Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 432 · 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? “Your library book is due on Monday” (a) spam (b) not spam
2. 2.🔍 Which is the odd one out? (a) copies of one photo (b) only one kind of example (c) correct labels (d) labels added at random
3. 3.🏷️ 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
4. 4.True or false: “copies of one photo” is bad for training a model. (a) True (b) False
5. 5.🏷️ 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
6. 6.Which of these is good for training a model? (a) testing on training data (b) checking labels twice (c) blurry, unclear photos (d) copies of one photo
7. 7.Which of these is good for training a model? (a) labels added at random (b) very few examples (c) many varied examples (d) testing on training data
8. 8.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) False (b) True
9. 9.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
10. 10.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
11. 11.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
12. 12.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
13. 13.Which of these is bad for training a model? (a) new data for testing (b) checking labels twice (c) wrong labels (d) many varied examples
14. 14.🔍 Which is the odd one out? (a) correct labels (b) only one kind of example (c) examples of every type (d) clear, sharp examples
15. 15.Which of these is good for training a model? (a) very few examples (b) testing on training data (c) correct labels (d) blurry, unclear photos
16. 16.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
17. 17.True or false: “blurry, unclear photos” is good for training a model. (a) True (b) False
18. 18.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
19. 19.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
20. 20.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) spam (b) not spam
21. 21.True or false: “very few examples” is bad for training a model. (a) False (b) True
22. 22.🔍 Which is the odd one out? (a) examples of every type (b) copies of one photo (c) checking labels twice (d) new data for testing
23. 23.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it will turn yellow (c) it may get it wrong (d) it will shut down
24. 24.True or false: “very few examples” is good for training a model. (a) False (b) True
25. 25.True or false: “new data for testing” is bad for training a model. (a) True (b) False
26. 26.🏷️ What is a “label” in machine learning? (a) the font size (b) the right answer tag (c) a sticker on a laptop (d) the price
27. 27.🔍 Which is the odd one out? (a) checking labels twice (b) clear, sharp examples (c) correct labels (d) labels added at random
28. 28.🏷️ 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
29. 29.True or false: “many varied examples” is good for training a model. (a) False (b) True
30. 30.Which of these is good for training a model? (a) only one kind of example (b) new data for testing (c) labels added at random (d) testing on training data
31. 31.🏷️ 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
32. 32.Which of these is good for training a model? (a) only one kind of example (b) examples of every type (c) blurry, unclear photos (d) very few examples
33. 33.True or false: “photos in many lights” is good for training a model. (a) True (b) False
34. 34.Which of these is bad for training a model? (a) only one kind of example (b) new data for testing (c) correct labels (d) photos in many lights
35. 35.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
36. 36.🔍 Which is the odd one out? (a) many varied examples (b) checking labels twice (c) clear, sharp examples (d) very few examples
37. 37.Which of these is good for training a model? (a) copies of one photo (b) only one kind of example (c) photos in many lights (d) very few examples
38. 38.🏷️ 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
39. 39.🧠 Machine learning is a way for computers to… (a) clean screens (b) learn from data (c) charge faster (d) print pages
40. 40.🔍 Which is the odd one out? (a) labels added at random (b) blurry, unclear photos (c) testing on training data (d) clear, sharp examples

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