Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 474 · 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 good for training a model? (a) checking labels twice (b) copies of one photo (c) blurry, unclear photos (d) very few examples
2. 2.Which of these is bad for training a model? (a) many varied examples (b) correct labels (c) labels added at random (d) checking labels twice
3. 3.Which of these is bad for training a model? (a) checking labels twice (b) testing on training data (c) many varied examples (d) correct labels
4. 4.Which of these is good for training a model? (a) new data for testing (b) testing on training data (c) wrong labels (d) only one kind of example
5. 5.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) spam (b) not spam
6. 6.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
7. 7.True or false: “testing on training data” is good for training a model. (a) True (b) False
8. 8.True or false: “examples of every type” is bad for training a model. (a) True (b) False
9. 9.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) spam (b) not spam
10. 10.🔍 Which is the odd one out? (a) only one kind of example (b) new data for testing (c) labels added at random (d) testing on training data
11. 11.Which of these is good for training a model? (a) blurry, unclear photos (b) many varied examples (c) very few examples (d) wrong labels
12. 12.🔍 Which is the odd one out? (a) very few examples (b) examples of every type (c) testing on training data (d) copies of one photo
13. 13.Which of these is good for training a model? (a) copies of one photo (b) clear, sharp examples (c) wrong labels (d) only one kind of example
14. 14.Which of these is bad for training a model? (a) new data for testing (b) checking labels twice (c) correct labels (d) wrong labels
15. 15.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
16. 16.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) True (b) False
17. 17.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) not spam (b) spam
18. 18.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
19. 19.🔍 Which is the odd one out? (a) wrong labels (b) labels added at random (c) many varied examples (d) very few examples
20. 20.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
21. 21.🔍 Which is the odd one out? (a) labels added at random (b) many varied examples (c) clear, sharp examples (d) examples of every type
22. 22.📚 Usually, more good examples make a model… (a) slower to switch on (b) change colour (c) better at its task (d) forget everything
23. 23.🧠 Machine learning is a way for computers to… (a) charge faster (b) learn from data (c) print pages (d) clean screens
24. 24.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) True (b) False
25. 25.True or false: “examples of every type” is good for training a model. (a) False (b) True
26. 26.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
27. 27.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
28. 28.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) False (b) True
29. 29.Which of these is good for training a model? (a) copies of one photo (b) blurry, unclear photos (c) correct labels (d) wrong labels
30. 30.🔍 Which is the odd one out? (a) only one kind of example (b) checking labels twice (c) very few examples (d) wrong labels
31. 31.🐶 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
32. 32.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
33. 33.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
34. 34.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) True (b) False
35. 35.True or false: “copies of one photo” is good for training a model. (a) True (b) False
36. 36.True or false: “correct labels” is good for training a model. (a) True (b) False
37. 37.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it may get it wrong (c) it will shut down (d) it will turn yellow
38. 38.Which of these is bad for training a model? (a) checking labels twice (b) new data for testing (c) correct labels (d) very few examples
39. 39.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
40. 40.Which of these is bad for training a model? (a) many varied examples (b) only one kind of example (c) correct labels (d) new data for testing

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