Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 366 · 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 “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
2. 2.🏷️ 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
3. 3.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) spam (b) not spam
4. 4.🏷️ 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
5. 5.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it may get it wrong (b) it will turn yellow (c) it will be perfect (d) it will shut down
6. 6.True or false: “photos in many lights” is bad for training a model. (a) True (b) False
7. 7.True or false: “checking labels twice” is good for training a model. (a) False (b) True
8. 8.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a song about dogs (c) many labelled photos (d) a list of rules only
9. 9.Which of these is good for training a model? (a) checking labels twice (b) testing on training data (c) copies of one photo (d) blurry, unclear photos
10. 10.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) spam (b) not spam
11. 11.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
12. 12.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) spam (b) not spam
13. 13.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) False (b) True
14. 14.🏷️ 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
15. 15.Which of these is good for training a model? (a) many varied examples (b) only one kind of example (c) very few examples (d) blurry, unclear photos
16. 16.🔍 Which is the odd one out? (a) very few examples (b) labels added at random (c) testing on training data (d) correct labels
17. 17.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
18. 18.Which of these is bad for training a model? (a) photos in many lights (b) copies of one photo (c) correct labels (d) many varied examples
19. 19.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
20. 20.🧠 Machine learning is a way for computers to… (a) learn from data (b) clean screens (c) charge faster (d) print pages
21. 21.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
22. 22.Which of these is good for training a model? (a) wrong labels (b) blurry, unclear photos (c) very few examples (d) new data for testing
23. 23.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
24. 24.🔍 Which is the odd one out? (a) labels added at random (b) only one kind of example (c) copies of one photo (d) examples of every type
25. 25.Which of these is good for training a model? (a) blurry, unclear photos (b) testing on training data (c) wrong labels (d) correct labels
26. 26.🔍 Which is the odd one out? (a) checking labels twice (b) only one kind of example (c) clear, sharp examples (d) correct labels
27. 27.🏷️ What is a “label” in machine learning? (a) the price (b) the right answer tag (c) a sticker on a laptop (d) the font size
28. 28.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
29. 29.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
30. 30.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
31. 31.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) True (b) False
32. 32.Which of these is good for training a model? (a) labels added at random (b) only one kind of example (c) copies of one photo (d) examples of every type
33. 33.🔍 Which is the odd one out? (a) examples of every type (b) labels added at random (c) correct labels (d) many varied examples
34. 34.True or false: “photos in many lights” is good for training a model. (a) False (b) True
35. 35.True or false: “correct labels” is good for training a model. (a) True (b) False
36. 36.📚 Usually, more good examples make a model… (a) slower to switch on (b) change colour (c) better at its task (d) forget everything
37. 37.True or false: “only one kind of example” is bad for training a model. (a) False (b) True
38. 38.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
39. 39.🔍 Which is the odd one out? (a) very few examples (b) examples of every type (c) checking labels twice (d) clear, sharp examples
40. 40.True or false: “clear, sharp examples” is bad for training a model. (a) False (b) True

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