Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 321 · 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: clear, sharp examples? (a) bad for training (b) good for training
2. 2.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
3. 3.🔍 Which is the odd one out? (a) testing on training data (b) blurry, unclear photos (c) checking labels twice (d) only one kind of example
4. 4.🏷️ 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
5. 5.Which of these is bad for training a model? (a) clear, sharp examples (b) checking labels twice (c) testing on training data (d) correct labels
6. 6.🔍 Which is the odd one out? (a) labels added at random (b) many varied examples (c) copies of one photo (d) only one kind of example
7. 7.Which of these is good for training a model? (a) labels added at random (b) blurry, unclear photos (c) examples of every type (d) wrong labels
8. 8.🔍 Which is the odd one out? (a) blurry, unclear photos (b) many varied examples (c) checking labels twice (d) new data for testing
9. 9.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
10. 10.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) True (b) False
11. 11.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) spam (b) not spam
12. 12.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
13. 13.Which of these is good for training a model? (a) blurry, unclear photos (b) very few examples (c) checking labels twice (d) only one kind of example
14. 14.True or false: “many varied examples” is good for training a model. (a) True (b) False
15. 15.🔍 Which is the odd one out? (a) correct labels (b) very few examples (c) photos in many lights (d) many varied examples
16. 16.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) True (b) False
17. 17.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) False (b) True
18. 18.True or false: “examples of every type” is good for training a model. (a) True (b) False
19. 19.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) not spam (b) spam
20. 20.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) True (b) False
21. 21.True or false: “blurry, unclear photos” is bad for training a model. (a) True (b) False
22. 22.True or false: “testing on training data” is good for training a model. (a) True (b) False
23. 23.🔍 Which is the odd one out? (a) checking labels twice (b) new data for testing (c) copies of one photo (d) examples of every type
24. 24.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
25. 25.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) False (b) True
26. 26.🏷️ 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
27. 27.Which of these is good for training a model? (a) very few examples (b) wrong labels (c) new data for testing (d) testing on training data
28. 28.Which of these is bad for training a model? (a) correct labels (b) examples of every type (c) new data for testing (d) very few examples
29. 29.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it will turn yellow (c) it may get it wrong (d) it will be perfect
30. 30.True or false: “labels added at random” is good for training a model. (a) True (b) False
31. 31.🏷️ 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
32. 32.Which of these is bad for training a model? (a) new data for testing (b) clear, sharp examples (c) only one kind of example (d) correct labels
33. 33.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
34. 34.Which of these is bad for training a model? (a) new data for testing (b) many varied examples (c) examples of every type (d) labels added at random
35. 35.🔍 Which is the odd one out? (a) testing on training data (b) correct labels (c) many varied examples (d) clear, sharp examples
36. 36.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
37. 37.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) spam (b) not spam
38. 38.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
39. 39.True or false: “examples of every type” is bad for training a model. (a) False (b) True
40. 40.True or false: “blurry, unclear photos” is good for training a model. (a) True (b) False

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