Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 422 · 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: “clear, sharp examples” is good for training a model. (a) False (b) True
2. 2.🔍 Which is the odd one out? (a) clear, sharp examples (b) only one kind of example (c) checking labels twice (d) new data for testing
3. 3.Which of these is good for training a model? (a) wrong labels (b) only one kind of example (c) blurry, unclear photos (d) many varied examples
4. 4.True or false: “photos in many lights” is good for training a model. (a) False (b) True
5. 5.Which of these is bad for training a model? (a) new data for testing (b) examples of every type (c) copies of one photo (d) many varied examples
6. 6.True or false: “very few examples” is bad for training a model. (a) False (b) True
7. 7.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) False (b) True
8. 8.Which of these is bad for training a model? (a) clear, sharp examples (b) correct labels (c) testing on training data (d) checking labels twice
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) not spam (b) spam
10. 10.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
11. 11.🔍 Which is the odd one out? (a) only one kind of example (b) wrong labels (c) very few examples (d) photos in many lights
12. 12.Which of these is good for training a model? (a) checking labels twice (b) wrong labels (c) labels added at random (d) very few examples
13. 13.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) False (b) True
14. 14.Which of these is good for training a model? (a) testing on training data (b) correct labels (c) very few examples (d) blurry, unclear photos
15. 15.Which of these is bad for training a model? (a) many varied examples (b) clear, sharp examples (c) only one kind of example (d) checking labels twice
16. 16.🔍 Which is the odd one out? (a) blurry, unclear photos (b) new data for testing (c) wrong labels (d) very few examples
17. 17.Which of these is bad for training a model? (a) wrong labels (b) correct labels (c) checking labels twice (d) new data for testing
18. 18.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) spam (b) not spam
19. 19.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it will shut down (c) it will turn yellow (d) it may get it wrong
20. 20.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
21. 21.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) False (b) True
22. 22.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
23. 23.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) False (b) True
24. 24.🔍 Which is the odd one out? (a) only one kind of example (b) copies of one photo (c) very few examples (d) clear, sharp examples
25. 25.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) a song about dogs (c) one single photo (d) many labelled photos
26. 26.True or false: “correct labels” is good for training a model. (a) True (b) False
27. 27.True or false: “examples of every type” is bad for training a model. (a) False (b) True
28. 28.🧠 Machine learning is a way for computers to… (a) charge faster (b) clean screens (c) print pages (d) learn from data
29. 29.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False
30. 30.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
31. 31.Which of these is bad for training a model? (a) correct labels (b) examples of every type (c) photos in many lights (d) very few examples
32. 32.True or false: “blurry, unclear photos” is good for training a model. (a) True (b) False
33. 33.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
34. 34.🔍 Which is the odd one out? (a) checking labels twice (b) labels added at random (c) only one kind of example (d) wrong labels
35. 35.True or false: “only one kind of example” is good for training a model. (a) False (b) True
36. 36.📚 Usually, more good examples make a model… (a) forget everything (b) slower to switch on (c) better at its task (d) change colour
37. 37.Which of these is good for training a model? (a) only one kind of example (b) copies of one photo (c) examples of every type (d) wrong labels
38. 38.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) True (b) False
39. 39.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
40. 40.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training

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