Machine Learning for Kids Worksheet

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

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