Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 427 · 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? “Send your password to claim a prize” (a) not spam (b) spam
2. 2.🔍 Which is the odd one out? (a) only one kind of example (b) labels added at random (c) new data for testing (d) blurry, unclear photos
3. 3.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
4. 4.Which of these is good for training a model? (a) many varied examples (b) very few examples (c) wrong labels (d) blurry, unclear photos
5. 5.Which of these is bad for training a model? (a) only one kind of example (b) checking labels twice (c) many varied examples (d) clear, sharp examples
6. 6.🧠 Machine learning is a way for computers to… (a) charge faster (b) learn from data (c) print pages (d) clean screens
7. 7.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
8. 8.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) not spam (b) spam
9. 9.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the price (c) the right answer tag (d) the font size
10. 10.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
11. 11.🏷️ 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
12. 12.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) one single photo (c) a song about dogs (d) a list of rules only
13. 13.Which of these is good for training a model? (a) labels added at random (b) blurry, unclear photos (c) photos in many lights (d) testing on training data
14. 14.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
15. 15.🔍 Which is the odd one out? (a) new data for testing (b) many varied examples (c) clear, sharp examples (d) very few examples
16. 16.True or false: “correct labels” is bad for training a model. (a) False (b) True
17. 17.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) True (b) False
18. 18.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
19. 19.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
20. 20.Which of these is bad for training a model? (a) checking labels twice (b) clear, sharp examples (c) blurry, unclear photos (d) correct labels
21. 21.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it will shut down (c) it may get it wrong (d) it will be perfect
22. 22.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
23. 23.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) True (b) False
24. 24.True or false: “copies of one photo” is bad for training a model. (a) False (b) True
25. 25.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
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: “photos in many lights” is bad for training a model. (a) False (b) True
28. 28.Which of these is bad for training a model? (a) many varied examples (b) labels added at random (c) examples of every type (d) clear, sharp examples
29. 29.True or false: “new data for testing” is bad for training a model. (a) True (b) False
30. 30.True or false: “correct labels” is good for training a model. (a) True (b) False
31. 31.🔍 Which is the odd one out? (a) new data for testing (b) correct labels (c) copies of one photo (d) clear, sharp examples
32. 32.Which of these is good for training a model? (a) blurry, unclear photos (b) labels added at random (c) wrong labels (d) clear, sharp examples
33. 33.🏷️ 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
34. 34.True or false: “many varied examples” is bad for training a model. (a) False (b) True
35. 35.True or false: “examples of every type” is bad for training a model. (a) True (b) False
36. 36.Which of these is bad for training a model? (a) clear, sharp examples (b) photos in many lights (c) examples of every type (d) testing on training data
37. 37.Which of these is good for training a model? (a) copies of one photo (b) only one kind of example (c) testing on training data (d) correct labels
38. 38.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) True (b) False
39. 39.True or false: “checking labels twice” is good for training a model. (a) True (b) False
40. 40.🏷️ 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

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