Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 152 · 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.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) a song about dogs (c) many labelled photos (d) one single photo
2. 2.Which of these is bad for training a model? (a) blurry, unclear photos (b) many varied examples (c) new data for testing (d) clear, sharp examples
3. 3.True or false: “very few examples” is bad for training a model. (a) False (b) True
4. 4.🏷️ 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
5. 5.Which of these is good for training a model? (a) photos in many lights (b) copies of one photo (c) testing on training data (d) labels added at random
6. 6.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
7. 7.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
8. 8.True or false: “only one kind of example” is bad for training a model. (a) False (b) True
9. 9.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) False (b) True
10. 10.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) True (b) False
11. 11.True or false: “checking labels twice” is good for training a model. (a) True (b) False
12. 12.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) False (b) True
13. 13.🔍 Which is the odd one out? (a) new data for testing (b) wrong labels (c) correct labels (d) many varied examples
14. 14.Which of these is bad for training a model? (a) many varied examples (b) clear, sharp examples (c) checking labels twice (d) only one kind of example
15. 15.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
16. 16.True or false: “correct labels” is good for training a model. (a) True (b) False
17. 17.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
18. 18.Which of these is good for training a model? (a) correct labels (b) labels added at random (c) very few examples (d) copies of one photo
19. 19.Which of these is good for training a model? (a) wrong labels (b) copies of one photo (c) many varied examples (d) only one kind of example
20. 20.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
21. 21.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the right answer tag (c) the font size (d) the price
22. 22.Which of these is good for training a model? (a) wrong labels (b) only one kind of example (c) labels added at random (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 shut down (b) it may get it wrong (c) it will turn yellow (d) it will be perfect
24. 24.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
25. 25.True or false: the message “Match practice moved to 5 pm” 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? “The class picnic is on Friday at 8 am” (a) spam (b) not spam
27. 27.Which of these is bad for training a model? (a) checking labels twice (b) many varied examples (c) wrong labels (d) clear, sharp examples
28. 28.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) True (b) False
29. 29.🔍 Which is the odd one out? (a) blurry, unclear photos (b) clear, sharp examples (c) correct labels (d) examples of every type
30. 30.Which of these is good for training a model? (a) testing on training data (b) blurry, unclear photos (c) examples of every type (d) labels added at random
31. 31.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
32. 32.🧠 Machine learning is a way for computers to… (a) learn from data (b) print pages (c) charge faster (d) clean screens
33. 33.True or false: “copies of one photo” is bad for training a model. (a) False (b) True
34. 34.🏷️ 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
35. 35.🔍 Which is the odd one out? (a) copies of one photo (b) checking labels twice (c) testing on training data (d) labels added at random
36. 36.True or false: “wrong labels” is good for training a model. (a) True (b) False
37. 37.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
38. 38.🔍 Which is the odd one out? (a) correct labels (b) examples of every type (c) many varied examples (d) very few examples
39. 39.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) not spam (b) spam
40. 40.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) spam (b) not spam

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