Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 483 · 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: only one kind of example? (a) bad for training (b) good for training
2. 2.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) not spam (b) spam
3. 3.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) True (b) False
4. 4.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
5. 5.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) a song about dogs (c) one single photo (d) a list of rules only
6. 6.Which of these is bad for training a model? (a) correct labels (b) examples of every type (c) copies of one photo (d) clear, sharp examples
7. 7.True or false: “new data for testing” is bad for training a model. (a) True (b) False
8. 8.True or false: “many varied examples” is good for training a model. (a) False (b) True
9. 9.Which of these is good for training a model? (a) copies of one photo (b) testing on training data (c) photos in many lights (d) wrong labels
10. 10.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) not spam (b) spam
11. 11.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
12. 12.🔍 Which is the odd one out? (a) wrong labels (b) very few examples (c) checking labels twice (d) blurry, unclear photos
13. 13.Which of these is good for training a model? (a) copies of one photo (b) very few examples (c) correct labels (d) only one kind of example
14. 14.📚 Usually, more good examples make a model… (a) forget everything (b) better at its task (c) change colour (d) slower to switch on
15. 15.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
16. 16.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
17. 17.Which of these is good for training a model? (a) very few examples (b) wrong labels (c) checking labels twice (d) testing on training data
18. 18.🔍 Which is the odd one out? (a) testing on training data (b) many varied examples (c) examples of every type (d) checking labels twice
19. 19.🔍 Which is the odd one out? (a) many varied examples (b) wrong labels (c) correct labels (d) new data for testing
20. 20.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it will be perfect (c) it will shut down (d) it may get it wrong
21. 21.🏷️ 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
22. 22.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) True (b) False
23. 23.Which of these is good for training a model? (a) only one kind of example (b) copies of one photo (c) testing on training data (d) examples of every type
24. 24.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) True (b) False
25. 25.🏷️ 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
26. 26.🏷️ 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
27. 27.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) True (b) False
28. 28.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
29. 29.Which of these is good for training a model? (a) very few examples (b) new data for testing (c) copies of one photo (d) wrong labels
30. 30.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) True (b) False
31. 31.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
32. 32.Which of these is bad for training a model? (a) new data for testing (b) photos in many lights (c) testing on training data (d) many varied examples
33. 33.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
34. 34.🔍 Which is the odd one out? (a) testing on training data (b) examples of every type (c) labels added at random (d) only one kind of example
35. 35.🏷️ 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
36. 36.🔍 Which is the odd one out? (a) clear, sharp examples (b) wrong labels (c) testing on training data (d) blurry, unclear photos
37. 37.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
38. 38.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
39. 39.🏷️ 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
40. 40.Which of these is bad for training a model? (a) only one kind of example (b) many varied examples (c) new data for testing (d) correct labels

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