Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 278 · 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.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
3. 3.🏷️ 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
4. 4.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True
5. 5.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) True (b) False
6. 6.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) not spam (b) spam
7. 7.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it may get it wrong (b) it will shut down (c) it will be perfect (d) it will turn yellow
8. 8.🏷️ 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
9. 9.🏷️ 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
10. 10.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
11. 11.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
12. 12.Which of these is bad for training a model? (a) many varied examples (b) only one kind of example (c) correct labels (d) examples of every type
13. 13.Which of these is good for training a model? (a) many varied examples (b) copies of one photo (c) very few examples (d) testing on training data
14. 14.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a song about dogs (c) a list of rules only (d) many labelled photos
15. 15.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
16. 16.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
17. 17.🔍 Which is the odd one out? (a) blurry, unclear photos (b) many varied examples (c) very few examples (d) labels added at random
18. 18.True or false: “wrong labels” is good for training a model. (a) True (b) False
19. 19.True or false: “clear, sharp examples” is good for training a model. (a) False (b) True
20. 20.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
21. 21.Which of these is good for training a model? (a) blurry, unclear photos (b) labels added at random (c) very few examples (d) checking labels twice
22. 22.🔍 Which is the odd one out? (a) checking labels twice (b) new data for testing (c) photos in many lights (d) very few examples
23. 23.🧠 Machine learning is a way for computers to… (a) print pages (b) clean screens (c) charge faster (d) learn from data
24. 24.🔍 Which is the odd one out? (a) new data for testing (b) only one kind of example (c) labels added at random (d) testing on training data
25. 25.Which of these is good for training a model? (a) labels added at random (b) blurry, unclear photos (c) new data for testing (d) wrong labels
26. 26.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) True (b) False
27. 27.🏷️ 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
28. 28.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
29. 29.True or false: “correct labels” is good for training a model. (a) False (b) True
30. 30.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
31. 31.📚 Good or bad for training a model: new data for testing? (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 “not spam”. (a) True (b) False
33. 33.True or false: “photos in many lights” is good for training a model. (a) True (b) False
34. 34.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
35. 35.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
36. 36.True or false: “checking labels twice” is bad for training a model. (a) True (b) False
37. 37.🔍 Which is the odd one out? (a) very few examples (b) labels added at random (c) clear, sharp examples (d) only one kind of example
38. 38.Which of these is good for training a model? (a) correct labels (b) labels added at random (c) very few examples (d) only one kind of example
39. 39.📚 Usually, more good examples make a model… (a) slower to switch on (b) forget everything (c) better at its task (d) change colour
40. 40.🏷️ What is a “label” in machine learning? (a) the right answer tag (b) the price (c) a sticker on a laptop (d) the font size

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