Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 531 · 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 “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
2. 2.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
3. 3.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
4. 4.🔍 Which is the odd one out? (a) wrong labels (b) very few examples (c) blurry, unclear photos (d) new data for testing
5. 5.True or false: “wrong labels” is good for training a model. (a) True (b) False
6. 6.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
7. 7.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) True (b) False
8. 8.Which of these is good for training a model? (a) labels added at random (b) testing on training data (c) many varied examples (d) blurry, unclear photos
9. 9.🏷️ What is a “label” in machine learning? (a) the price (b) the font size (c) the right answer tag (d) a sticker on a laptop
10. 10.Which of these is bad for training a model? (a) many varied examples (b) wrong labels (c) new data for testing (d) checking labels twice
11. 11.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
12. 12.True or false: “only one kind of example” is good for training a model. (a) True (b) False
13. 13.🔍 Which is the odd one out? (a) very few examples (b) many varied examples (c) photos in many lights (d) checking labels twice
14. 14.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
15. 15.🏷️ 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
16. 16.🥭 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
17. 17.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
18. 18.True or false: “many varied examples” is good for training a model. (a) True (b) False
19. 19.🔍 Which is the odd one out? (a) wrong labels (b) copies of one photo (c) labels added at random (d) many varied examples
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) one single photo (d) a song about dogs
21. 21.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
22. 22.🧠 Machine learning is a way for computers to… (a) clean screens (b) charge faster (c) learn from data (d) print pages
23. 23.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
24. 24.🔍 Which is the odd one out? (a) many varied examples (b) new data for testing (c) only one kind of example (d) correct labels
25. 25.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) True (b) False
26. 26.True or false: “testing on training data” is bad for training a model. (a) False (b) True
27. 27.Which of these is bad for training a model? (a) many varied examples (b) copies of one photo (c) correct labels (d) examples of every type
28. 28.Which of these is bad for training a model? (a) correct labels (b) photos in many lights (c) new data for testing (d) blurry, unclear photos
29. 29.🏷️ 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
30. 30.🔍 Which is the odd one out? (a) only one kind of example (b) wrong labels (c) checking labels twice (d) very few examples
31. 31.True or false: “photos in many lights” is good for training a model. (a) False (b) True
32. 32.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
33. 33.🏷️ 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
34. 34.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
35. 35.📚 Usually, more good examples make a model… (a) better at its task (b) change colour (c) slower to switch on (d) forget everything
36. 36.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
37. 37.True or false: “clear, sharp examples” is good for training a model. (a) True (b) False
38. 38.Which of these is good for training a model? (a) testing on training data (b) very few examples (c) checking labels twice (d) labels added at random
39. 39.True or false: “new data for testing” is good for training a model. (a) True (b) False
40. 40.🔍 Which is the odd one out? (a) examples of every type (b) clear, sharp examples (c) checking labels twice (d) labels added at random

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