Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 295 · 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? “You won a free phone! Click now!” (a) spam (b) not spam
2. 2.🏷️ 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
3. 3.🏷️ 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
4. 4.Which of these is bad for training a model? (a) only one kind of example (b) photos in many lights (c) clear, sharp examples (d) correct labels
5. 5.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) False (b) True
6. 6.Which of these is good for training a model? (a) blurry, unclear photos (b) testing on training data (c) only one kind of example (d) examples of every type
7. 7.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
8. 8.Which of these is bad for training a model? (a) clear, sharp examples (b) examples of every type (c) copies of one photo (d) many varied examples
9. 9.🔍 Which is the odd one out? (a) blurry, unclear photos (b) very few examples (c) checking labels twice (d) wrong labels
10. 10.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
11. 11.🧠 Machine learning is a way for computers to… (a) clean screens (b) learn from data (c) print pages (d) charge faster
12. 12.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) True (b) False
13. 13.True or false: “many varied examples” is good for training a model. (a) True (b) False
14. 14.📚 Usually, more good examples make a model… (a) better at its task (b) slower to switch on (c) change colour (d) forget everything
15. 15.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) a list of rules only (c) a song about dogs (d) one single photo
16. 16.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) False (b) True
17. 17.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
18. 18.Which of these is bad for training a model? (a) photos in many lights (b) checking labels twice (c) very few examples (d) clear, sharp examples
19. 19.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
20. 20.Which of these is good for training a model? (a) very few examples (b) only one kind of example (c) blurry, unclear photos (d) correct labels
21. 21.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
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) spam (b) not spam
23. 23.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
24. 24.True or false: “testing on training data” is good for training a model. (a) True (b) False
25. 25.True or false: “testing on training data” is bad for training a model. (a) False (b) True
26. 26.🏷️ What is a “label” in machine learning? (a) the price (b) a sticker on a laptop (c) the right answer tag (d) the font size
27. 27.🏷️ 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
28. 28.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) spam (b) not spam
29. 29.Which of these is good for training a model? (a) labels added at random (b) checking labels twice (c) only one kind of example (d) testing on training data
30. 30.🔍 Which is the odd one out? (a) copies of one photo (b) examples of every type (c) correct labels (d) checking labels twice
31. 31.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) spam (b) not spam
32. 32.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) True (b) False
33. 33.True or false: “photos in many lights” is good for training a model. (a) False (b) True
34. 34.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
35. 35.🔍 Which is the odd one out? (a) clear, sharp examples (b) checking labels twice (c) only one kind of example (d) correct labels
36. 36.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) False (b) True
37. 37.🔍 Which is the odd one out? (a) new data for testing (b) very few examples (c) only one kind of example (d) copies of one photo
38. 38.Which of these is good for training a model? (a) only one kind of example (b) new data for testing (c) copies of one photo (d) very few examples
39. 39.🔍 Which is the odd one out? (a) very few examples (b) labels added at random (c) examples of every type (d) copies of one photo
40. 40.True or false: “labels added at random” is good for training a model. (a) False (b) True

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