Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 344 · 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) very few examples (b) checking labels twice (c) examples of every type (d) new data for testing
2. 2.🏷️ 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
3. 3.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) True (b) False
4. 4.Which of these is bad for training a model? (a) many varied examples (b) new data for testing (c) examples of every type (d) only one kind of example
5. 5.🔍 Which is the odd one out? (a) wrong labels (b) only one kind of example (c) examples of every type (d) blurry, unclear photos
6. 6.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) a song about dogs (c) a list of rules only (d) one single photo
7. 7.Which of these is bad for training a model? (a) blurry, unclear photos (b) many varied examples (c) examples of every type (d) correct labels
8. 8.True or false: “correct labels” is good for training a model. (a) False (b) True
9. 9.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it may get it wrong (c) it will be perfect (d) it will shut down
10. 10.🏷️ 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
11. 11.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) False (b) True
12. 12.True or false: “examples of every type” is bad for training a model. (a) True (b) False
13. 13.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the price (c) the right answer tag (d) the font size
14. 14.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
15. 15.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) True (b) False
16. 16.Which of these is good for training a model? (a) examples of every type (b) very few examples (c) only one kind of example (d) copies of one photo
17. 17.Which of these is good for training a model? (a) labels added at random (b) many varied examples (c) testing on training data (d) only one kind of example
18. 18.Which of these is good for training a model? (a) labels added at random (b) blurry, unclear photos (c) wrong labels (d) clear, sharp examples
19. 19.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
20. 20.Which of these is bad for training a model? (a) clear, sharp examples (b) examples of every type (c) copies of one photo (d) new data for testing
21. 21.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) spam (b) not spam
22. 22.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
23. 23.True or false: “wrong labels” is bad for training a model. (a) True (b) False
24. 24.True or false: “examples of every type” is good for training a model. (a) False (b) True
25. 25.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) True (b) False
26. 26.Which of these is bad for training a model? (a) many varied examples (b) checking labels twice (c) new data for testing (d) labels added at random
27. 27.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) False (b) True
28. 28.Which of these is bad for training a model? (a) photos in many lights (b) checking labels twice (c) very few examples (d) correct labels
29. 29.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) not spam (b) spam
30. 30.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
31. 31.🔍 Which is the odd one out? (a) very few examples (b) testing on training data (c) wrong labels (d) many varied examples
32. 32.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
33. 33.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
34. 34.🏷️ 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
35. 35.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
36. 36.🏷️ 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
37. 37.📚 Usually, more good examples make a model… (a) forget everything (b) slower to switch on (c) better at its task (d) change colour
38. 38.Which of these is good for training a model? (a) testing on training data (b) correct labels (c) very few examples (d) wrong labels
39. 39.🧠 Machine learning is a way for computers to… (a) learn from data (b) charge faster (c) print pages (d) clean screens
40. 40.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) True (b) False

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