Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 439 · 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.🔍 Which is the odd one out? (a) wrong labels (b) photos in many lights (c) correct labels (d) many varied examples
2. 2.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False
3. 3.True or false: “examples of every type” is good for training a model. (a) False (b) True
4. 4.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) spam (b) not spam
5. 5.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
6. 6.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
7. 7.Which of these is good for training a model? (a) testing on training data (b) only one kind of example (c) new data for testing (d) blurry, unclear photos
8. 8.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) not spam (b) spam
9. 9.🏷️ 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
10. 10.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
11. 11.Which of these is good for training a model? (a) correct labels (b) wrong labels (c) copies of one photo (d) blurry, unclear photos
12. 12.Which of these is good for training a model? (a) copies of one photo (b) wrong labels (c) very few examples (d) checking labels twice
13. 13.Which of these is bad for training a model? (a) correct labels (b) labels added at random (c) checking labels twice (d) examples of every type
14. 14.True or false: “checking labels twice” is good for training a model. (a) False (b) True
15. 15.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
16. 16.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
17. 17.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it will shut down (c) it will turn yellow (d) it may get it wrong
18. 18.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) False (b) True
19. 19.🧠 Machine learning is a way for computers to… (a) clean screens (b) charge faster (c) print pages (d) learn from data
20. 20.🏷️ 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
21. 21.🔍 Which is the odd one out? (a) copies of one photo (b) many varied examples (c) very few examples (d) labels added at random
22. 22.🔍 Which is the odd one out? (a) copies of one photo (b) blurry, unclear photos (c) wrong labels (d) clear, sharp examples
23. 23.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
24. 24.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) one single photo (c) many labelled photos (d) a song about dogs
25. 25.🏷️ 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
26. 26.🔍 Which is the odd one out? (a) new data for testing (b) photos in many lights (c) checking labels twice (d) very few examples
27. 27.🏷️ 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
28. 28.Which of these is bad for training a model? (a) photos in many lights (b) checking labels twice (c) only one kind of example (d) examples of every type
29. 29.Which of these is bad for training a model? (a) many varied examples (b) photos in many lights (c) very few examples (d) checking labels twice
30. 30.Which of these is good for training a model? (a) labels added at random (b) many varied examples (c) wrong labels (d) very few examples
31. 31.True or false: “only one kind of example” is good for training a model. (a) True (b) False
32. 32.Which of these is good for training a model? (a) clear, sharp examples (b) wrong labels (c) only one kind of example (d) testing on training data
33. 33.🔍 Which is the odd one out? (a) new data for testing (b) many varied examples (c) copies of one photo (d) checking labels twice
34. 34.True or false: “checking labels twice” is bad for training a model. (a) False (b) True
35. 35.🏷️ 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
36. 36.📚 Usually, more good examples make a model… (a) forget everything (b) change colour (c) better at its task (d) slower to switch on
37. 37.True or false: “very few examples” is bad for training a model. (a) True (b) False
38. 38.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
39. 39.True or false: “labels added at random” is bad for training a model. (a) False (b) True
40. 40.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False

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