Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 120 · 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: “clear, sharp examples” is bad for training a model. (a) False (b) True
2. 2.📚 Usually, more good examples make a model… (a) slower to switch on (b) forget everything (c) change colour (d) better at its task
3. 3.True or false: “very few examples” is bad for training a model. (a) False (b) True
4. 4.🔍 Which is the odd one out? (a) checking labels twice (b) testing on training data (c) new data for testing (d) photos in many lights
5. 5.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it will be perfect (c) it may get it wrong (d) it will shut down
6. 6.🏷️ 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
7. 7.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
8. 8.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) a song about dogs (c) one single photo (d) many labelled photos
9. 9.🔍 Which is the odd one out? (a) new data for testing (b) clear, sharp examples (c) examples of every type (d) copies of one photo
10. 10.Which of these is good for training a model? (a) copies of one photo (b) only one kind of example (c) many varied examples (d) very few examples
11. 11.True or false: “examples of every type” is bad for training a model. (a) True (b) False
12. 12.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
13. 13.🔍 Which is the odd one out? (a) only one kind of example (b) correct labels (c) labels added at random (d) copies of one photo
14. 14.🧠 Machine learning is a way for computers to… (a) learn from data (b) charge faster (c) clean screens (d) print pages
15. 15.Which of these is bad for training a model? (a) examples of every type (b) photos in many lights (c) very few examples (d) many varied examples
16. 16.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) not spam (b) spam
17. 17.🔍 Which is the odd one out? (a) examples of every type (b) correct labels (c) clear, sharp examples (d) very few examples
18. 18.Which of these is good for training a model? (a) blurry, unclear photos (b) labels added at random (c) checking labels twice (d) testing on training data
19. 19.True or false: “testing on training data” is bad for training a model. (a) True (b) False
20. 20.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
21. 21.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
22. 22.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
23. 23.🔍 Which is the odd one out? (a) clear, sharp examples (b) labels added at random (c) examples of every type (d) correct labels
24. 24.🏷️ 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) spam (b) not spam
25. 25.🏷️ 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
26. 26.Which of these is good for training a model? (a) very few examples (b) labels added at random (c) wrong labels (d) new data for testing
27. 27.🔍 Which is the odd one out? (a) only one kind of example (b) many varied examples (c) checking labels twice (d) examples of every type
28. 28.🏷️ 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
29. 29.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) spam (b) not spam
30. 30.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
31. 31.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) True (b) False
32. 32.🔍 Which is the odd one out? (a) very few examples (b) wrong labels (c) photos in many lights (d) blurry, unclear photos
33. 33.🏷️ 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
34. 34.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
35. 35.Which of these is bad for training a model? (a) correct labels (b) examples of every type (c) many varied examples (d) labels added at random
36. 36.Which of these is bad for training a model? (a) many varied examples (b) checking labels twice (c) correct labels (d) blurry, unclear photos
37. 37.True or false: “copies of one photo” is good for training a model. (a) False (b) True
38. 38.True or false: “copies of one photo” is bad for training a model. (a) True (b) False
39. 39.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
40. 40.🏷️ What is a “label” in machine learning? (a) the price (b) the font size (c) a sticker on a laptop (d) the right answer tag

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