Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 77 · 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: “photos in many lights” is bad for training a model. (a) False (b) True
2. 2.🏷️ 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
3. 3.🏷️ What is a “label” in machine learning? (a) the price (b) the font size (c) a sticker on a laptop (d) the right answer tag
4. 4.Which of these is good for training a model? (a) testing on training data (b) very few examples (c) photos in many lights (d) labels added at random
5. 5.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) one single photo (c) a list of rules only (d) a song about dogs
6. 6.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) not spam (b) spam
7. 7.📚 Usually, more good examples make a model… (a) forget everything (b) change colour (c) slower to switch on (d) better at its task
8. 8.🔍 Which is the odd one out? (a) new data for testing (b) many varied examples (c) labels added at random (d) clear, sharp examples
9. 9.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
10. 10.🏷️ 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
11. 11.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
12. 12.Which of these is bad for training a model? (a) correct labels (b) new data for testing (c) blurry, unclear photos (d) many varied examples
13. 13.🏷️ 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
14. 14.🏷️ 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
15. 15.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True
16. 16.Which of these is bad for training a model? (a) many varied examples (b) examples of every type (c) testing on training data (d) checking labels twice
17. 17.🔍 Which is the odd one out? (a) checking labels twice (b) photos in many lights (c) many varied examples (d) only one kind of example
18. 18.🔍 Which is the odd one out? (a) clear, sharp examples (b) many varied examples (c) blurry, unclear photos (d) correct labels
19. 19.True or false: “photos in many lights” is good for training a model. (a) True (b) False
20. 20.Which of these is good for training a model? (a) very few examples (b) many varied examples (c) copies of one photo (d) blurry, unclear photos
21. 21.🔍 Which is the odd one out? (a) blurry, unclear photos (b) testing on training data (c) examples of every type (d) labels added at random
22. 22.🏷️ 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
23. 23.🏷️ 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
24. 24.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
25. 25.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
26. 26.🔍 Which is the odd one out? (a) new data for testing (b) photos in many lights (c) wrong labels (d) many varied examples
27. 27.True or false: “examples of every type” is good for training a model. (a) False (b) True
28. 28.Which of these is good for training a model? (a) labels added at random (b) wrong labels (c) correct labels (d) very few examples
29. 29.Which of these is good for training a model? (a) wrong labels (b) examples of every type (c) very few examples (d) testing on training data
30. 30.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
31. 31.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
32. 32.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) True (b) False
33. 33.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
34. 34.🧠 Machine learning is a way for computers to… (a) charge faster (b) print pages (c) clean screens (d) learn from data
35. 35.True or false: “only one kind of example” is bad for training a model. (a) False (b) True
36. 36.🔍 Which is the odd one out? (a) labels added at random (b) photos in many lights (c) blurry, unclear photos (d) wrong labels
37. 37.True or false: “checking labels twice” is good for training a model. (a) False (b) True
38. 38.Which of these is good for training a model? (a) new data for testing (b) wrong labels (c) very few examples (d) testing on training data
39. 39.🏷️ 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
40. 40.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) False (b) True

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