Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 530 · 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.Which of these is bad for training a model? (a) checking labels twice (b) very few examples (c) clear, sharp examples (d) many varied examples
2. 2.True or false: “new data for testing” is good for training a model. (a) False (b) True
3. 3.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) False (b) True
4. 4.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True
5. 5.🔍 Which is the odd one out? (a) examples of every type (b) new data for testing (c) blurry, unclear photos (d) clear, sharp examples
6. 6.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) True (b) False
7. 7.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
8. 8.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
9. 9.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
10. 10.True or false: “photos in many lights” is good for training a model. (a) True (b) False
11. 11.🏷️ 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
12. 12.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) True (b) False
13. 13.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
14. 14.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the price (c) the right answer tag (d) the font size
15. 15.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
16. 16.🔍 Which is the odd one out? (a) copies of one photo (b) many varied examples (c) only one kind of example (d) blurry, unclear photos
17. 17.📚 Usually, more good examples make a model… (a) better at its task (b) slower to switch on (c) change colour (d) forget everything
18. 18.🔍 Which is the odd one out? (a) very few examples (b) clear, sharp examples (c) checking labels twice (d) correct labels
19. 19.🔍 Which is the odd one out? (a) photos in many lights (b) correct labels (c) wrong labels (d) many varied examples
20. 20.Which of these is good for training a model? (a) testing on training data (b) wrong labels (c) only one kind of example (d) new data for testing
21. 21.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) not spam (b) spam
22. 22.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
23. 23.Which of these is good for training a model? (a) copies of one photo (b) labels added at random (c) clear, sharp examples (d) very few examples
24. 24.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
25. 25.True or false: “correct labels” is bad for training a model. (a) False (b) True
26. 26.Which of these is good for training a model? (a) checking labels twice (b) only one kind of example (c) blurry, unclear photos (d) labels added at random
27. 27.Which of these is good for training a model? (a) examples of every type (b) wrong labels (c) testing on training data (d) labels added at random
28. 28.True or false: “examples of every type” is bad for training a model. (a) False (b) True
29. 29.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) not spam (b) spam
30. 30.True or false: “only one kind of example” is bad for training a model. (a) True (b) False
31. 31.Which of these is good for training a model? (a) correct labels (b) labels added at random (c) wrong labels (d) testing on training data
32. 32.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
33. 33.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
34. 34.Which of these is bad for training a model? (a) checking labels twice (b) testing on training data (c) clear, sharp examples (d) many varied examples
35. 35.🔍 Which is the odd one out? (a) labels added at random (b) copies of one photo (c) blurry, unclear photos (d) photos in many lights
36. 36.Which of these is good for training a model? (a) blurry, unclear photos (b) wrong labels (c) many varied examples (d) labels added at random
37. 37.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) False (b) True
38. 38.🔍 Which is the odd one out? (a) new data for testing (b) copies of one photo (c) many varied examples (d) checking labels twice
39. 39.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) True (b) False
40. 40.🔍 Which is the odd one out? (a) copies of one photo (b) blurry, unclear photos (c) new data for testing (d) only one kind of example

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