Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 189 · 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: labels added at random? (a) good for training (b) bad for training
2. 2.Which of these is bad for training a model? (a) checking labels twice (b) many varied examples (c) clear, sharp examples (d) only one kind of example
3. 3.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) not spam (b) spam
4. 4.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) a song about dogs (c) many labelled photos (d) one single photo
5. 5.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True
6. 6.Which of these is good for training a model? (a) very few examples (b) wrong labels (c) examples of every type (d) only one kind of example
7. 7.Which of these is good for training a model? (a) testing on training data (b) wrong labels (c) very few examples (d) photos in many lights
8. 8.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
9. 9.🏷️ 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
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) spam (b) not spam
11. 11.🥭 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
12. 12.True or false: “many varied examples” is bad for training a model. (a) False (b) True
13. 13.🔍 Which is the odd one out? (a) examples of every type (b) very few examples (c) labels added at random (d) blurry, unclear photos
14. 14.Which of these is good for training a model? (a) copies of one photo (b) only one kind of example (c) new data for testing (d) labels added at random
15. 15.🏷️ 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) not spam (b) spam
16. 16.🏷️ 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
17. 17.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
18. 18.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) True (b) False
19. 19.True or false: “labels added at random” is bad for training a model. (a) False (b) True
20. 20.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) spam (b) not spam
21. 21.True or false: “only one kind of example” is bad for training a model. (a) False (b) True
22. 22.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
23. 23.🏷️ 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
24. 24.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
25. 25.🔍 Which is the odd one out? (a) copies of one photo (b) wrong labels (c) labels added at random (d) checking labels twice
26. 26.📚 Usually, more good examples make a model… (a) change colour (b) better at its task (c) slower to switch on (d) forget everything
27. 27.True or false: the message “You won a free phone! Click now!” should be labelled “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.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) False (b) True
30. 30.Which of these is bad for training a model? (a) new data for testing (b) checking labels twice (c) examples of every type (d) copies of one photo
31. 31.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
32. 32.🔍 Which is the odd one out? (a) checking labels twice (b) photos in many lights (c) labels added at random (d) correct labels
33. 33.🔍 Which is the odd one out? (a) many varied examples (b) copies of one photo (c) checking labels twice (d) examples of every type
34. 34.Which of these is good for training a model? (a) blurry, unclear photos (b) copies of one photo (c) wrong labels (d) correct labels
35. 35.🔍 Which is the odd one out? (a) many varied examples (b) only one kind of example (c) clear, sharp examples (d) correct labels
36. 36.True or false: “copies of one photo” is good for training a model. (a) True (b) False
37. 37.True or false: “examples of every type” is good for training a model. (a) False (b) True
38. 38.True or false: “new data for testing” is bad for training a model. (a) True (b) False
39. 39.True or false: “labels added at random” is good for training a model. (a) False (b) True
40. 40.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) True (b) False

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