Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 302 · 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.🧠 Machine learning is a way for computers to… (a) charge faster (b) clean screens (c) print pages (d) learn from data
2. 2.🏷️ 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
3. 3.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) True (b) False
4. 4.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) True (b) False
5. 5.Which of these is bad for training a model? (a) new data for testing (b) clear, sharp examples (c) examples of every type (d) blurry, unclear photos
6. 6.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
7. 7.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
8. 8.🏷️ 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
9. 9.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
10. 10.Which of these is bad for training a model? (a) checking labels twice (b) correct labels (c) examples of every type (d) copies of one photo
11. 11.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
12. 12.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) False (b) True
13. 13.Which of these is good for training a model? (a) copies of one photo (b) many varied examples (c) only one kind of example (d) labels added at random
14. 14.True or false: “new data for testing” is good for training a model. (a) True (b) False
15. 15.Which of these is bad for training a model? (a) labels added at random (b) checking labels twice (c) many varied examples (d) clear, sharp examples
16. 16.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) False (b) True
17. 17.🏷️ 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
18. 18.🔍 Which is the odd one out? (a) wrong labels (b) very few examples (c) labels added at random (d) correct labels
19. 19.🐶 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) one single photo (d) many labelled photos
20. 20.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) True (b) False
21. 21.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) not spam (b) spam
22. 22.📚 Usually, more good examples make a model… (a) forget everything (b) slower to switch on (c) change colour (d) better at its task
23. 23.🏷️ 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
24. 24.Which of these is good for training a model? (a) examples of every type (b) copies of one photo (c) labels added at random (d) only one kind of example
25. 25.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) spam (b) not spam
26. 26.True or false: “examples of every type” is good for training a model. (a) True (b) False
27. 27.🔍 Which is the odd one out? (a) examples of every type (b) wrong labels (c) many varied examples (d) photos in many lights
28. 28.Which of these is bad for training a model? (a) checking labels twice (b) photos in many lights (c) clear, sharp examples (d) wrong labels
29. 29.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
30. 30.True or false: “clear, sharp examples” is good for training a model. (a) False (b) True
31. 31.🏷️ 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
32. 32.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
33. 33.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) True (b) False
34. 34.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
35. 35.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) True (b) False
36. 36.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) False (b) True
37. 37.🔍 Which is the odd one out? (a) very few examples (b) examples of every type (c) only one kind of example (d) wrong labels
38. 38.Which of these is good for training a model? (a) labels added at random (b) very few examples (c) blurry, unclear photos (d) checking labels twice
39. 39.Which of these is bad for training a model? (a) new data for testing (b) checking labels twice (c) only one kind of example (d) many varied examples
40. 40.Which of these is good for training a model? (a) clear, sharp examples (b) testing on training data (c) wrong labels (d) blurry, unclear photos

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