Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 430 · 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) not spam (b) spam
2. 2.🧠 Machine learning is a way for computers to… (a) charge faster (b) print pages (c) clean screens (d) learn from data
3. 3.Which of these is good for training a model? (a) testing on training data (b) labels added at random (c) very few examples (d) examples of every type
4. 4.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) spam (b) not spam
5. 5.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
6. 6.True or false: “copies of one photo” is good for training a model. (a) True (b) False
7. 7.🔍 Which is the odd one out? (a) examples of every type (b) labels added at random (c) correct labels (d) checking labels twice
8. 8.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a song about dogs (c) a list of rules only (d) many labelled photos
9. 9.True or false: “checking labels twice” is bad for training a model. (a) False (b) True
10. 10.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) True (b) False
11. 11.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
12. 12.🔍 Which is the odd one out? (a) only one kind of example (b) clear, sharp examples (c) photos in many lights (d) examples of every type
13. 13.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False
14. 14.🏷️ 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
15. 15.🔍 Which is the odd one out? (a) copies of one photo (b) wrong labels (c) only one kind of example (d) many varied examples
16. 16.🔍 Which is the odd one out? (a) wrong labels (b) blurry, unclear photos (c) copies of one photo (d) checking labels twice
17. 17.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) True (b) False
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: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) True (b) False
20. 20.🏷️ 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
21. 21.Which of these is good for training a model? (a) labels added at random (b) very few examples (c) blurry, unclear photos (d) clear, sharp examples
22. 22.Which of these is good for training a model? (a) testing on training data (b) very few examples (c) new data for testing (d) labels added at random
23. 23.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
24. 24.Which of these is bad for training a model? (a) examples of every type (b) many varied examples (c) copies of one photo (d) clear, sharp examples
25. 25.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
26. 26.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) True (b) False
27. 27.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) False (b) True
28. 28.🏷️ What is a “label” in machine learning? (a) the right answer tag (b) the price (c) a sticker on a laptop (d) the font size
29. 29.True or false: “very few examples” is bad for training a model. (a) False (b) True
30. 30.🔍 Which is the odd one out? (a) new data for testing (b) labels added at random (c) only one kind of example (d) blurry, unclear photos
31. 31.🏷️ 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
32. 32.Which of these is bad for training a model? (a) checking labels twice (b) examples of every type (c) wrong labels (d) clear, sharp examples
33. 33.True or false: “clear, sharp examples” is good for training a model. (a) False (b) True
34. 34.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) spam (b) not spam
35. 35.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
36. 36.Which of these is good for training a model? (a) copies of one photo (b) correct labels (c) testing on training data (d) very few examples
37. 37.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
38. 38.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) False (b) True
39. 39.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
40. 40.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True

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