Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 592 · 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.True or false: “photos in many lights” is good for training a model. (a) True (b) False
2. 2.🏷️ 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
3. 3.🔍 Which is the odd one out? (a) new data for testing (b) correct labels (c) very few examples (d) examples of every type
4. 4.🧠 Machine learning is a way for computers to… (a) print pages (b) learn from data (c) clean screens (d) charge faster
5. 5.Which of these is good for training a model? (a) blurry, unclear photos (b) very few examples (c) copies of one photo (d) correct labels
6. 6.Which of these is good for training a model? (a) blurry, unclear photos (b) many varied examples (c) labels added at random (d) very few examples
7. 7.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) True (b) False
8. 8.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) spam (b) not spam
9. 9.🏷️ 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
10. 10.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
11. 11.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
12. 12.Which of these is good for training a model? (a) very few examples (b) testing on training data (c) blurry, unclear photos (d) new data for testing
13. 13.🔍 Which is the odd one out? (a) many varied examples (b) labels added at random (c) very few examples (d) only one kind of example
14. 14.🔍 Which is the odd one out? (a) photos in many lights (b) correct labels (c) checking labels twice (d) wrong labels
15. 15.🔍 Which is the odd one out? (a) only one kind of example (b) correct labels (c) blurry, unclear photos (d) testing on training data
16. 16.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it may get it wrong (c) it will turn yellow (d) it will be perfect
17. 17.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
18. 18.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) False (b) True
19. 19.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) True (b) False
20. 20.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
21. 21.True or false: “new data for testing” is good for training a model. (a) False (b) True
22. 22.🔍 Which is the odd one out? (a) copies of one photo (b) clear, sharp examples (c) new data for testing (d) many varied examples
23. 23.Which of these is good for training a model? (a) blurry, unclear photos (b) photos in many lights (c) testing on training data (d) very few examples
24. 24.Which of these is bad for training a model? (a) new data for testing (b) checking labels twice (c) photos in many lights (d) labels added at random
25. 25.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
26. 26.True or false: “copies of one photo” is good for training a model. (a) True (b) False
27. 27.🏷️ What is a “label” in machine learning? (a) the right answer tag (b) the price (c) a sticker on a laptop (d) the font size
28. 28.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
29. 29.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
30. 30.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
31. 31.🏷️ 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
32. 32.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
33. 33.📚 Usually, more good examples make a model… (a) slower to switch on (b) change colour (c) better at its task (d) forget everything
34. 34.🔍 Which is the odd one out? (a) very few examples (b) blurry, unclear photos (c) examples of every type (d) testing on training data
35. 35.Which of these is bad for training a model? (a) many varied examples (b) examples of every type (c) photos in many lights (d) very few examples
36. 36.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
37. 37.True or false: “checking labels twice” is good for training a model. (a) False (b) True
38. 38.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
39. 39.True or false: “many varied examples” is good for training a model. (a) True (b) False
40. 40.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True

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