Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 132 · 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: “testing on training data” is good for training a model. (a) True (b) False
2. 2.🏷️ 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
3. 3.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) True (b) False
4. 4.True or false: “examples of every type” is good for training a model. (a) False (b) True
5. 5.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) True (b) False
6. 6.Which of these is good for training a model? (a) testing on training data (b) very few examples (c) wrong labels (d) clear, sharp examples
7. 7.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) spam (b) not spam
8. 8.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
9. 9.True or false: “only one kind of example” is bad for training a model. (a) True (b) False
10. 10.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
11. 11.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
12. 12.Which of these is good for training a model? (a) blurry, unclear photos (b) labels added at random (c) only one kind of example (d) correct labels
13. 13.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
14. 14.Which of these is good for training a model? (a) testing on training data (b) very few examples (c) labels added at random (d) many varied examples
15. 15.🔍 Which is the odd one out? (a) photos in many lights (b) new data for testing (c) examples of every type (d) testing on training data
16. 16.🥭 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 may get it wrong (d) it will turn yellow
17. 17.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
18. 18.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) False (b) True
19. 19.🔍 Which is the odd one out? (a) photos in many lights (b) checking labels twice (c) correct labels (d) very few examples
20. 20.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
21. 21.Which of these is good for training a model? (a) testing on training data (b) wrong labels (c) photos in many lights (d) only one kind of example
22. 22.Which of these is bad for training a model? (a) testing on training data (b) examples of every type (c) many varied examples (d) photos in many lights
23. 23.🏷️ 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
24. 24.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
25. 25.Which of these is bad for training a model? (a) copies of one photo (b) photos in many lights (c) correct labels (d) clear, sharp examples
26. 26.🔍 Which is the odd one out? (a) blurry, unclear photos (b) very few examples (c) examples of every type (d) labels added at random
27. 27.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the right answer tag (c) the price (d) the font size
28. 28.True or false: “photos in many lights” is good for training a model. (a) False (b) True
29. 29.Which of these is bad for training a model? (a) clear, sharp examples (b) only one kind of example (c) new data for testing (d) examples of every type
30. 30.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
31. 31.True or false: “wrong labels” is bad for training a model. (a) True (b) False
32. 32.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) a song about dogs (c) a list of rules only (d) one single photo
33. 33.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
34. 34.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
35. 35.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
36. 36.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
37. 37.🏷️ 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
38. 38.Which of these is bad for training a model? (a) new data for testing (b) blurry, unclear photos (c) checking labels twice (d) clear, sharp examples
39. 39.🔍 Which is the odd one out? (a) clear, sharp examples (b) very few examples (c) blurry, unclear photos (d) only one kind of example
40. 40.📚 Usually, more good examples make a model… (a) better at its task (b) change colour (c) slower to switch on (d) forget everything

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