Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 219 · 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: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
2. 2.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
3. 3.True or false: “wrong labels” is good for training a model. (a) True (b) False
4. 4.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
5. 5.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True
6. 6.Which of these is bad for training a model? (a) examples of every type (b) many varied examples (c) very few examples (d) photos in many lights
7. 7.Which of these is good for training a model? (a) only one kind of example (b) examples of every type (c) testing on training data (d) copies of one photo
8. 8.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) True (b) False
9. 9.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
10. 10.🏷️ 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
11. 11.Which of these is bad for training a model? (a) wrong labels (b) clear, sharp examples (c) checking labels twice (d) examples of every type
12. 12.📚 Usually, more good examples make a model… (a) better at its task (b) slower to switch on (c) change colour (d) forget everything
13. 13.True or false: “blurry, unclear photos” is bad for training a model. (a) False (b) True
14. 14.Which of these is good for training a model? (a) very few examples (b) checking labels twice (c) labels added at random (d) wrong labels
15. 15.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) spam (b) not spam
16. 16.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the font size (c) the price (d) the right answer tag
17. 17.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
18. 18.True or false: “very few examples” is good for training a model. (a) False (b) True
19. 19.True or false: “correct labels” is bad for training a model. (a) True (b) False
20. 20.🏷️ 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
21. 21.Which of these is bad for training a model? (a) photos in many lights (b) examples of every type (c) testing on training data (d) correct labels
22. 22.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) not spam (b) spam
23. 23.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) True (b) False
24. 24.True or false: “testing on training data” is good for training a model. (a) False (b) True
25. 25.True or false: “photos in many lights” is bad for training a model. (a) True (b) False
26. 26.True or false: “labels added at random” is bad for training a model. (a) True (b) False
27. 27.Which of these is good for training a model? (a) very few examples (b) blurry, unclear photos (c) only one kind of example (d) clear, sharp examples
28. 28.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
29. 29.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) True (b) False
30. 30.🏷️ 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
31. 31.🔍 Which is the odd one out? (a) only one kind of example (b) checking labels twice (c) clear, sharp examples (d) correct labels
32. 32.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) False (b) True
33. 33.🔍 Which is the odd one out? (a) wrong labels (b) testing on training data (c) many varied examples (d) blurry, unclear photos
34. 34.Which of these is bad for training a model? (a) clear, sharp examples (b) copies of one photo (c) checking labels twice (d) photos in many lights
35. 35.Which of these is good for training a model? (a) very few examples (b) blurry, unclear photos (c) copies of one photo (d) photos in many lights
36. 36.🔍 Which is the odd one out? (a) blurry, unclear photos (b) wrong labels (c) copies of one photo (d) checking labels twice
37. 37.🔍 Which is the odd one out? (a) correct labels (b) photos in many lights (c) clear, sharp examples (d) testing on training data
38. 38.True or false: “copies of one photo” is bad for training a model. (a) False (b) True
39. 39.🏷️ 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
40. 40.Which of these is good for training a model? (a) labels added at random (b) new data for testing (c) wrong labels (d) blurry, unclear photos

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