Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 413 · 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.🏷️ 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
2. 2.Which of these is good for training a model? (a) copies of one photo (b) very few examples (c) only one kind of example (d) clear, sharp examples
3. 3.📚 Usually, more good examples make a model… (a) better at its task (b) forget everything (c) slower to switch on (d) change colour
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.Which of these is bad for training a model? (a) clear, sharp examples (b) photos in many lights (c) wrong labels (d) checking labels twice
6. 6.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True
7. 7.🧠 Machine learning is a way for computers to… (a) clean screens (b) learn from data (c) print pages (d) charge faster
8. 8.🏷️ What is a “label” in machine learning? (a) the price (b) the right answer tag (c) a sticker on a laptop (d) the font size
9. 9.True or false: “very few examples” is good for training a model. (a) False (b) True
10. 10.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False
11. 11.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
12. 12.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
13. 13.Which of these is bad for training a model? (a) photos in many lights (b) labels added at random (c) many varied examples (d) correct labels
14. 14.True or false: “new data for testing” is good for training a model. (a) False (b) True
15. 15.🔍 Which is the odd one out? (a) wrong labels (b) correct labels (c) many varied examples (d) photos in many lights
16. 16.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) not spam (b) spam
17. 17.Which of these is good for training a model? (a) only one kind of example (b) labels added at random (c) correct labels (d) testing on training data
18. 18.Which of these is bad for training a model? (a) only one kind of example (b) correct labels (c) examples of every type (d) checking labels twice
19. 19.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
20. 20.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a list of rules only (c) many labelled photos (d) a song about dogs
21. 21.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
22. 22.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) not spam (b) spam
23. 23.Which of these is good for training a model? (a) copies of one photo (b) testing on training data (c) wrong labels (d) new data for testing
24. 24.🏷️ 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
25. 25.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) True (b) False
26. 26.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
27. 27.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
28. 28.Which of these is good for training a model? (a) examples of every type (b) copies of one photo (c) only one kind of example (d) labels added at random
29. 29.🔍 Which is the odd one out? (a) new data for testing (b) correct labels (c) clear, sharp examples (d) only one kind of example
30. 30.🔍 Which is the odd one out? (a) very few examples (b) photos in many lights (c) clear, sharp examples (d) checking labels twice
31. 31.Which of these is bad for training a model? (a) many varied examples (b) blurry, unclear photos (c) examples of every type (d) clear, sharp examples
32. 32.🔍 Which is the odd one out? (a) photos in many lights (b) labels added at random (c) only one kind of example (d) very few examples
33. 33.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) False (b) True
34. 34.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
35. 35.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) True (b) False
36. 36.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True
37. 37.Which of these is good for training a model? (a) wrong labels (b) many varied examples (c) copies of one photo (d) very few examples
38. 38.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
39. 39.True or false: “checking labels twice” is good for training a model. (a) True (b) False
40. 40.Which of these is good for training a model? (a) labels added at random (b) wrong labels (c) photos in many lights (d) only one kind of example

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