Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 246 · 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? “Share your OTP to get cashback” (a) spam (b) not spam
2. 2.Which of these is good for training a model? (a) wrong labels (b) blurry, unclear photos (c) clear, sharp examples (d) testing on training data
3. 3.Which of these is good for training a model? (a) correct labels (b) wrong labels (c) labels added at random (d) only one kind of example
4. 4.True or false: “labels added at random” is bad for training a model. (a) True (b) False
5. 5.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
6. 6.True or false: “examples of every type” is bad for training a model. (a) True (b) False
7. 7.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) True (b) False
8. 8.🐶 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) one single photo (d) many labelled photos
9. 9.🔍 Which is the odd one out? (a) blurry, unclear photos (b) testing on training data (c) only one kind of example (d) new data for testing
10. 10.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
11. 11.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) True (b) False
12. 12.🔍 Which is the odd one out? (a) labels added at random (b) testing on training data (c) many varied examples (d) wrong labels
13. 13.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
14. 14.Which of these is bad for training a model? (a) wrong labels (b) checking labels twice (c) many varied examples (d) examples of every type
15. 15.True or false: “wrong labels” is good for training a model. (a) True (b) False
16. 16.🏷️ 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
17. 17.True or false: “wrong labels” is bad for training a model. (a) False (b) True
18. 18.Which of these is good for training a model? (a) photos in many lights (b) labels added at random (c) wrong labels (d) copies of one photo
19. 19.True or false: “photos in many lights” is bad for training a model. (a) False (b) True
20. 20.🔍 Which is the odd one out? (a) checking labels twice (b) many varied examples (c) clear, sharp examples (d) testing on training data
21. 21.📚 Usually, more good examples make a model… (a) slower to switch on (b) change colour (c) better at its task (d) forget everything
22. 22.Which of these is bad for training a model? (a) many varied examples (b) only one kind of example (c) new data for testing (d) correct labels
23. 23.True or false: “new data for testing” is bad for training a model. (a) True (b) False
24. 24.True or false: “examples of every type” is good for training a model. (a) True (b) False
25. 25.🔍 Which is the odd one out? (a) correct labels (b) many varied examples (c) examples of every type (d) very few examples
26. 26.🔍 Which is the odd one out? (a) very few examples (b) copies of one photo (c) blurry, unclear photos (d) correct labels
27. 27.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it may get it wrong (c) it will shut down (d) it will be perfect
28. 28.True or false: “photos in many lights” is good for training a model. (a) True (b) False
29. 29.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) not spam (b) spam
30. 30.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
31. 31.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
32. 32.True or false: “checking labels twice” is good for training a model. (a) False (b) True
33. 33.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
34. 34.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
35. 35.True or false: “copies of one photo” is bad for training a model. (a) False (b) True
36. 36.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
37. 37.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
38. 38.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) False (b) True
39. 39.Which of these is bad for training a model? (a) very few examples (b) many varied examples (c) checking labels twice (d) new data for testing
40. 40.🔍 Which is the odd one out? (a) copies of one photo (b) clear, sharp examples (c) correct labels (d) photos in many lights

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