Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 572 · 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) not spam (b) spam
2. 2.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
3. 3.🔍 Which is the odd one out? (a) testing on training data (b) blurry, unclear photos (c) only one kind of example (d) clear, sharp examples
4. 4.True or false: “wrong labels” is good for training a model. (a) True (b) False
5. 5.Which of these is bad for training a model? (a) examples of every type (b) clear, sharp examples (c) photos in many lights (d) wrong labels
6. 6.🏷️ 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
7. 7.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) False (b) True
8. 8.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) True (b) False
9. 9.True or false: “new data for testing” is bad for training a model. (a) True (b) False
10. 10.True or false: “many varied examples” is bad for training a model. (a) True (b) False
11. 11.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) False (b) True
12. 12.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) True (b) False
13. 13.🔍 Which is the odd one out? (a) only one kind of example (b) blurry, unclear photos (c) new data for testing (d) very few examples
14. 14.🏷️ 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
15. 15.True or false: “correct labels” is bad for training a model. (a) False (b) True
16. 16.🏷️ 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
17. 17.🏷️ What is a “label” in machine learning? (a) the right answer tag (b) a sticker on a laptop (c) the price (d) the font size
18. 18.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) False (b) True
19. 19.Which of these is bad for training a model? (a) many varied examples (b) new data for testing (c) checking labels twice (d) testing on training data
20. 20.🔍 Which is the odd one out? (a) only one kind of example (b) labels added at random (c) wrong labels (d) many varied examples
21. 21.🏷️ 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
22. 22.True or false: “photos in many lights” is good for training a model. (a) False (b) True
23. 23.True or false: “correct labels” is good for training a model. (a) False (b) True
24. 24.Which of these is good for training a model? (a) many varied examples (b) labels added at random (c) very few examples (d) wrong labels
25. 25.🔍 Which is the odd one out? (a) many varied examples (b) checking labels twice (c) labels added at random (d) clear, sharp examples
26. 26.Which of these is good for training a model? (a) only one kind of example (b) very few examples (c) blurry, unclear photos (d) clear, sharp examples
27. 27.🔍 Which is the odd one out? (a) only one kind of example (b) wrong labels (c) blurry, unclear photos (d) photos in many lights
28. 28.🏷️ 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
29. 29.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
30. 30.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
31. 31.Which of these is bad for training a model? (a) photos in many lights (b) examples of every type (c) very few examples (d) correct labels
32. 32.True or false: “labels added at random” is bad for training a model. (a) False (b) True
33. 33.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
34. 34.🧠 Machine learning is a way for computers to… (a) clean screens (b) print pages (c) learn from data (d) charge faster
35. 35.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) not spam (b) spam
36. 36.True or false: “blurry, unclear photos” is bad for training a model. (a) True (b) False
37. 37.True or false: “very few examples” is good for training a model. (a) False (b) True
38. 38.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it will turn yellow (c) it will be perfect (d) it may get it wrong
39. 39.🔍 Which is the odd one out? (a) checking labels twice (b) photos in many lights (c) many varied examples (d) blurry, unclear photos
40. 40.🔍 Which is the odd one out? (a) wrong labels (b) examples of every type (c) very few examples (d) testing on training data

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