Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 355 · 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: checking labels twice? (a) good for training (b) bad for training
2. 2.🔍 Which is the odd one out? (a) only one kind of example (b) correct labels (c) clear, sharp examples (d) many varied examples
3. 3.🧠 Machine learning is a way for computers to… (a) print pages (b) clean screens (c) charge faster (d) learn from data
4. 4.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) False (b) True
5. 5.Which of these is good for training a model? (a) correct labels (b) copies of one photo (c) labels added at random (d) blurry, unclear photos
6. 6.🏷️ 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) not spam (b) spam
7. 7.True or false: “copies of one photo” is good for training a model. (a) False (b) True
8. 8.🔍 Which is the odd one out? (a) clear, sharp examples (b) very few examples (c) new data for testing (d) examples of every type
9. 9.📚 Good or bad for training a model: very few examples? (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? “Your library book is due on Monday” (a) spam (b) not spam
11. 11.🏷️ 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
12. 12.Which of these is good for training a model? (a) testing on training data (b) many varied examples (c) only one kind of example (d) labels added at random
13. 13.🔍 Which is the odd one out? (a) new data for testing (b) blurry, unclear photos (c) photos in many lights (d) many varied examples
14. 14.🔍 Which is the odd one out? (a) photos in many lights (b) very few examples (c) testing on training data (d) only one kind of example
15. 15.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
16. 16.🏷️ 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
17. 17.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True
18. 18.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
19. 19.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
20. 20.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
21. 21.🔍 Which is the odd one out? (a) new data for testing (b) clear, sharp examples (c) many varied examples (d) wrong labels
22. 22.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
23. 23.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it will be perfect (c) it will turn yellow (d) it may get it wrong
24. 24.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
25. 25.🏷️ What is a “label” in machine learning? (a) the right answer tag (b) a sticker on a laptop (c) the font size (d) the price
26. 26.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) False (b) True
27. 27.🔍 Which is the odd one out? (a) many varied examples (b) clear, sharp examples (c) labels added at random (d) photos in many lights
28. 28.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) False (b) True
29. 29.Which of these is good for training a model? (a) copies of one photo (b) labels added at random (c) only one kind of example (d) new data for testing
30. 30.Which of these is bad for training a model? (a) photos in many lights (b) examples of every type (c) labels added at random (d) many varied examples
31. 31.True or false: “many varied examples” is bad for training a model. (a) True (b) False
32. 32.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
33. 33.🏷️ 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
34. 34.True or false: “correct labels” is bad for training a model. (a) False (b) True
35. 35.🔍 Which is the odd one out? (a) testing on training data (b) blurry, unclear photos (c) many varied examples (d) copies of one photo
36. 36.True or false: “many varied examples” is good for training a model. (a) False (b) True
37. 37.📚 Usually, more good examples make a model… (a) slower to switch on (b) forget everything (c) better at its task (d) change colour
38. 38.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) True (b) False
39. 39.Which of these is bad for training a model? (a) clear, sharp examples (b) photos in many lights (c) examples of every type (d) wrong labels
40. 40.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False

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