Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 383 · 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.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False
2. 2.🔍 Which is the odd one out? (a) wrong labels (b) labels added at random (c) many varied examples (d) blurry, unclear photos
3. 3.🔍 Which is the odd one out? (a) testing on training data (b) checking labels twice (c) blurry, unclear photos (d) wrong labels
4. 4.Which of these is bad for training a model? (a) new data for testing (b) blurry, unclear photos (c) clear, sharp examples (d) many varied examples
5. 5.🏷️ 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
6. 6.🏷️ 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
7. 7.True or false: “many varied examples” is good for training a model. (a) False (b) True
8. 8.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) spam (b) not spam
9. 9.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) True (b) False
10. 10.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the price (c) the right answer tag (d) the font size
11. 11.True or false: “examples of every type” is bad for training a model. (a) True (b) False
12. 12.🔍 Which is the odd one out? (a) correct labels (b) new data for testing (c) labels added at random (d) many varied examples
13. 13.Which of these is bad for training a model? (a) copies of one photo (b) new data for testing (c) photos in many lights (d) clear, sharp examples
14. 14.True or false: “photos in many lights” is bad for training a model. (a) True (b) False
15. 15.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
16. 16.True or false: “only one kind of example” is bad for training a model. (a) True (b) False
17. 17.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
18. 18.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) True (b) False
19. 19.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) True (b) False
20. 20.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) many labelled photos (c) a song about dogs (d) one single photo
21. 21.📚 Usually, more good examples make a model… (a) slower to switch on (b) forget everything (c) better at its task (d) change colour
22. 22.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
23. 23.True or false: “many varied examples” is bad for training a model. (a) False (b) True
24. 24.🏷️ 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
25. 25.🏷️ 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
26. 26.🏷️ 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
27. 27.🔍 Which is the odd one out? (a) only one kind of example (b) photos in many lights (c) testing on training data (d) copies of one photo
28. 28.🔍 Which is the odd one out? (a) clear, sharp examples (b) copies of one photo (c) correct labels (d) many varied examples
29. 29.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
30. 30.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
31. 31.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
32. 32.True or false: “very few examples” is bad for training a model. (a) False (b) True
33. 33.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
34. 34.🏷️ 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
35. 35.🏷️ 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
36. 36.🔍 Which is the odd one out? (a) testing on training data (b) labels added at random (c) examples of every type (d) blurry, unclear photos
37. 37.Which of these is good for training a model? (a) blurry, unclear photos (b) testing on training data (c) wrong labels (d) photos in many lights
38. 38.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
39. 39.🔍 Which is the odd one out? (a) checking labels twice (b) many varied examples (c) testing on training data (d) examples of every type
40. 40.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) True (b) False

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