Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 51 · 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.🏷️ What is a “label” in machine learning? (a) the font size (b) the price (c) the right answer tag (d) a sticker on a laptop
2. 2.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
3. 3.True or false: “blurry, unclear photos” is bad for training a model. (a) True (b) False
4. 4.🐶 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
5. 5.Which of these is good for training a model? (a) testing on training data (b) correct labels (c) wrong labels (d) copies of one photo
6. 6.True or false: “very few examples” is good for training a model. (a) False (b) True
7. 7.True or false: “wrong labels” is bad for training a model. (a) True (b) False
8. 8.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
9. 9.Which of these is good for training a model? (a) testing on training data (b) labels added at random (c) checking labels twice (d) wrong labels
10. 10.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True
11. 11.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it will be perfect (c) it may get it wrong (d) it will turn yellow
12. 12.🧠 Machine learning is a way for computers to… (a) charge faster (b) print pages (c) learn from data (d) clean screens
13. 13.🏷️ 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
14. 14.Which of these is good for training a model? (a) wrong labels (b) very few examples (c) examples of every type (d) blurry, unclear photos
15. 15.🔍 Which is the odd one out? (a) many varied examples (b) very few examples (c) new data for testing (d) examples of every type
16. 16.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) False (b) True
17. 17.🏷️ 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
18. 18.Which of these is bad for training a model? (a) checking labels twice (b) examples of every type (c) new data for testing (d) blurry, unclear photos
19. 19.📚 Usually, more good examples make a model… (a) change colour (b) slower to switch on (c) better at its task (d) forget everything
20. 20.True or false: “only one kind of example” is bad for training a model. (a) False (b) True
21. 21.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
22. 22.🏷️ 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
23. 23.Which of these is good for training a model? (a) clear, sharp examples (b) copies of one photo (c) testing on training data (d) only one kind of example
24. 24.🔍 Which is the odd one out? (a) wrong labels (b) checking labels twice (c) copies of one photo (d) very few examples
25. 25.🏷️ 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
26. 26.Which of these is bad for training a model? (a) very few examples (b) photos in many lights (c) correct labels (d) new data for testing
27. 27.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
28. 28.True or false: “correct labels” is bad for training a model. (a) True (b) False
29. 29.🏷️ 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
30. 30.Which of these is bad for training a model? (a) correct labels (b) wrong labels (c) photos in many lights (d) checking labels twice
31. 31.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
32. 32.True or false: “many varied examples” is bad for training a model. (a) False (b) True
33. 33.Which of these is bad for training a model? (a) examples of every type (b) checking labels twice (c) testing on training data (d) many varied examples
34. 34.🏷️ 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
35. 35.Which of these is bad for training a model? (a) many varied examples (b) labels added at random (c) photos in many lights (d) new data for testing
36. 36.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) True (b) False
37. 37.🔍 Which is the odd one out? (a) wrong labels (b) blurry, unclear photos (c) very few examples (d) correct labels
38. 38.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True
39. 39.True or false: “copies of one photo” is good for training a model. (a) True (b) False
40. 40.Which of these is bad for training a model? (a) copies of one photo (b) examples of every type (c) clear, sharp examples (d) many varied examples

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