Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 541 · 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.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
2. 2.True or false: “correct labels” is good for training a model. (a) False (b) True
3. 3.True or false: “checking labels twice” is good for training a model. (a) False (b) True
4. 4.🏷️ What is a “label” in machine learning? (a) the price (b) a sticker on a laptop (c) the font size (d) the right answer tag
5. 5.Which of these is good for training a model? (a) labels added at random (b) testing on training data (c) clear, sharp examples (d) copies of one photo
6. 6.Which of these is bad for training a model? (a) correct labels (b) new data for testing (c) copies of one photo (d) examples of every type
7. 7.True or false: “copies of one photo” is good for training a model. (a) True (b) False
8. 8.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) False (b) True
9. 9.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) spam (b) not spam
10. 10.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) True (b) False
11. 11.True or false: “blurry, unclear photos” is good for training a model. (a) True (b) False
12. 12.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
13. 13.🏷️ 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
14. 14.🔍 Which is the odd one out? (a) photos in many lights (b) blurry, unclear photos (c) clear, sharp examples (d) checking labels twice
15. 15.Which of these is bad for training a model? (a) new data for testing (b) testing on training data (c) examples of every type (d) checking labels twice
16. 16.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
17. 17.Which of these is good for training a model? (a) examples of every type (b) very few examples (c) blurry, unclear photos (d) only one kind of example
18. 18.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
19. 19.🔍 Which is the odd one out? (a) testing on training data (b) many varied examples (c) correct labels (d) photos in many lights
20. 20.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
21. 21.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
22. 22.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
23. 23.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) False (b) True
24. 24.True or false: “clear, sharp examples” is good for training a model. (a) False (b) True
25. 25.True or false: “labels added at random” is bad for training a model. (a) False (b) True
26. 26.True or false: “copies of one photo” is bad for training a model. (a) True (b) False
27. 27.🔍 Which is the odd one out? (a) labels added at random (b) photos in many lights (c) wrong labels (d) very few examples
28. 28.🔍 Which is the odd one out? (a) examples of every type (b) many varied examples (c) only one kind of example (d) photos in many lights
29. 29.🔍 Which is the odd one out? (a) correct labels (b) only one kind of example (c) very few examples (d) wrong labels
30. 30.True or false: “testing on training data” is good for training a model. (a) False (b) True
31. 31.Which of these is good for training a model? (a) wrong labels (b) very few examples (c) only one kind of example (d) checking labels twice
32. 32.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) True (b) False
33. 33.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
34. 34.📚 Usually, more good examples make a model… (a) forget everything (b) better at its task (c) change colour (d) slower to switch on
35. 35.True or false: “only one kind of example” is good for training a model. (a) True (b) False
36. 36.🔍 Which is the odd one out? (a) clear, sharp examples (b) copies of one photo (c) very few examples (d) wrong labels
37. 37.Which of these is good for training a model? (a) labels added at random (b) testing on training data (c) copies of one photo (d) many varied examples
38. 38.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
39. 39.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) not spam (b) spam
40. 40.Which of these is bad for training a model? (a) correct labels (b) wrong labels (c) many varied examples (d) clear, sharp examples

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