Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 556 · 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? “Send your password to claim a prize” (a) not spam (b) spam
2. 2.🧠 Machine learning is a way for computers to… (a) clean screens (b) charge faster (c) print pages (d) learn from data
3. 3.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) True (b) False
4. 4.Which of these is bad for training a model? (a) copies of one photo (b) new data for testing (c) many varied examples (d) correct labels
5. 5.True or false: “clear, sharp examples” is bad for training a model. (a) False (b) True
6. 6.🔍 Which is the odd one out? (a) checking labels twice (b) labels added at random (c) correct labels (d) new data for testing
7. 7.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it may get it wrong (c) it will be perfect (d) it will turn yellow
8. 8.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) True (b) False
9. 9.🏷️ What is a “label” in machine learning? (a) the font size (b) a sticker on a laptop (c) the price (d) the right answer tag
10. 10.🏷️ 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
11. 11.Which of these is good for training a model? (a) only one kind of example (b) testing on training data (c) new data for testing (d) labels added at random
12. 12.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
13. 13.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
14. 14.True or false: “blurry, unclear photos” is bad for training a model. (a) False (b) True
15. 15.True or false: “correct labels” is good for training a model. (a) True (b) False
16. 16.📚 Usually, more good examples make a model… (a) better at its task (b) forget everything (c) slower to switch on (d) change colour
17. 17.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
18. 18.True or false: “examples of every type” is bad for training a model. (a) True (b) False
19. 19.🏷️ 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
20. 20.🔍 Which is the odd one out? (a) photos in many lights (b) checking labels twice (c) copies of one photo (d) many varied examples
21. 21.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
22. 22.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
23. 23.True or false: “copies of one photo” is good for training a model. (a) True (b) False
24. 24.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
25. 25.True or false: “checking labels twice” is good for training a model. (a) True (b) False
26. 26.True or false: “many varied examples” is bad for training a model. (a) False (b) True
27. 27.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) True (b) False
28. 28.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
29. 29.🏷️ 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
30. 30.Which of these is bad for training a model? (a) testing on training data (b) new data for testing (c) many varied examples (d) clear, sharp examples
31. 31.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) a list of rules only (c) one single photo (d) many labelled photos
32. 32.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) not spam (b) spam
33. 33.Which of these is good for training a model? (a) very few examples (b) labels added at random (c) copies of one photo (d) examples of every type
34. 34.True or false: “photos in many lights” is bad for training a model. (a) False (b) True
35. 35.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
36. 36.🔍 Which is the odd one out? (a) new data for testing (b) correct labels (c) clear, sharp examples (d) wrong labels
37. 37.Which of these is bad for training a model? (a) clear, sharp examples (b) photos in many lights (c) very few examples (d) checking labels twice
38. 38.🔍 Which is the odd one out? (a) very few examples (b) blurry, unclear photos (c) only one kind of example (d) correct labels
39. 39.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
40. 40.🏷️ 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

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