Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 482 · 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) many varied examples (b) checking labels twice (c) copies of one photo (d) examples of every type
2. 2.Which of these is good for training a model? (a) wrong labels (b) blurry, unclear photos (c) copies of one photo (d) clear, sharp examples
3. 3.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
4. 4.🏷️ 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
5. 5.🔍 Which is the odd one out? (a) very few examples (b) wrong labels (c) checking labels twice (d) copies of one photo
6. 6.🔍 Which is the odd one out? (a) labels added at random (b) very few examples (c) only one kind of example (d) many varied examples
7. 7.🏷️ What is a “label” in machine learning? (a) the font size (b) the price (c) a sticker on a laptop (d) the right answer tag
8. 8.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
9. 9.Which of these is good for training a model? (a) only one kind of example (b) very few examples (c) labels added at random (d) photos in many lights
10. 10.🐶 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) a song about dogs (d) many labelled photos
11. 11.🧠 Machine learning is a way for computers to… (a) print pages (b) learn from data (c) clean screens (d) charge faster
12. 12.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
13. 13.Which of these is good for training a model? (a) very few examples (b) only one kind of example (c) wrong labels (d) correct labels
14. 14.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
15. 15.True or false: “checking labels twice” is good for training a model. (a) True (b) False
16. 16.🔍 Which is the odd one out? (a) testing on training data (b) photos in many lights (c) correct labels (d) checking labels twice
17. 17.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
18. 18.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
19. 19.🏷️ 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
20. 20.True or false: “correct labels” is bad for training a model. (a) True (b) False
21. 21.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
22. 22.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
23. 23.Which of these is bad for training a model? (a) correct labels (b) wrong labels (c) photos in many lights (d) clear, sharp examples
24. 24.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
25. 25.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) False (b) True
26. 26.True or false: “wrong labels” is good for training a model. (a) False (b) True
27. 27.🔍 Which is the odd one out? (a) checking labels twice (b) clear, sharp examples (c) examples of every type (d) very few examples
28. 28.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
29. 29.📚 Usually, more good examples make a model… (a) slower to switch on (b) change colour (c) forget everything (d) better at its task
30. 30.🏷️ 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
31. 31.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
32. 32.Which of these is bad for training a model? (a) new data for testing (b) testing on training data (c) many varied examples (d) photos in many lights
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.True or false: “blurry, unclear photos” is bad for training a model. (a) False (b) True
35. 35.True or false: “wrong labels” is bad for training a model. (a) True (b) False
36. 36.True or false: “many varied examples” is good for training a model. (a) False (b) True
37. 37.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) False (b) True
38. 38.Which of these is good for training a model? (a) new data for testing (b) wrong labels (c) labels added at random (d) blurry, unclear photos
39. 39.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
40. 40.Which of these is bad for training a model? (a) blurry, unclear photos (b) new data for testing (c) examples of every type (d) correct labels

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