Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 298 · 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) examples of every type (b) copies of one photo (c) clear, sharp examples (d) photos in many lights
2. 2.🏷️ What is a “label” in machine learning? (a) the right answer tag (b) a sticker on a laptop (c) the price (d) the font size
3. 3.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
4. 4.Which of these is bad for training a model? (a) correct labels (b) new data for testing (c) photos in many lights (d) labels added at random
5. 5.🔍 Which is the odd one out? (a) very few examples (b) blurry, unclear photos (c) only one kind of example (d) many varied examples
6. 6.Which of these is bad for training a model? (a) many varied examples (b) new data for testing (c) correct labels (d) very few examples
7. 7.🔍 Which is the odd one out? (a) very few examples (b) testing on training data (c) correct labels (d) copies of one photo
8. 8.True or false: “examples of every type” is good for training a model. (a) False (b) True
9. 9.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
10. 10.🐶 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
11. 11.True or false: “checking labels twice” is bad for training a model. (a) True (b) False
12. 12.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
13. 13.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
14. 14.Which of these is bad for training a model? (a) many varied examples (b) photos in many lights (c) only one kind of example (d) checking labels twice
15. 15.🏷️ 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
16. 16.True or false: “blurry, unclear photos” is bad for training a model. (a) False (b) True
17. 17.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
18. 18.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
19. 19.True or false: “testing on training data” is bad for training a model. (a) True (b) False
20. 20.True or false: “only one kind of example” is bad for training a model. (a) True (b) False
21. 21.Which of these is good for training a model? (a) examples of every type (b) only one kind of example (c) wrong labels (d) testing on training data
22. 22.True or false: “correct labels” is good for training a model. (a) True (b) False
23. 23.🔍 Which is the odd one out? (a) checking labels twice (b) labels added at random (c) examples of every type (d) many varied examples
24. 24.Which of these is good for training a model? (a) very few examples (b) correct labels (c) copies of one photo (d) blurry, unclear photos
25. 25.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) True (b) False
26. 26.🔍 Which is the odd one out? (a) clear, sharp examples (b) examples of every type (c) very few examples (d) new data for testing
27. 27.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
28. 28.🔍 Which is the odd one out? (a) correct labels (b) many varied examples (c) examples of every type (d) copies of one photo
29. 29.Which of these is bad for training a model? (a) checking labels twice (b) many varied examples (c) new data for testing (d) testing on training data
30. 30.True or false: “photos in many lights” is good for training a model. (a) True (b) False
31. 31.True or false: “blurry, unclear photos” is good for training a model. (a) True (b) False
32. 32.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True
33. 33.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
34. 34.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
35. 35.Which of these is good for training a model? (a) testing on training data (b) copies of one photo (c) clear, sharp examples (d) very few examples
36. 36.🔍 Which is the odd one out? (a) photos in many lights (b) examples of every type (c) new data for testing (d) blurry, unclear photos
37. 37.True or false: “clear, sharp examples” is bad for training a model. (a) False (b) True
38. 38.True or false: “new data for testing” is good for training a model. (a) False (b) True
39. 39.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) not spam (b) spam
40. 40.Which of these is bad for training a model? (a) checking labels twice (b) many varied examples (c) wrong labels (d) correct labels

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