Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 61 · 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.🏷️ 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
3. 3.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
4. 4.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
5. 5.Which of these is bad for training a model? (a) blurry, unclear photos (b) new data for testing (c) examples of every type (d) photos in many lights
6. 6.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
7. 7.True or false: “copies of one photo” is good for training a model. (a) True (b) False
8. 8.🔍 Which is the odd one out? (a) examples of every type (b) photos in many lights (c) correct labels (d) wrong labels
9. 9.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) True (b) False
10. 10.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) not spam (b) spam
11. 11.Which of these is good for training a model? (a) copies of one photo (b) checking labels twice (c) wrong labels (d) labels added at random
12. 12.Which of these is good for training a model? (a) examples of every type (b) copies of one photo (c) wrong labels (d) very few examples
13. 13.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
14. 14.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) True (b) False
15. 15.🔍 Which is the odd one out? (a) many varied examples (b) checking labels twice (c) photos in many lights (d) only one kind of example
16. 16.Which of these is bad for training a model? (a) clear, sharp examples (b) correct labels (c) labels added at random (d) checking labels twice
17. 17.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it may get it wrong (c) it will be perfect (d) it will shut down
18. 18.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) True (b) False
19. 19.True or false: “examples of every type” is bad for training a model. (a) False (b) True
20. 20.Which of these is good for training a model? (a) very few examples (b) copies of one photo (c) testing on training data (d) new data for testing
21. 21.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
22. 22.True or false: “many varied examples” is bad for training a model. (a) False (b) True
23. 23.True or false: “checking labels twice” is good for training a model. (a) False (b) True
24. 24.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) False (b) True
25. 25.🔍 Which is the odd one out? (a) clear, sharp examples (b) many varied examples (c) new data for testing (d) labels added at random
26. 26.🏷️ 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
27. 27.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
28. 28.🔍 Which is the odd one out? (a) labels added at random (b) correct labels (c) very few examples (d) testing on training data
29. 29.🏷️ 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
30. 30.🔍 Which is the odd one out? (a) very few examples (b) wrong labels (c) examples of every type (d) copies of one photo
31. 31.True or false: “testing on training data” is bad for training a model. (a) False (b) True
32. 32.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) not spam (b) spam
33. 33.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) False (b) True
34. 34.🔍 Which is the odd one out? (a) checking labels twice (b) copies of one photo (c) new data for testing (d) correct labels
35. 35.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) False (b) True
36. 36.Which of these is bad for training a model? (a) copies of one photo (b) new data for testing (c) photos in many lights (d) examples of every type
37. 37.Which of these is bad for training a model? (a) testing on training data (b) clear, sharp examples (c) correct labels (d) checking labels twice
38. 38.Which of these is good for training a model? (a) many varied examples (b) copies of one photo (c) wrong labels (d) very few examples
39. 39.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
40. 40.🔍 Which is the odd one out? (a) correct labels (b) new data for testing (c) blurry, unclear photos (d) clear, sharp examples

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