Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 107 · 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.🏷️ 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
2. 2.Which of these is good for training a model? (a) blurry, unclear photos (b) wrong labels (c) many varied examples (d) testing on training data
3. 3.Which of these is good for training a model? (a) copies of one photo (b) correct labels (c) wrong labels (d) very few examples
4. 4.🔍 Which is the odd one out? (a) copies of one photo (b) testing on training data (c) clear, sharp examples (d) wrong labels
5. 5.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
6. 6.🏷️ 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
7. 7.🏷️ What is a “label” in machine learning? (a) the right answer tag (b) a sticker on a laptop (c) the font size (d) the price
8. 8.🔍 Which is the odd one out? (a) wrong labels (b) labels added at random (c) copies of one photo (d) photos in many lights
9. 9.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) spam (b) not spam
10. 10.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) False (b) True
11. 11.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) False (b) True
12. 12.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) True (b) False
13. 13.🏷️ 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
14. 14.True or false: “checking labels twice” is good for training a model. (a) False (b) True
15. 15.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
16. 16.True or false: “clear, sharp examples” is good for training a model. (a) False (b) True
17. 17.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it will shut down (c) it will turn yellow (d) it may get it wrong
18. 18.Which of these is bad for training a model? (a) many varied examples (b) correct labels (c) checking labels twice (d) labels added at random
19. 19.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
20. 20.Which of these is good for training a model? (a) examples of every type (b) blurry, unclear photos (c) wrong labels (d) very few examples
21. 21.True or false: “wrong labels” is good for training a model. (a) False (b) True
22. 22.📚 Usually, more good examples make a model… (a) slower to switch on (b) forget everything (c) change colour (d) better at its task
23. 23.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
24. 24.🐶 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
25. 25.Which of these is good for training a model? (a) only one kind of example (b) copies of one photo (c) labels added at random (d) new data for testing
26. 26.🔍 Which is the odd one out? (a) examples of every type (b) copies of one photo (c) correct labels (d) new data for testing
27. 27.🔍 Which is the odd one out? (a) new data for testing (b) very few examples (c) clear, sharp examples (d) correct labels
28. 28.True or false: “new data for testing” is bad for training a model. (a) True (b) False
29. 29.🔍 Which is the odd one out? (a) blurry, unclear photos (b) labels added at random (c) very few examples (d) new data for testing
30. 30.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
31. 31.Which of these is bad for training a model? (a) examples of every type (b) only one kind of example (c) photos in many lights (d) many varied examples
32. 32.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) False (b) True
33. 33.True or false: “labels added at random” is bad for training a model. (a) False (b) True
34. 34.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
35. 35.🔍 Which is the odd one out? (a) only one kind of example (b) examples of every type (c) correct labels (d) many varied examples
36. 36.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) spam (b) not spam
37. 37.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
38. 38.🏷️ 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
39. 39.Which of these is good for training a model? (a) clear, sharp examples (b) only one kind of example (c) blurry, unclear photos (d) very few examples
40. 40.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False

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