Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 382 · 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.🧠 Machine learning is a way for computers to… (a) charge faster (b) learn from data (c) print pages (d) clean screens
2. 2.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
3. 3.🏷️ 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
4. 4.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a list of rules only (c) many labelled photos (d) a song about dogs
5. 5.Which of these is good for training a model? (a) very few examples (b) photos in many lights (c) copies of one photo (d) wrong labels
6. 6.🏷️ 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
7. 7.Which of these is good for training a model? (a) very few examples (b) blurry, unclear photos (c) only one kind of example (d) new data for testing
8. 8.Which of these is good for training a model? (a) checking labels twice (b) very few examples (c) only one kind of example (d) blurry, unclear photos
9. 9.Which of these is good for training a model? (a) wrong labels (b) blurry, unclear photos (c) clear, sharp examples (d) only one kind of example
10. 10.🔍 Which is the odd one out? (a) clear, sharp examples (b) many varied examples (c) photos in many lights (d) blurry, unclear photos
11. 11.Which of these is good for training a model? (a) only one kind of example (b) wrong labels (c) copies of one photo (d) many varied examples
12. 12.🔍 Which is the odd one out? (a) very few examples (b) correct labels (c) many varied examples (d) examples of every type
13. 13.🔍 Which is the odd one out? (a) very few examples (b) examples of every type (c) only one kind of example (d) copies of one photo
14. 14.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
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: “new data for testing” is good for training a model. (a) False (b) True
17. 17.True or false: “only one kind of example” is good for training a model. (a) True (b) False
18. 18.True or false: “correct labels” is bad for training a model. (a) False (b) True
19. 19.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
20. 20.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
21. 21.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
22. 22.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
23. 23.🔍 Which is the odd one out? (a) copies of one photo (b) wrong labels (c) blurry, unclear photos (d) many varied examples
24. 24.True or false: “many varied examples” is bad for training a model. (a) True (b) False
25. 25.True or false: “examples of every type” is bad for training a model. (a) True (b) False
26. 26.True or false: “photos in many lights” is bad for training a model. (a) True (b) False
27. 27.🔍 Which is the odd one out? (a) photos in many lights (b) checking labels twice (c) examples of every type (d) only one kind of example
28. 28.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) False (b) True
29. 29.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) True (b) False
30. 30.Which of these is bad for training a model? (a) checking labels twice (b) very few examples (c) correct labels (d) clear, sharp examples
31. 31.True or false: “blurry, unclear photos” is bad for training a model. (a) False (b) True
32. 32.Which of these is bad for training a model? (a) photos in many lights (b) copies of one photo (c) new data for testing (d) checking labels twice
33. 33.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) False (b) True
34. 34.📚 Usually, more good examples make a model… (a) change colour (b) better at its task (c) forget everything (d) slower to switch on
35. 35.True or false: “copies of one photo” is bad for training a model. (a) False (b) True
36. 36.🔍 Which is the odd one out? (a) very few examples (b) only one kind of example (c) wrong labels (d) correct labels
37. 37.🏷️ 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
38. 38.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
39. 39.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) True (b) False
40. 40.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) not spam (b) spam

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