Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 89 · 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 good for training a model. (a) False (b) True
2. 2.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) not spam (b) spam
3. 3.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
4. 4.🏷️ 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
5. 5.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
6. 6.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
7. 7.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
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.Which of these is bad for training a model? (a) correct labels (b) blurry, unclear photos (c) many varied examples (d) examples of every type
10. 10.🔍 Which is the odd one out? (a) testing on training data (b) labels added at random (c) only one kind of example (d) many varied examples
11. 11.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
12. 12.Which of these is bad for training a model? (a) clear, sharp examples (b) very few examples (c) photos in many lights (d) checking labels twice
13. 13.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) True (b) False
14. 14.🏷️ 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
15. 15.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) False (b) True
16. 16.📚 Usually, more good examples make a model… (a) better at its task (b) change colour (c) slower to switch on (d) forget everything
17. 17.🔍 Which is the odd one out? (a) photos in many lights (b) checking labels twice (c) many varied examples (d) wrong labels
18. 18.Which of these is bad for training a model? (a) many varied examples (b) examples of every type (c) labels added at random (d) correct labels
19. 19.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
20. 20.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
21. 21.Which of these is good for training a model? (a) photos in many lights (b) wrong labels (c) blurry, unclear photos (d) labels added at random
22. 22.True or false: “copies of one photo” is good for training a model. (a) False (b) True
23. 23.🔍 Which is the odd one out? (a) very few examples (b) copies of one photo (c) clear, sharp examples (d) only one kind of example
24. 24.🔍 Which is the odd one out? (a) correct labels (b) very few examples (c) labels added at random (d) copies of one photo
25. 25.True or false: “very few examples” is bad for training a model. (a) False (b) True
26. 26.🏷️ What is a “label” in machine learning? (a) the right answer tag (b) the price (c) a sticker on a laptop (d) the font size
27. 27.True or false: “clear, sharp examples” is bad for training a model. (a) False (b) True
28. 28.🔍 Which is the odd one out? (a) testing on training data (b) photos in many lights (c) new data for testing (d) correct labels
29. 29.🏷️ 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
30. 30.True or false: “blurry, unclear photos” is good for training a model. (a) False (b) True
31. 31.Which of these is bad for training a model? (a) new data for testing (b) testing on training data (c) clear, sharp examples (d) examples of every type
32. 32.True or false: “checking labels twice” is bad for training a model. (a) True (b) False
33. 33.True or false: “only one kind of example” is good for training a model. (a) False (b) True
34. 34.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) True (b) False
35. 35.🔍 Which is the odd one out? (a) checking labels twice (b) many varied examples (c) clear, sharp examples (d) only one kind of example
36. 36.🧠 Machine learning is a way for computers to… (a) learn from data (b) clean screens (c) charge faster (d) print pages
37. 37.True or false: “many varied examples” is good for training a model. (a) True (b) False
38. 38.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) one single photo (c) many labelled photos (d) a list of rules only
39. 39.Which of these is bad for training a model? (a) examples of every type (b) only one kind of example (c) clear, sharp examples (d) many varied examples
40. 40.Which of these is bad for training a model? (a) checking labels twice (b) new data for testing (c) photos in many lights (d) copies of one photo

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