Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 328 · 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.🏷️ What is a “label” in machine learning? (a) the font size (b) the right answer tag (c) a sticker on a laptop (d) the price
2. 2.True or false: “labels added at random” is bad for training a model. (a) True (b) False
3. 3.🔍 Which is the odd one out? (a) correct labels (b) copies of one photo (c) many varied examples (d) checking labels twice
4. 4.True or false: “examples of every type” is good for training a model. (a) False (b) True
5. 5.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) True (b) False
6. 6.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “The class picnic is on Friday at 8 am” (a) spam (b) not spam
7. 7.🔍 Which is the odd one out? (a) only one kind of example (b) blurry, unclear photos (c) very few examples (d) many varied examples
8. 8.True or false: “correct labels” is bad for training a model. (a) True (b) False
9. 9.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
10. 10.🧠 Machine learning is a way for computers to… (a) clean screens (b) charge faster (c) learn from data (d) print pages
11. 11.True or false: “many varied examples” is good for training a model. (a) False (b) True
12. 12.True or false: “many varied examples” is bad for training a model. (a) False (b) True
13. 13.True or false: “photos in many lights” is bad for training a model. (a) True (b) False
14. 14.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) False (b) True
15. 15.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) not spam (b) spam
16. 16.Which of these is good for training a model? (a) correct labels (b) labels added at random (c) very few examples (d) blurry, unclear photos
17. 17.🔍 Which is the odd one out? (a) new data for testing (b) checking labels twice (c) many varied examples (d) blurry, unclear photos
18. 18.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
19. 19.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) True (b) False
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) a song about dogs (d) one single photo
21. 21.Which of these is bad for training a model? (a) very few examples (b) correct labels (c) examples of every type (d) clear, sharp examples
22. 22.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
23. 23.🔍 Which is the odd one out? (a) only one kind of example (b) checking labels twice (c) copies of one photo (d) very few examples
24. 24.🔍 Which is the odd one out? (a) wrong labels (b) many varied examples (c) examples of every type (d) checking labels twice
25. 25.🏷️ 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
26. 26.True or false: “new data for testing” is good for training a model. (a) True (b) False
27. 27.Which of these is bad for training a model? (a) checking labels twice (b) testing on training data (c) correct labels (d) photos in many lights
28. 28.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True
29. 29.Which of these is good for training a model? (a) labels added at random (b) very few examples (c) testing on training data (d) examples of every type
30. 30.True or false: “examples of every type” is bad for training a model. (a) False (b) True
31. 31.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
32. 32.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) spam (b) not spam
33. 33.Which of these is bad for training a model? (a) photos in many lights (b) clear, sharp examples (c) correct labels (d) labels added at random
34. 34.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
35. 35.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
36. 36.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
37. 37.Which of these is bad for training a model? (a) new data for testing (b) copies of one photo (c) correct labels (d) checking labels twice
38. 38.🏷️ 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
39. 39.Which of these is bad for training a model? (a) only one kind of example (b) new data for testing (c) correct labels (d) examples of every type
40. 40.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) spam (b) not spam

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