Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 265 · 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.🏷️ 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
2. 2.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) True (b) False
3. 3.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
4. 4.🔍 Which is the odd one out? (a) copies of one photo (b) new data for testing (c) checking labels twice (d) many varied examples
5. 5.True or false: “correct labels” is bad for training a model. (a) True (b) False
6. 6.🏷️ 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
7. 7.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
8. 8.Which of these is good for training a model? (a) blurry, unclear photos (b) examples of every type (c) testing on training data (d) labels added at random
9. 9.True or false: “many varied examples” is bad for training a model. (a) False (b) True
10. 10.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
11. 11.Which of these is good for training a model? (a) blurry, unclear photos (b) copies of one photo (c) only one kind of example (d) checking labels twice
12. 12.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
13. 13.🔍 Which is the odd one out? (a) new data for testing (b) examples of every type (c) testing on training data (d) correct labels
14. 14.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
15. 15.True or false: “checking labels twice” is good for training a model. (a) False (b) True
16. 16.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False
17. 17.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) False (b) True
18. 18.Which of these is bad for training a model? (a) examples of every type (b) clear, sharp examples (c) wrong labels (d) new data for testing
19. 19.🏷️ 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
20. 20.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
21. 21.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
22. 22.🧠 Machine learning is a way for computers to… (a) learn from data (b) print pages (c) clean screens (d) charge faster
23. 23.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) True (b) False
24. 24.🏷️ 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
25. 25.🏷️ What is a “label” in machine learning? (a) the price (b) the right answer tag (c) the font size (d) a sticker on a laptop
26. 26.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
27. 27.Which of these is good for training a model? (a) testing on training data (b) clear, sharp examples (c) copies of one photo (d) blurry, unclear photos
28. 28.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) True (b) False
29. 29.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
30. 30.Which of these is good for training a model? (a) testing on training data (b) new data for testing (c) labels added at random (d) very few examples
31. 31.True or false: “clear, sharp examples” is good for training a model. (a) True (b) False
32. 32.🏷️ 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
33. 33.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) spam (b) not spam
34. 34.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
35. 35.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
36. 36.🏷️ 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
37. 37.🔍 Which is the odd one out? (a) clear, sharp examples (b) very few examples (c) checking labels twice (d) many varied examples
38. 38.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
39. 39.True or false: “very few examples” is good for training a model. (a) False (b) True
40. 40.🔍 Which is the odd one out? (a) clear, sharp examples (b) wrong labels (c) very few examples (d) labels added at random

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