Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 277 · 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? “Please buy milk on the way home” (a) spam (b) not spam
2. 2.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
3. 3.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) True (b) False
4. 4.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
5. 5.True or false: “only one kind of example” is good for training a model. (a) False (b) True
6. 6.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
7. 7.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) True (b) False
8. 8.Which of these is bad for training a model? (a) new data for testing (b) many varied examples (c) wrong labels (d) examples of every type
9. 9.🔍 Which is the odd one out? (a) blurry, unclear photos (b) labels added at random (c) checking labels twice (d) copies of one photo
10. 10.Which of these is good for training a model? (a) copies of one photo (b) blurry, unclear photos (c) examples of every type (d) labels added at random
11. 11.🔍 Which is the odd one out? (a) many varied examples (b) photos in many lights (c) clear, sharp examples (d) copies of one photo
12. 12.Which of these is good for training a model? (a) very few examples (b) copies of one photo (c) testing on training data (d) clear, sharp examples
13. 13.Which of these is bad for training a model? (a) many varied examples (b) correct labels (c) examples of every type (d) very few examples
14. 14.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) False (b) True
15. 15.🥭 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
16. 16.True or false: “examples of every type” is good for training a model. (a) False (b) True
17. 17.🔍 Which is the odd one out? (a) very few examples (b) new data for testing (c) testing on training data (d) blurry, unclear photos
18. 18.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) False (b) True
19. 19.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
20. 20.True or false: “clear, sharp examples” is good for training a model. (a) False (b) True
21. 21.True or false: “new data for testing” is bad for training a model. (a) False (b) True
22. 22.🏷️ 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
23. 23.True or false: “photos in many lights” is good for training a model. (a) True (b) False
24. 24.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
25. 25.Which of these is good for training a model? (a) testing on training data (b) only one kind of example (c) very few examples (d) many varied examples
26. 26.🔍 Which is the odd one out? (a) many varied examples (b) new data for testing (c) photos in many lights (d) very few examples
27. 27.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) False (b) True
28. 28.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) True (b) False
29. 29.📚 Usually, more good examples make a model… (a) slower to switch on (b) better at its task (c) forget everything (d) change colour
30. 30.Which of these is bad for training a model? (a) clear, sharp examples (b) examples of every type (c) new data for testing (d) only one kind of example
31. 31.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
32. 32.Which of these is good for training a model? (a) wrong labels (b) testing on training data (c) only one kind of example (d) correct labels
33. 33.Which of these is bad for training a model? (a) correct labels (b) testing on training data (c) many varied examples (d) photos in many lights
34. 34.Which of these is bad for training a model? (a) new data for testing (b) examples of every type (c) correct labels (d) blurry, unclear photos
35. 35.True or false: “copies of one photo” is bad for training a model. (a) False (b) True
36. 36.🏷️ 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
37. 37.🏷️ 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
38. 38.True or false: “new data for testing” is good for training a model. (a) True (b) False
39. 39.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) a list of rules only (c) many labelled photos (d) one single photo
40. 40.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) False (b) True

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