Machine Learning for Kids Worksheet

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

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