Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 188 · 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) copies of one photo (b) wrong labels (c) examples of every type (d) blurry, unclear photos
2. 2.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) False (b) True
3. 3.🔍 Which is the odd one out? (a) clear, sharp examples (b) correct labels (c) blurry, unclear photos (d) examples of every type
4. 4.True or false: “many varied examples” is bad for training a model. (a) False (b) True
5. 5.Which of these is good for training a model? (a) wrong labels (b) very few examples (c) blurry, unclear photos (d) checking labels twice
6. 6.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
7. 7.🥭 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
8. 8.📚 Usually, more good examples make a model… (a) better at its task (b) slower to switch on (c) forget everything (d) change colour
9. 9.🏷️ 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
10. 10.Which of these is bad for training a model? (a) correct labels (b) examples of every type (c) new data for testing (d) labels added at random
11. 11.Which of these is bad for training a model? (a) checking labels twice (b) wrong labels (c) many varied examples (d) clear, sharp examples
12. 12.🏷️ 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
13. 13.🏷️ 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
14. 14.True or false: “checking labels twice” is bad for training a model. (a) True (b) False
15. 15.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
16. 16.🔍 Which is the odd one out? (a) only one kind of example (b) testing on training data (c) new data for testing (d) very few examples
17. 17.True or false: “wrong labels” is bad for training a model. (a) True (b) False
18. 18.True or false: “testing on training data” is good for training a model. (a) False (b) True
19. 19.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
20. 20.True or false: “many varied examples” is good for training a model. (a) False (b) True
21. 21.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) False (b) True
22. 22.Which of these is good for training a model? (a) very few examples (b) correct labels (c) only one kind of example (d) testing on training data
23. 23.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
24. 24.🔍 Which is the odd one out? (a) very few examples (b) photos in many lights (c) only one kind of example (d) copies of one photo
25. 25.🔍 Which is the odd one out? (a) many varied examples (b) testing on training data (c) very few examples (d) blurry, unclear photos
26. 26.🔍 Which is the odd one out? (a) testing on training data (b) checking labels twice (c) only one kind of example (d) wrong labels
27. 27.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
28. 28.🔍 Which is the odd one out? (a) clear, sharp examples (b) wrong labels (c) new data for testing (d) checking labels twice
29. 29.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
30. 30.🏷️ 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
31. 31.🔍 Which is the odd one out? (a) only one kind of example (b) many varied examples (c) correct labels (d) new data for testing
32. 32.🏷️ What is a “label” in machine learning? (a) the font size (b) a sticker on a laptop (c) the right answer tag (d) the price
33. 33.Which of these is good for training a model? (a) new data for testing (b) labels added at random (c) copies of one photo (d) testing on training data
34. 34.True or false: “wrong labels” is good for training a model. (a) False (b) True
35. 35.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
36. 36.🏷️ 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
37. 37.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
38. 38.🧠 Machine learning is a way for computers to… (a) clean screens (b) learn from data (c) print pages (d) charge faster
39. 39.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
40. 40.🏷️ 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

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