Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 319 · 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? “Happy birthday! See you at lunch” (a) spam (b) not spam
2. 2.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
3. 3.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
4. 4.🔍 Which is the odd one out? (a) copies of one photo (b) photos in many lights (c) blurry, unclear photos (d) wrong labels
5. 5.Which of these is good for training a model? (a) wrong labels (b) copies of one photo (c) very few examples (d) correct labels
6. 6.🔍 Which is the odd one out? (a) correct labels (b) many varied examples (c) wrong labels (d) checking labels twice
7. 7.🏷️ 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
8. 8.Which of these is good for training a model? (a) blurry, unclear photos (b) many varied examples (c) very few examples (d) wrong labels
9. 9.🔍 Which is the odd one out? (a) correct labels (b) clear, sharp examples (c) new data for testing (d) testing on training data
10. 10.🧠 Machine learning is a way for computers to… (a) learn from data (b) charge faster (c) print pages (d) clean screens
11. 11.True or false: “checking labels twice” is good for training a model. (a) True (b) False
12. 12.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) True (b) False
13. 13.🐶 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) a song about dogs (d) many labelled photos
14. 14.🔍 Which is the odd one out? (a) blurry, unclear photos (b) labels added at random (c) clear, sharp examples (d) very few examples
15. 15.🏷️ 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
16. 16.Which of these is good for training a model? (a) labels added at random (b) testing on training data (c) clear, sharp examples (d) copies of one photo
17. 17.Which of these is bad for training a model? (a) blurry, unclear photos (b) photos in many lights (c) examples of every type (d) correct labels
18. 18.True or false: the message “Your library book is due on Monday” 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? “Please buy milk on the way home” (a) spam (b) not spam
20. 20.🏷️ 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
21. 21.Which of these is bad for training a model? (a) photos in many lights (b) correct labels (c) copies of one photo (d) checking labels twice
22. 22.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it will be perfect (c) it may get it wrong (d) it will shut down
23. 23.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
24. 24.Which of these is bad for training a model? (a) new data for testing (b) only one kind of example (c) checking labels twice (d) photos in many lights
25. 25.🏷️ What is a “label” in machine learning? (a) the right answer tag (b) a sticker on a laptop (c) the price (d) the font size
26. 26.Which of these is bad for training a model? (a) new data for testing (b) photos in many lights (c) wrong labels (d) checking labels twice
27. 27.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) spam (b) not spam
28. 28.True or false: “examples of every type” is bad for training a model. (a) False (b) True
29. 29.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
30. 30.True or false: “very few examples” is good for training a model. (a) True (b) False
31. 31.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
32. 32.True or false: “many varied examples” is good for training a model. (a) False (b) True
33. 33.🏷️ 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
34. 34.🔍 Which is the odd one out? (a) new data for testing (b) photos in many lights (c) checking labels twice (d) blurry, unclear photos
35. 35.True or false: “testing on training data” is bad for training a model. (a) False (b) True
36. 36.True or false: “only one kind of example” is good for training a model. (a) False (b) True
37. 37.🔍 Which is the odd one out? (a) labels added at random (b) clear, sharp examples (c) correct labels (d) new data for testing
38. 38.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
39. 39.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True
40. 40.🔍 Which is the odd one out? (a) very few examples (b) examples of every type (c) new data for testing (d) photos in many lights

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