Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 31 · 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.🔍 Which is the odd one out? (a) photos in many lights (b) wrong labels (c) testing on training data (d) blurry, unclear photos
2. 2.Which of these is good for training a model? (a) examples of every type (b) only one kind of example (c) blurry, unclear photos (d) labels added at random
3. 3.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) False (b) True
4. 4.Which of these is good for training a model? (a) correct labels (b) testing on training data (c) wrong labels (d) labels added at random
5. 5.Which of these is good for training a model? (a) labels added at random (b) blurry, unclear photos (c) wrong labels (d) checking labels twice
6. 6.🧠 Machine learning is a way for computers to… (a) print pages (b) charge faster (c) learn from data (d) clean screens
7. 7.True or false: “only one kind of example” is good for training a model. (a) False (b) True
8. 8.Which of these is bad for training a model? (a) new data for testing (b) correct labels (c) examples of every type (d) labels added at random
9. 9.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True
10. 10.🥭 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
11. 11.🏷️ 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
12. 12.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
13. 13.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
14. 14.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) False (b) True
15. 15.🔍 Which is the odd one out? (a) labels added at random (b) blurry, unclear photos (c) testing on training data (d) correct labels
16. 16.🔍 Which is the odd one out? (a) new data for testing (b) examples of every type (c) correct labels (d) very few examples
17. 17.🏷️ 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
18. 18.🔍 Which is the odd one out? (a) clear, sharp examples (b) many varied examples (c) examples of every type (d) wrong labels
19. 19.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
20. 20.True or false: “testing on training data” is good for training a model. (a) True (b) False
21. 21.Which of these is bad for training a model? (a) examples of every type (b) many varied examples (c) correct labels (d) very few examples
22. 22.True or false: “copies of one photo” is bad for training a model. (a) True (b) False
23. 23.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
24. 24.🔍 Which is the odd one out? (a) labels added at random (b) checking labels twice (c) examples of every type (d) many varied examples
25. 25.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) True (b) False
26. 26.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
27. 27.Which of these is good for training a model? (a) very few examples (b) new data for testing (c) copies of one photo (d) testing on training data
28. 28.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) one single photo (c) a list of rules only (d) a song about dogs
29. 29.True or false: “many varied examples” is bad for training a model. (a) True (b) False
30. 30.True or false: “blurry, unclear photos” is good for training a model. (a) False (b) True
31. 31.🏷️ 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
32. 32.🔍 Which is the odd one out? (a) labels added at random (b) blurry, unclear photos (c) testing on training data (d) new data for testing
33. 33.Which of these is good for training a model? (a) only one kind of example (b) copies of one photo (c) many varied examples (d) wrong labels
34. 34.🔍 Which is the odd one out? (a) correct labels (b) testing on training data (c) new data for testing (d) photos in many lights
35. 35.🏷️ 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
36. 36.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) True (b) False
37. 37.🏷️ What is a “label” in machine learning? (a) the price (b) a sticker on a laptop (c) the font size (d) the right answer tag
38. 38.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
39. 39.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
40. 40.True or false: “labels added at random” is bad for training a model. (a) False (b) True

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