Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 576 · 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.🔍 Which is the odd one out? (a) checking labels twice (b) labels added at random (c) clear, sharp examples (d) many varied examples
2. 2.🏷️ 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
3. 3.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it will turn yellow (c) it will shut down (d) it may get it wrong
4. 4.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
5. 5.🏷️ 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
6. 6.🧠 Machine learning is a way for computers to… (a) clean screens (b) learn from data (c) charge faster (d) print pages
7. 7.🏷️ 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
8. 8.True or false: “labels added at random” is good for training a model. (a) False (b) True
9. 9.🔍 Which is the odd one out? (a) clear, sharp examples (b) wrong labels (c) labels added at random (d) copies of one photo
10. 10.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
11. 11.🔍 Which is the odd one out? (a) very few examples (b) many varied examples (c) correct labels (d) photos in many lights
12. 12.Which of these is bad for training a model? (a) clear, sharp examples (b) examples of every type (c) copies of one photo (d) new data for testing
13. 13.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) False (b) True
14. 14.True or false: “wrong labels” is bad for training a model. (a) False (b) True
15. 15.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) False (b) True
16. 16.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
17. 17.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
18. 18.True or false: “correct labels” is bad for training a model. (a) False (b) True
19. 19.Which of these is good for training a model? (a) many varied examples (b) very few examples (c) testing on training data (d) only one kind of example
20. 20.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True
21. 21.Which of these is bad for training a model? (a) very few examples (b) photos in many lights (c) checking labels twice (d) examples of every type
22. 22.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) False (b) True
23. 23.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) not spam (b) spam
24. 24.Which of these is good for training a model? (a) very few examples (b) labels added at random (c) clear, sharp examples (d) testing on training data
25. 25.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) True (b) False
26. 26.Which of these is good for training a model? (a) labels added at random (b) very few examples (c) blurry, unclear photos (d) photos in many lights
27. 27.🏷️ 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
28. 28.📚 Usually, more good examples make a model… (a) better at its task (b) change colour (c) slower to switch on (d) forget everything
29. 29.True or false: “copies of one photo” is bad for training a model. (a) True (b) False
30. 30.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) False (b) True
31. 31.Which of these is bad for training a model? (a) clear, sharp examples (b) new data for testing (c) wrong labels (d) examples of every type
32. 32.Which of these is good for training a model? (a) wrong labels (b) copies of one photo (c) new data for testing (d) only one kind of example
33. 33.🔍 Which is the odd one out? (a) correct labels (b) examples of every type (c) clear, sharp examples (d) wrong labels
34. 34.Which of these is good for training a model? (a) labels added at random (b) only one kind of example (c) very few examples (d) checking labels twice
35. 35.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) spam (b) not spam
36. 36.🔍 Which is the odd one out? (a) correct labels (b) testing on training data (c) wrong labels (d) very few examples
37. 37.🏷️ 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
38. 38.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
39. 39.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
40. 40.🔍 Which is the odd one out? (a) correct labels (b) new data for testing (c) many varied examples (d) only one kind of example

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