo (d) wrong labels
21. 21.🔍 Which is the odd one out? (a) photos in many lights (b) clear, sharp examples (c) new data for testing (d) only one kind of example
22. 22.🐶 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
23. 23.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
24. 24.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) not spam (b) spam
25. 25.🏷️ 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
26. 26.🔍 Which is the odd one out? (a) new data for testing (b) very few examples (c) blurry, unclear photos (d) only one kind of example
27. 27.🔍 Which is the odd one out? (a) clear, sharp examples (b) photos in many lights (c) checking labels twice (d) testing on training data
28. 28.Which of these is good for training a model? (a) correct labels (b) testing on training data (c) very few examples (d) blurry, unclear photos
29. 29.🔍 Which is the odd one out? (a) photos in many lights (b) correct labels (c) blurry, unclear photos (d) examples of every type
30. 30.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) not spam (b) spam
31. 31.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) False (b) True
32. 32.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
33. 33.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
34. 34.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
35. 35.Which of these is good for training a model? (a) very few examples (b) copies of one photo (c) only one kind of example (d) checking labels twice
36. 36.Which of these is bad for training a model? (a) photos in many lights (b) wrong labels (c) new data for testing (d) examples of every type
37. 37.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
38. 38.True or false: “only one kind of example” is good for training a model. (a) False (b) True
39. 39.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
40. 40.Which of these is bad for training a model? (a) many varied examples (b) photos in many lights (c) testing on training data (d) correct labels

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