Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 496 · 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 of these is bad for training a model? (a) many varied examples (b) checking labels twice (c) correct labels (d) only one kind of example
2. 2.🏷️ 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
3. 3.🏷️ 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
4. 4.🔍 Which is the odd one out? (a) wrong labels (b) checking labels twice (c) photos in many lights (d) new data for testing
5. 5.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) spam (b) not spam
6. 6.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it may get it wrong (c) it will turn yellow (d) it will shut down
7. 7.🧠 Machine learning is a way for computers to… (a) clean screens (b) learn from data (c) print pages (d) charge faster
8. 8.Which of these is bad for training a model? (a) clear, sharp examples (b) checking labels twice (c) many varied examples (d) testing on training data
9. 9.True or false: “copies of one photo” is bad for training a model. (a) True (b) False
10. 10.🔍 Which is the odd one out? (a) photos in many lights (b) wrong labels (c) only one kind of example (d) very few examples
11. 11.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
12. 12.True or false: “many varied examples” is good for training a model. (a) False (b) True
13. 13.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) True (b) False
14. 14.True or false: “correct labels” is bad for training a model. (a) False (b) True
15. 15.True or false: “many varied examples” is bad for training a model. (a) True (b) False
16. 16.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) spam (b) not spam
17. 17.🔍 Which is the odd one out? (a) correct labels (b) labels added at random (c) testing on training data (d) very few examples
18. 18.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
19. 19.🔍 Which is the odd one out? (a) checking labels twice (b) copies of one photo (c) photos in many lights (d) new data for testing
20. 20.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) True (b) False
21. 21.🏷️ 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
22. 22.Which of these is bad for training a model? (a) checking labels twice (b) correct labels (c) labels added at random (d) many varied examples
23. 23.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) a list of rules only (c) one single photo (d) a song about dogs
24. 24.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the font size (c) the right answer tag (d) the price
25. 25.📚 Usually, more good examples make a model… (a) better at its task (b) change colour (c) slower to switch on (d) forget everything
26. 26.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
27. 27.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
28. 28.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
29. 29.True or false: “clear, sharp examples” is bad for training a model. (a) False (b) True
30. 30.True or false: “copies of one photo” is good for training a model. (a) True (b) False
31. 31.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
32. 32.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
33. 33.Which of these is good for training a model? (a) new data for testing (b) very few examples (c) labels added at random (d) wrong labels
34. 34.🔍 Which is the odd one out? (a) blurry, unclear photos (b) new data for testing (c) labels added at random (d) testing on training data
35. 35.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) False (b) True
36. 36.🔍 Which is the odd one out? (a) checking labels twice (b) examples of every type (c) testing on training data (d) correct labels
37. 37.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
38. 38.🏷️ 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
39. 39.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) False (b) True
40. 40.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) False (b) True

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