Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 124 · 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: “photos in many lights” is bad for training a model. (a) False (b) True
2. 2.Which of these is bad for training a model? (a) very few examples (b) many varied examples (c) examples of every type (d) clear, sharp examples
3. 3.Which of these is good for training a model? (a) clear, sharp examples (b) only one kind of example (c) wrong labels (d) very few examples
4. 4.🧠 Machine learning is a way for computers to… (a) learn from data (b) clean screens (c) print pages (d) charge faster
5. 5.🐶 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
6. 6.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) False (b) True
7. 7.🔍 Which is the odd one out? (a) copies of one photo (b) blurry, unclear photos (c) checking labels twice (d) wrong labels
8. 8.🔍 Which is the odd one out? (a) correct labels (b) only one kind of example (c) checking labels twice (d) examples of every type
9. 9.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
10. 10.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) True (b) False
11. 11.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) True (b) False
12. 12.📚 Usually, more good examples make a model… (a) slower to switch on (b) better at its task (c) change colour (d) forget everything
13. 13.🔍 Which is the odd one out? (a) wrong labels (b) very few examples (c) many varied examples (d) copies of one photo
14. 14.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) not spam (b) spam
15. 15.🔍 Which is the odd one out? (a) checking labels twice (b) many varied examples (c) very few examples (d) photos in many lights
16. 16.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
17. 17.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
18. 18.🔍 Which is the odd one out? (a) many varied examples (b) wrong labels (c) new data for testing (d) clear, sharp examples
19. 19.Which of these is bad for training a model? (a) clear, sharp examples (b) photos in many lights (c) testing on training data (d) many varied examples
20. 20.True or false: “only one kind of example” is bad for training a model. (a) True (b) False
21. 21.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
22. 22.🏷️ 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
23. 23.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) False (b) True
24. 24.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) True (b) False
25. 25.Which of these is good for training a model? (a) copies of one photo (b) wrong labels (c) only one kind of example (d) new data for testing
26. 26.🔍 Which is the odd one out? (a) correct labels (b) copies of one photo (c) clear, sharp examples (d) new data for testing
27. 27.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
28. 28.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) False (b) True
29. 29.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
30. 30.True or false: “checking labels twice” is bad for training a model. (a) True (b) False
31. 31.True or false: “very few examples” is bad for training a model. (a) False (b) True
32. 32.🔍 Which is the odd one out? (a) testing on training data (b) new data for testing (c) checking labels twice (d) photos in many lights
33. 33.True or false: “examples of every type” is good for training a model. (a) True (b) False
34. 34.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True
35. 35.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
36. 36.🔍 Which is the odd one out? (a) correct labels (b) labels added at random (c) many varied examples (d) photos in many lights
37. 37.Which of these is good for training a model? (a) many varied examples (b) testing on training data (c) labels added at random (d) copies of one photo
38. 38.True or false: “new data for testing” is bad for training a model. (a) False (b) True
39. 39.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
40. 40.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False

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