Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 253 · 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.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
2. 2.🔍 Which is the odd one out? (a) wrong labels (b) testing on training data (c) only one kind of example (d) photos in many lights
3. 3.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
4. 4.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
5. 5.🔍 Which is the odd one out? (a) many varied examples (b) testing on training data (c) labels added at random (d) copies of one photo
6. 6.🔍 Which is the odd one out? (a) clear, sharp examples (b) checking labels twice (c) correct labels (d) wrong labels
7. 7.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
8. 8.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) False (b) True
9. 9.True or false: the message “Your account is locked, pay ₹99 now” 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 be perfect (b) it will shut down (c) it will turn yellow (d) it may get it wrong
11. 11.🔍 Which is the odd one out? (a) copies of one photo (b) only one kind of example (c) blurry, unclear photos (d) new data for testing
12. 12.Which of these is good for training a model? (a) blurry, unclear photos (b) correct labels (c) very few examples (d) wrong labels
13. 13.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) spam (b) not spam
14. 14.Which of these is bad for training a model? (a) wrong labels (b) correct labels (c) checking labels twice (d) many varied examples
15. 15.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True
16. 16.True or false: “blurry, unclear photos” is bad for training a model. (a) False (b) True
17. 17.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) True (b) False
18. 18.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) True (b) False
19. 19.Which of these is bad for training a model? (a) blurry, unclear photos (b) correct labels (c) clear, sharp examples (d) new data for testing
20. 20.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
21. 21.📚 Usually, more good examples make a model… (a) change colour (b) slower to switch on (c) better at its task (d) forget everything
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) photos in many lights (b) labels added at random (c) only one kind of example (d) copies of one photo
24. 24.🏷️ 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
25. 25.True or false: the message “Send your password to claim a prize” 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.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
28. 28.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
29. 29.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
30. 30.True or false: “correct labels” is good for training a model. (a) False (b) True
31. 31.Which of these is good for training a model? (a) wrong labels (b) copies of one photo (c) testing on training data (d) clear, sharp examples
32. 32.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) False (b) True
33. 33.🐶 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
34. 34.🔍 Which is the odd one out? (a) checking labels twice (b) very few examples (c) photos in many lights (d) examples of every type
35. 35.🔍 Which is the odd one out? (a) many varied examples (b) correct labels (c) checking labels twice (d) labels added at random
36. 36.🧠 Machine learning is a way for computers to… (a) learn from data (b) print pages (c) charge faster (d) clean screens
37. 37.Which of these is good for training a model? (a) only one kind of example (b) many varied examples (c) copies of one photo (d) blurry, unclear photos
38. 38.🔍 Which is the odd one out? (a) checking labels twice (b) copies of one photo (c) only one kind of example (d) blurry, unclear photos
39. 39.Which of these is good for training a model? (a) labels added at random (b) only one kind of example (c) new data for testing (d) blurry, unclear photos
40. 40.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True

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